{"schemaVersion":"1.0","publication":{"slug":"pivot-cursor","name":"Cursor HQ","description":"Product updates and proven workflows for building software with Cursor.","audience":"Engineers and product teams using the Cursor editor.","geography":null},"edition":{"id":"55aac043-04b8-445b-a31f-0b000d11b384","date":"2026-09-25","status":"locked","createdAt":"2026-09-24T17:52:45.211Z","storyCount":7,"newsletterSubject":"Cursor coding agent gets 7% cheaper, Zip file exploits Cursor and six tools, Blender MCP stops generic AI designs"},"updatedAt":"2026-09-24T22:30:29.757Z","stories":[{"id":"ac5afb84-da88-440b-9977-013c8655fb42","title":"Cursor's coding agent now costs 7% less to run","dek":"Cursor overhauled the harness, the code that assembles every request its AI coding agent sends to a model, cutting the tokens (the text chunks models read and charge for) it uses per task by about 7%.","bodyMd":"Cursor announced on September 23 that it had spent the past few months overhauling the harness behind its AI coding agent, cutting the tokens the agent burns per task by about 7% without making its output worse, according to a Cursor blog post. A harness is the layer of code Cursor writes around the underlying model: it decides what instructions and tools go into each request and how much of a previous turn gets reused. Tokens are the chunks of text that a model reads and that providers bill for, so fewer tokens per task means a cheaper agent run for the same amount of work.\n\nThe biggest single cut came from the system prompt, the block of standing instructions Cursor sends with every agent turn telling the model how to behave. Cursor trimmed it by roughly 66%. Older, less capable models needed long lists of \"DO NOT\" and \"you must\" rules to stop them from doing things like dumping huge hashes or spamming emojis; newer models mostly comply once a tool's behavior is simply described, so much of that boilerplate could go. Cursor says it validates these changes with A/B tests on live traffic rather than relying only on benchmark evals, which it argues skew toward harder problems than what most users actually ask for.\n\nCursor also stopped listing every one of its built-in tools in full on every request. As it added capabilities like background shell monitoring and cloud subagents over the year, tool definitions piled up even though Cursor says most individual tools get used in fewer than 20% of conversations. Earlier this year Cursor applied the same fix to external MCP tools, cutting total tokens by 46.9% in sessions that called one; it has now extended dynamic loading to its own tools, keeping only high-frequency ones like reading, searching, editing, and shell access, plus ask_question and Plan Mode's create_plan, loaded by default. That change cut the token count sitting in tool descriptions by 60%.\n\nThe rest of the savings came from caching and file-reading changes. Since OpenAI's GPT-5.6 started letting clients mark explicit \"cache breakpoints\" showing which parts of a request are safe to reuse, Cursor moved its system prompt and tool definitions ahead of those breakpoints and pushed session-specific details like skills and environment info into what it calls a \"phantom user message\" placed after them. That cut cold cache misses by 20%. Separately, Cursor's Read tool used to number every single line of code so the model could cite it back to the user; numbering only every tenth line still lets models cite code properly and shaved 1.6% off cache-read tokens.\n\nCursor also changed how its agent hands work to subagents, smaller agent instances that start fresh instead of inheriting the parent's full conversation. It removed prompting that had pushed agents toward spinning up subagents for codebase exploration, on the theory that newer models already learned that habit from training data, and it stopped subagents from switching to a different underlying model unless a user or the harness told them to.\n\nOne engineer on the project described the rollout as tricky, since token spending feeds directly into how Cursor prices its product, but said the point was protecting low prices through efficiency rather than cutting corners. Cursor frames the 7% figure as ongoing work rather than a finish line, saying it wants token use to grow more slowly than the amount of work an agent can complete, and that it is carrying the same techniques into the separate harness running its Grok Bot.","status":"published","storyType":"news","category":"Agents","clusterKey":"cursor-cuts-agent-token-costs-7-percent","slug":"cursor-cuts-agent-costs-7-by-trimming-the-instructions-it-sends-the-ai-ac5afb","url":"https://cursorhq.ai/news/cursor-cuts-agent-costs-7-by-trimming-the-instructions-it-sends-the-ai-ac5afb/","relayUrl":"https://relaygrid.com/publications/pivot-cursor/stories/ac5afb84-da88-440b-9977-013c8655fb42","role":"lead","position":0,"imageStatus":"ready","imageUrl":"https://media.pivotnews.ai/brands/cursor-hq/articles/cursor-cuts-agent-costs-7-by-trimming-the-instructions-it-sends-the-ai-ac5afb/bdb38976619f5d73-d1c944d619e7b92f/web_hero.webp","imageAlt":"A metallic server cartridge with a row of ten blocks, one of which is being removed to show a reduction in required components.","createdAt":"2026-09-24T15:57:39.448Z","updatedAt":"2026-09-24T17:00:28.195Z","sources":[{"role":"primary","title":"Cursor Cuts Agent Token Costs 7% With Smarter Context and Tool Loading","url":"https://cursor.com/blog/improved-token-efficiency","sourceName":"Cursor Blog","author":"Cursor Blog","publishedAt":"2026-09-23T12:00:00Z"},{"role":"supporting","title":"Cursor Cut Agent Token Costs With New Optimized Harness","url":"https://x.com/jediahkatz/status/2102805846438580599","sourceName":"Jediah Katz","author":"Jediah Katz","publishedAt":"2026-09-23T17:02:36Z"},{"role":"supporting","title":"Tokens now cost 7% less in Cursor thanks to harness improvements Shout out to the team for the amazing work.","url":"https://x.com/mattyp/status/2102787325327806714","sourceName":"matt palmer","author":"matt palmer","publishedAt":"2026-09-23T15:49:00Z"}]},{"id":"a21a2196-0cab-481c-a9b2-c4306b2e9ee7","title":"A zip file of code can hijack Cursor and six other AI coding tools","dek":"GitSpawn hides in .git/config, a hidden settings file that Cursor and other AI coding agents read automatically the moment a project opens, letting attacker-chosen commands run before a developer approves anything or types a single prompt.","bodyMd":"Security research firm Manifold Security disclosed GitSpawn on September 1, a class of flaw that lets a malicious project take over the background git commands run by Cursor and six other AI coding agents: Claude Code, OpenAI Codex, Goose, Qwen Code, Grok Build and Hermes. The findings span eight separate vulnerabilities across those seven tools, and two of them carry official tracking numbers, CVE-2026-72718 and CVE-2026-71963.\n\nThe background calls are routine, which is what makes the flaw dangerous. Every one of these agents runs git in the background the instant a developer opens a project folder, gathering context like commit history and branch status before the chat window even loads. Git obeys whatever settings sit in that folder's own.git/config file, a hidden configuration file that ships with every git-tracked project. Manifold Security researcher Francisco Rosales found that a project's.git/config can set values like core.fsmonitor to hijack that background call and run arbitrary commands on the developer's machine, with no warning dialog, no sandbox, and access to SSH keys, cloud credentials and every other project on the same disk.\n\nThe danger depends on how the project arrives. Cloning a project through git does not carry the same risk, because git builds a fresh local config instead of copying an attacker's settings wholesale. A project handed over as a zip file, a shared folder or a USB drive copies the exact.git/config file as it sat on the sender's machine, malicious entries included. Rosales compared it to a furniture delivery: while everyone in the house watches the crew carry a new couch into the living room, an impostor slips into another room and walks out with something valuable. That handoff is common in consultancies and technical interviews, where a client or candidate hands over a finished project as a zip instead of a repository link.\n\nHow much the developer has to do before the payload fires varies by tool. On Claude Code, Manifold Security says the payload ran before the user even accepted the workspace-trust prompt, the dialog that normally asks whether to trust a new folder. On Qwen Code it fired even without the user being logged in, and on Goose it ran at startup, launching nothing more alarming than a calculator in the researchers' proof of concept. Grok Build triggered after a user's first keystroke, and Hermes waited until the first prompt was sent, the point at which most people naturally start typing anyway.\n\nAt publication on September 1, at least four of the eight findings were still unpatched despite repeated outreach to vendors, according to Manifold Security. By the September 21 interview, Hermes had shipped a fix the day after the blog post went up and Grok Build had also patched its agent; other vendors had not, and Manifold Security says one vendor never triaged its report after six separate contact attempts. Rosales said chasing vendors took multiple tries across the board, a pattern he attributed to security teams overwhelmed by the sheer volume of reports they now receive.\n\nManifold Security's advice is procedural rather than dramatic: before pointing a coding agent at a project that arrived as a zip file, shared folder or drive rather than a git clone, check what's sitting inside its.git/config. The flaw lives in each agent's own background plumbing, not in git or in the underlying model, which is why a fix has to come from every vendor separately rather than from a single upstream patch.","status":"published","storyType":"news","category":"Ecosystem","clusterKey":"gitspawn-vulnerability-hijacks-coding-agents","slug":"a-zip-file-of-code-can-hijack-cursor-and-six-other-ai-coding-tools-a21a21","url":"https://cursorhq.ai/news/a-zip-file-of-code-can-hijack-cursor-and-six-other-ai-coding-tools-a21a21/","relayUrl":"https://relaygrid.com/publications/pivot-cursor/stories/a21a2196-0cab-481c-a9b2-c4306b2e9ee7","role":"item","position":1,"imageStatus":"ready","imageUrl":"https://media.pivotnews.ai/brands/cursor-hq/articles/a-zip-file-of-code-can-hijack-cursor-and-six-other-ai-coding-tools-a21a21/6e4d7144084b076f-9047940feabdcac9/web_hero.webp","imageAlt":"Editorial illustration accompanying “A zip file of code can hijack Cursor and six other AI coding tools”.","createdAt":"2026-09-24T15:50:59.693Z","updatedAt":"2026-09-24T16:00:24.214Z","sources":[{"role":"primary","title":"GitSpawn Vulnerability Lets Malicious Repos Hijack Claude Code and Cursor","url":"https://www.youtube.com/watch?v=Mw465Fhxqvk","sourceName":"@security-report","author":"@security-report","publishedAt":"2026-09-21T14:55:40Z"}]},{"id":"a1cc26c1-37a7-4650-a680-bfd469fb67d7","title":"A Blender MCP workflow keeps AI-designed websites from looking generic in Cursor","dek":"The technique pairs Blender, a 3D design program, with an MCP server that lets Cursor, Codex, or Claude Code drive it directly, plus two installed skills meant to teach the agent design taste.","bodyMd":"A recent walkthrough builds a \"cinematic\" Formula 1 showcase site, complete with a rotating 3D car and layered scroll effects, using an AI coding tool such as Cursor, Codex, or Claude Code alongside Blender, a 3D modeling program, and a pair of installed skills, small instruction files that give the coding agent extra guidance it doesn't have by default, meant to stop AI-built pages from looking generic. The builder says he has no design background and no prior experience with Blender.\n\n**What it does.** The workflow lets an AI coding agent design a 3D, motion-heavy website end to end, including modeling and animating 3D assets in Blender, without the person directing it ever having to learn Blender or a design tool like Figma.\n\n**How to do it**, per the walkthrough:\n\n1. Pick a coding tool with a built-in browser. Cursor, Codex, and Claude Code all qualify, and the browser matters because the agent needs to screenshot its own output and check it against references as it works.\n2. Choose a leading model for the job, since it has to handle interface design and operate Blender without breaking anything. The walkthrough names Fable 5.1, GPT-6, and Opus as strong options, and specifically warns against OpenAI's GPT-5.5 and 5.6, which it says are weak at this kind of work.\n3. Install an MCP server for Blender: a connector that lets the AI agent drive the 3D software directly, standing in for Blender knowledge the builder doesn't have.\n4. Install two \"taste\" skills, meaning two installable instruction files that give the coding agent extra design guidance it wouldn't otherwise have: a design-engineering skill built by Emil Kowalski, a former Vercel engineer, focused on animation and design cues, and a second skill also called \"taste,\" described as a bundle of multiple skills forming an anti-slop framework for AI interface design.\n5. Describe the idea loosely, not as a spec. For the F1 site, the brief was: car centered, team name text behind it, a driver on each side with names below, and three scrollable \"depth layers\" ending in a camera move around the car that stops at six parts (side pod, rear wing, power unit, halo, front suspension, front wing).\n6. Before building, gather reference screenshots. The walkthrough pulls four example layouts from Awwwards and Dribbble that share elements of the intended design, saves them to a references folder, and hands them to the agent. A vague brief like \"cinematic, premium\" means little on its own; a reference image shows the agent exactly what those words are supposed to look like.\n7. Let the browser run the check loop: the agent screenshots its own progress and compares it to the saved references to judge how close the result is, refining from there.\n\n**When it's worth using.** The walkthrough frames this specifically for sites that go beyond a flat landing page: ones involving a custom 3D asset, camera motion, or a layered scroll sequence, where a one-line prompt tends to produce something generic.\n\n**Caveats.** The walkthrough stresses that model choice matters more here than on a typical landing page, since weaker models struggle to combine interface judgment with safely operating Blender. It also cuts off before showing how the car asset itself gets generated, so the asset-creation step isn't fully covered.","status":"published","storyType":"tip","category":"Workflow","clusterKey":"cinematic-3d-websites-cursor-claude-blender-mcp","slug":"a-blender-mcp-workflow-keeps-ai-designed-websites-from-looking-generic-i-a1cc26","url":"https://cursorhq.ai/guides/a-blender-mcp-workflow-keeps-ai-designed-websites-from-looking-generic-i-a1cc26/","relayUrl":"https://relaygrid.com/publications/pivot-cursor/stories/a1cc26c1-37a7-4650-a680-bfd469fb67d7","role":"item","position":2,"imageStatus":"ready","imageUrl":"https://media.pivotnews.ai/brands/cursor-hq/articles/a-blender-mcp-workflow-keeps-ai-designed-websites-from-looking-generic-i-a1cc26/2afdf3ef7d912e30-37617a156bf10a4c/web_hero.webp","imageAlt":"A modular technical console displays a 3D car model, with two peripheral skill units attached to the sides to inject specific design instructions into the central processing hub.","createdAt":"2026-09-24T18:50:58.730Z","updatedAt":"2026-09-24T19:00:22.839Z","sources":[{"role":"primary","title":"Build Cinematic 3D Websites Using Cursor, Claude, and Blender MCP","url":"https://www.youtube.com/watch?v=kO9qN194toM","sourceName":"@janmarshalcoding","author":"@janmarshalcoding","publishedAt":"2026-09-22T15:55:35Z"}]},{"id":"02800c64-5225-4cb4-a932-89b0474495ba","title":"A free Mac app tracks AI coding costs across Cursor and roughly 35 other tools","dek":"CodeBurn reads the local session files Cursor, Claude Code and roughly 35 other AI coding tools already save automatically, then flags setup problems, like forgotten plug-ins and bloated instruction files, that burn tokens, the text chunks these models charge you for, without producing any code.","bodyMd":"CodeBurn is a free Mac app that reads the local log files Cursor, Claude Code, Codex, GitHub Copilot, Gemini CLI and roughly 35 other AI coding tools already save on your disk, then breaks your spending down by project, model, git branch and task, according to posts describing the tool on Reddit. It needs no API keys and no sign-up: nothing leaves the Mac it runs on.\n\nThe app has two main parts:\n\n- **Spend tracking.** Today's spend sits in the Mac menu bar next to the clock, and a strip called the Capacity Dock sits on the edge of the screen with one ring per AI provider, filling up toward your 5-hour and weekly usage limits so you can see them building up before a long coding session instead of after it.\n- **Optimize.** This scan goes through your Claude Code sessions and configuration looking for things that cost tokens, the chunks of text these models read and get billed for, without doing anything useful. The posts list what it checks for: MCP servers (plug-ins that connect an AI coding tool to outside data or actions) installed months ago and never called but still paid for on every request; a CLAUDE.md file, the project instructions Claude Code sends with every message, that has grown long enough to bloat each request; files the agent re-reads repeatedly in one session; unused skills, agents and commands; and sessions that keep reading build folders or retrying the same step.\n\nEach Optimize finding comes with a grade, a suggested fix and an estimated savings. For configuration issues, CodeBurn can apply the fix itself: it shows the exact change first, backs up the file, and can undo the change with one command. A few days later it rechecks your actual sessions against the estimate, and if a fix didn't help, it says so and gives you the undo command rather than just assuming the fix worked.\n\nThe pitch, per the posts, is that a monthly AI bill gives one total with no breakdown by project or model, and each tool's own dashboard (where one exists) only covers that one tool. Anyone running more than one coding tool has to add the numbers up by hand and gets no guidance on what to cut.\n\nWorth noting: the Optimize waste-finding scan is built specifically around Claude Code sessions and setup files right now, so a Cursor-only user would get the spend breakdown and capacity tracking but not necessarily the same depth of waste detection. The app is Mac-only, and the builds are signed and notarized by Apple. It's open source under the MIT license.","status":"published","storyType":"tip","category":"Ecosystem","clusterKey":"codeburn-tracks-ai-coding-costs-across-cursor","slug":"a-free-mac-app-tracks-ai-coding-costs-across-cursor-and-roughly-35-other-02800c","url":"https://cursorhq.ai/guides/a-free-mac-app-tracks-ai-coding-costs-across-cursor-and-roughly-35-other-02800c/","relayUrl":"https://relaygrid.com/publications/pivot-cursor/stories/02800c64-5225-4cb4-a932-89b0474495ba","role":"item","position":3,"imageStatus":"ready","imageUrl":"https://media.pivotnews.ai/brands/cursor-hq/articles/a-free-mac-app-tracks-ai-coding-costs-across-cursor-and-roughly-35-other-02800c/2ae608dd8e7ec533-56d352301dcdb562/web_hero.webp","imageAlt":"A metallic manifold with 36 cables feeding into a central gauge, with discarded metal shims at its base.","createdAt":"2026-09-24T20:31:04.146Z","updatedAt":"2026-09-24T21:00:26.487Z","sources":[{"role":"primary","title":"Free Mac App Tracks and Cuts AI Coding Costs Across 41 Tools","url":"https://reddit.com/r/buildinpublic/comments/1wp0nbp/oscodeburn_a_free_opensource_mac_app_that_shows","sourceName":"/u/Lucky-Group9525","author":"/u/Lucky-Group9525","publishedAt":"2026-09-24T12:44:27Z"},{"role":"supporting","title":"Free Mac App Tracks AI Coding Spend Across 41 Tools and Finds Waste","url":"https://reddit.com/r/SaaS/comments/1woob3b/oscodeburn_a_free_opensource_mac_app_that_shows","sourceName":"/u/Lucky-Group9525","author":"/u/Lucky-Group9525","publishedAt":"2026-09-24T01:26:52Z"},{"role":"supporting","title":"Free Mac App Tracks and Cuts AI Coding Costs Across 41 Tools","url":"https://reddit.com/r/macapps/comments/1wol15f/oscodeburn_a_free_opensource_mac_app_that_shows","sourceName":"/u/Lucky-Group9525","author":"/u/Lucky-Group9525","publishedAt":"2026-09-23T23:00:39Z"}]},{"id":"8719d6e1-40d7-4f7e-bc97-e65a8356579b","title":"Cursor's Composer 2.5 Fast mode trades higher cost for faster replies","dek":"A billing-data comparison found the faster setting cuts Composer 2.5's task time nearly in half while charging about 2.3 times more per token, the small chunks of text a model reads and bills for.","bodyMd":"Cursor's Composer 2.5 model ships with two speed settings, Normal and Fast, and a new billing-data comparison puts a number on the tradeoff between them: Fast finishes the same coding task in roughly half the time but charges substantially more to do it.\n\nThe test ran the identical task repeatedly, alternating between Normal and Fast. Between each run, the tester cleared the generated code, wiped the agent's context, and started a fresh chat, so neither mode carried over any advantage from the previous attempt. To measure cost, the tester skipped Cursor's published pricing table and instead checked the actual billing page, working backward from how much usage each run deducted to estimate an effective price per million tokens. Tokens are the small chunks of text, each roughly three-quarters of a word, that a model reads and generates, and that Cursor bills by the million.\n\nFast averaged 36.25 seconds per run against 62.25 seconds for Normal, a 42% cut in completion time. Token counts came out roughly the same between the two modes, but Fast's effective price ran about 2.3 times higher per token, according to the billing-based calculation.\n\nThe tester's own reason for running the comparison was personal rather than a general recommendation: with the billing cycle nearing its end and Cursor usage sitting at about 50%, he wondered whether switching from Normal to Fast on his own account would be worth it rather than letting that unused allowance go to waste. That question is what prompted the experiment, not a broader claim about when Fast suits other users.\n\nOne more wrinkle: Normal's completion times varied a lot between runs, sometimes nearly matching Fast, sometimes running well behind, while Fast stayed consistent. A post describing the test raises the possibility that Normal and Fast aren't just two execution modes but two priority levels, with Fast's requests getting served first and Normal occasionally left waiting. The post is explicit that this is a hypothesis from a small, self-run experiment, not something confirmed about how Cursor's backend actually works.","status":"published","storyType":"tip","category":"Pricing","clusterKey":"composer-2-5-fast-vs-normal-cost-test","slug":"cursor-s-composer-2-5-fast-mode-trades-higher-cost-for-faster-replies-8719d6","url":"https://cursorhq.ai/guides/cursor-s-composer-2-5-fast-mode-trades-higher-cost-for-faster-replies-8719d6/","relayUrl":"https://relaygrid.com/publications/pivot-cursor/stories/8719d6e1-40d7-4f7e-bc97-e65a8356579b","role":"item","position":4,"imageStatus":"ready","imageUrl":"https://media.pivotnews.ai/brands/cursor-hq/articles/cursor-s-composer-2-5-fast-mode-trades-higher-cost-for-faster-replies-8719d6/76ecccb347922412-e4c1f093c6ac9626/web_hero.webp","imageAlt":"A mechanical dual-chambered hourglass with a pneumatic valve separating sand of two different densities representing different task execution speeds.","createdAt":"2026-09-24T19:41:17.526Z","updatedAt":"2026-09-24T20:00:13.551Z","sources":[{"role":"primary","title":"Cursor Composer 2.5 Fast vs Normal: Speed and Cost Test Results","url":"https://reddit.com/r/cursor/comments/1wp2ped/i_compared_cursor_composer_25_normal_vs_fast","sourceName":"/u/Machine2024","author":"/u/Machine2024","publishedAt":"2026-09-24T14:10:45Z"}]},{"id":"bb91341c-8db2-4d68-9c25-bb4f44f36fc8","title":"Cursor's Cloud Agents couldn't start on Grok 4.7 or Gemini 3.8 Flash for hours","dek":"A model-not-found bug blocked Cursor's remote coding agents from launching on Grok 4.7 and Gemini 3.8 Flash starting September 22, while the editor's own chat and older models kept working.","bodyMd":"Cursor's Cloud Agents, the feature that lets developers kick off coding agents from GitHub, Slack, the web app, or Linear instead of running them locally inside the editor, stopped starting on two models this week. Beginning the morning of September 22 (UTC), any Cloud Agent that selected Grok 4.7 or Gemini 3.8 Flash failed immediately with an \"AI Model Not Found\" or \"The model you chose is not available\" error. Reports came in from the web app, the desktop client, and the API, according to a thread on Cursor's official forum.\n\nThe bug's pattern made it hard to diagnose before Cursor stepped in. One developer found that a scheduled automation's \"Run Test\" button failed every time with \"Failed to start background composer: [not_found] Error\" whenever Grok 4.7 was selected, while the identical automation, on the identical environment, ran fine on Grok 4.6. Others described a cloud chat that would start, then disappear, with the model picker silently reverting to whatever had been selected before; a separate report said Grok 4.7 worked in Cursor's \"workspaces\" but not in \"projects.\" Because the failures came in waves rather than constantly, one user noted their first Cloud Agent chat of the day worked on Grok 4.7 but a second one, run a few hours later, did not.\n\nA Cursor team member confirmed on the forum that the problem sat on Cursor's side, not in anyone's setup, and that it had already been passed to the engineering team. While a fix was in progress, Cursor pointed affected users to two workarounds: run Cloud Agents on Grok 4.6 or Auto instead of Grok 4.7, since both were working normally, or keep using Grok 4.7 in the editor's own chat window, which the team confirmed wasn't affected.\n\nCursor said a fix was rolling out later the same day and reported personally starting a Cloud Agent on Grok 4.7 successfully afterward. Another user in the thread confirmed that automation-triggered agents were starting again with Grok 4.7 selected, and thanked Cursor for the quick turnaround.\n\nOne report stayed open when the thread ended. A user said Cloud Agents had also been silently flipping their model setting from \"Grok 4.7 xhigh 256k\" to \"Grok 4.7 low 500k\" without being asked, since early the same morning, and asked Cursor's team whether that behavior was tied to the same fix. No reply to that question appears in the thread yet.","status":"published","storyType":"news","category":"Agents","clusterKey":"cursor-cloud-agents-outage-grok-gemini","slug":"cursor-s-cloud-agents-couldn-t-start-on-grok-4-7-or-gemini-3-8-flash-for-bb9134","url":"https://cursorhq.ai/news/cursor-s-cloud-agents-couldn-t-start-on-grok-4-7-or-gemini-3-8-flash-for-bb9134/","relayUrl":"https://relaygrid.com/publications/pivot-cursor/stories/bb91341c-8db2-4d68-9c25-bb4f44f36fc8","role":"item","position":5,"imageStatus":"ready","imageUrl":"https://media.pivotnews.ai/brands/cursor-hq/articles/cursor-s-cloud-agents-couldn-t-start-on-grok-4-7-or-gemini-3-8-flash-for-bb9134/f2e69afc4e264dcf-7beb0aad5276e8a5/web_hero.webp","imageAlt":"A mechanical switchboard with a disconnected bridge component on two specific pins, symbolizing a disrupted connection to specific AI models.","createdAt":"2026-09-24T22:18:58.576Z","updatedAt":"2026-09-24T22:30:22.671Z","sources":[{"role":"primary","title":"Cursor Cloud Agents Hit Outage Blocking Grok 4.7 and Gemini 3.8 Flash","url":"https://forum.cursor.com/t/grok-4-7-not-found-in-cloud-agent/172633","sourceName":"Aldino Kemal","author":"Aldino Kemal","publishedAt":"2026-09-22T11:32:51Z"}]},{"id":"0e966869-5e8a-4044-a5d2-5fee3fd4104f","title":"A new tool lets Cursor build ComfyUI image workflows without connecting each step by hand","dek":"ComfyUI normally requires dragging and linking visual building blocks called nodes on a canvas to build each image pipeline, and the open-source mcp-comfy-ui-builder now lets Cursor or Claude Desktop assemble, check and run that chain automatically from a single text prompt.","bodyMd":"ComfyUI, a popular open-source app for building AI image-generation pipelines, normally makes you drag and connect visual building blocks called nodes on a canvas by hand: one node loads a model, another applies a LoRA, another upscales the result, and you wire them together yourself before you can generate anything. A new open-source project, mcp-comfy-ui-builder, does that wiring for you. Point it at a running ComfyUI instance and you can type a request like \"generate a portrait of an astronaut exploring neon ruins with LoRA, upscale 2x\" into Cursor or Claude Desktop, and the assistant builds the node chain, runs it, and hands back the finished image.\n\nThe connection runs through MCP, the Model Context Protocol, a standard that lets AI assistants like Cursor and Claude call outside apps and tools directly instead of you copying commands between windows. The project exposes more than 50 MCP tools covering node discovery, graph construction, model management and queue inspection, along with nine built-in templates for common jobs: text-to-image, image-to-image, inpainting, upscaling, LoRA chaining, ControlNet, and batch or sequential runs. It pre-indexes 62 core ComfyUI nodes and can sync a user's custom nodes with a single `npm run sync-nodes` command.\n\nOne detail addresses a real failure mode: before running a workflow, the assistant calls a `get_system_resources` tool to check available GPU memory, so it can catch a job that would crash ComfyUI with an out-of-memory error before it starts rather than after. Execution status also streams back over WebSockets with node-by-node progress updates, which the project's developer says lands under 100 milliseconds, compared with a roughly 1.5-second HTTP polling fallback.\n\nIt's free and MIT-licensed, installable with `npm install -g mcp-comfy-ui-builder` or as a Docker image, and configured in Claude Desktop by pointing a `COMFYUI_HOST` environment variable at a local ComfyUI server. The developer's release post illustrates the workflow with a written example prompt rather than a video or screenshots, and the developer is soliciting requests for additional templates, so which workflow patterns get built-in support next will depend on what users ask for.","status":"published","storyType":"news","category":"Ecosystem","clusterKey":"open-source-comfyui-mcp-server-for-cursor-claude","slug":"a-new-tool-lets-cursor-build-comfyui-image-workflows-without-connecting-0e9668","url":"https://cursorhq.ai/news/a-new-tool-lets-cursor-build-comfyui-image-workflows-without-connecting-0e9668/","relayUrl":"https://relaygrid.com/publications/pivot-cursor/stories/0e966869-5e8a-4044-a5d2-5fee3fd4104f","role":"item","position":6,"imageStatus":"ready","imageUrl":"https://media.pivotnews.ai/brands/cursor-hq/articles/a-new-tool-lets-cursor-build-comfyui-image-workflows-without-connecting-0e9668/8e6b71a0bd7dd9c2-554e42145b6ddcd3/web_hero.webp","imageAlt":"A complex modular circuit board with nine template slots and fifty-nine pins, showing a single automatic connector bridging a gap between node blocks to initiate a workflow.","createdAt":"2026-09-24T22:04:49.174Z","updatedAt":"2026-09-24T22:30:29.757Z","sources":[{"role":"primary","title":"I built an open-source MCP server for ComfyUI — build and run workflows from Claude / Cursor with 50+ tools (demo inside)","url":"https://reddit.com/r/comfyui/comments/1wormcl/i_built_an_opensource_mcp_server_for_comfyui","sourceName":"/u/Less_Actuary_9441","author":"/u/Less_Actuary_9441","publishedAt":"2026-09-24T04:08:11Z"}]}],"tips":[{"id":"7ab55b05-0f3c-466a-b353-6fcb7c6da174","title":"Find the good edit one agent silently overwrote for another, using git log","dek":"When parallel agents work in one repo, a file committed by two different sessions within an hour is the sign that one fix may have erased another.","bodyMd":"Running several background agents (AI assistants that edit code) or chats on one repository, or Cursor beside Claude Code or Codex, carries a failure that rarely shows up as a bad edit. It shows up as a good edit that vanishes. Agent A fixes a file. Agent B, working from what it read twenty minutes earlier, rewrites the same file and commits. A's fix is gone, nothing errors, and tests may still pass.\n\nGit keeps the evidence, according to the memento team, which builds a free, MIT-licensed tracker and disclosed that interest. The overwrite leaves the same trace each time: one file, two different sessions (a different author or a different branch), commits less than an hour apart. The tool for finding it is `git log`, the command that lists a repository's commit history.\n\n**How to look**\n\n1. Pull a month of history with the session identity attached to each commit:\n `git log --all --source --since='1 month ago' --name-only --format='@%at|%an|%S'`\n Each commit prints a timestamp, author and branch, followed by its files.\n2. Pipe that into an awk filter (awk is a command-line text-processing tool) that flags any file committed by two different author/branch pairs less than an hour apart, then sort by frequency. The memento team's git log plus awk one-liner does this and prints the most frequent files first. The same check also runs in the browser in its overwrite-risk grader, and the team says the log is not uploaded.\n3. Look at the top of the list. If it is config, routes or schema files, that is where your agents collide.\n\n**Two fixes**\n\n- Give each agent its own worktree (a separate working folder checked out from the same repository), so the clash becomes a visible merge conflict instead of a silent overwrite.\n- Have an agent claim a file before it writes: append one line to a shared file under `flock`, and tell the other agents to skip claimed files.\n\n**Caveats.** The check cannot separate sessions that share one branch and one author name. A hit is also a near miss, not proof of a lost edit, so read the two diffs before concluding anything.","category":"Workflow","slug":"find-the-good-edit-one-agent-silently-overwrote-for-another-using-git-lo-7ab55b","url":"https://cursorhq.ai/guides/find-the-good-edit-one-agent-silently-overwrote-for-another-using-git-lo-7ab55b/","relayUrl":"https://relaygrid.com/publications/pivot-cursor/stories/7ab55b05-0f3c-466a-b353-6fcb7c6da174","imageUrl":"https://media.pivotnews.ai/brands/cursor-hq/articles/find-the-good-edit-one-agent-silently-overwrote-for-another-using-git-lo-7ab55b/9b0bb9ac47984186-b6371947454b2e54/web_hero.webp","imageAlt":"Two rectangular metal cartridges are forced into a single vertical slot, with the second one partially overlapping the first.","createdAt":"2026-10-29T15:55:37.440Z"},{"id":"22bfcd77-ec8c-43ee-a7a7-d7f074c74961","title":"Have a different model review your agent's PR from inside Cursor","dek":"ThinkReview's MCP server lets Cursor call a single tool on a pull request URL and get back severity-ranked findings, so the agent can fix them in the same session.","bodyMd":"A quick glossary first: a PR (pull request) is a proposed code change awaiting review, and the agent is Cursor's AI assistant that writes and edits code.\n\nThinkReview, a pull request review tool for GitHub, GitLab, Azure DevOps and Bitbucket (including self-hosted), has an MCP server that works in Cursor, Claude Code, Codex, Antigravity and Windsurf. Your agent calls one tool, `review_url_code`, with a PR or MR URL. ThinkReview fetches the diff using git credentials stored in its portal, so nothing is pasted into chat.\n\nThe result is the structured review the ThinkReview extension already returns: a summary, severity-ranked findings, security notes and a plain-language reason. Your custom rules and chosen model apply, so the review can come from a different model family than the one that wrote the code. The reasoning is that the agent is the weakest last reader of its own change, and a recap in chat can drift from what the diff actually does.\n\n## Set it up in Cursor\n\n1. Before the first review, add a git PAT under Settings → Integrations in the ThinkReview portal. Without it, private diffs can't be read.\n2. Add the server to your MCP config. The hosted endpoint is `https://mcp.thinkreview.dev/v1`, which uses browser OAuth, so no token goes in config files.\n3. Click Authenticate.\n4. Ask the agent: \"Call thinkreview for https://github.com/org/repo/pull/123\".\n5. Then run `/mcp` and authenticate.\n\nCopy-paste configs for each client are on ThinkReview's MCP setup page.\n\n## Turn it into a loop\n\nWrapping the call in a skill is the better use. A Cursor skill such as `/thinkreview-pr` can find or open the PR, call `review_url_code`, fix the critical and high findings that deserve a change, run the tests, push to the same PR and review again. The same pattern works in Claude Code and Codex through a prompt, a custom command or an agent instruction file.\n\n## When it earns its keep\n\nTwo runs on real pull requests show the kind of problem it surfaces. On one PR, the review flagged that a Google sign-in popup handler was never set up, so the window could fail to open; the Cursor agent then patched `searchConsole.js` and restored a clear message when Google rejects the account. On a billing change, the review flagged a critical issue: when a cancel call failed, the handler still returned HTTP 200, so the billing provider would not retry and a trial could stay live. Both were easy to miss in the chat summary.\n\nReach for it on agent-written branches before merge, when the summary says \"done\" and you want a reader from outside the authoring session.","category":"Workflow","slug":"have-a-different-model-review-your-agent-s-pr-from-inside-cursor-22bfcd","url":"https://cursorhq.ai/guides/have-a-different-model-review-your-agent-s-pr-from-inside-cursor-22bfcd/","relayUrl":"https://relaygrid.com/publications/pivot-cursor/stories/22bfcd77-ec8c-43ee-a7a7-d7f074c74961","imageUrl":"https://media.pivotnews.ai/brands/cursor-hq/articles/have-a-different-model-review-your-agent-s-pr-from-inside-cursor-22bfcd/e9a2f1c5685ca535-d1e1b4689b6c5f4a/web_hero.webp","imageAlt":"A metal cartridge with two glass chambers slides into a hardware dock to bridge a code agent with an external review tool.","createdAt":"2026-10-29T15:08:20.314Z"},{"id":"633ea1f3-ccdd-4279-99b0-490dd30577ff","title":"Vicem swaps unchanged function bodies for one-line stubs to slim Agent Mode's context","dek":"Vicem, a free MIT-licensed MCP server, swaps unchanged function bodies for stubs to trim the context its developer says Cursor re-sends each turn, and hands full bodies back to the agent only when needed.","bodyMd":"Agent Mode is Cursor's AI agent: it reads files, runs commands and edits code across a chat. The developer behind Vicem says it is quick in a fresh chat, but that after 20 to 30 turns of file reads and test runs the \"Planning next moves\" pause grows noticeably. They attribute it to each turn re-sending a large payload built from chat history. That is the developer's own observation, not a documented description of how Cursor works. Starting a new chat restores the speed but costs the context: which files changed, what broke, what constraints apply.\n\nVicem, an open-source tool under the MIT license, attacks the payload size. It is also an MCP server, meaning a small local program that gives the agent extra tools it can call (MCP stands for Model Context Protocol). Its developer says it runs on Node.js built-ins only, with zero npm dependencies and no network calls, and cuts tokens per turn by \"usually 55% to 78%\". Tokens are the chunks of text a model reads and is billed for.\n\n**What it trims**\n\nA function body is the code between a function's braces, the part that does the work; the signature is the line that names the function and its inputs. A stub is a short placeholder left in the body's place.\n\n- **Code skeletonizer:** keeps imports, exported types and function signatures, and replaces unchanged function bodies with a one-line stub carrying an ID, such as `{ /* vicem:fn_a8c39f (42L) */ }`.\n- **Log slimmer:** strips passing test lines and `node_modules` stack frames from terminal output, so the agent sees the failing assertions.\n- **Data diet:** condenses large JSON, CSV and SQL files into compact schemas and ignores lockfiles.\n- **Secret guard:** masks `.env` values and keys such as `sk-*`, `ghp_*` and `AKIA*` locally before they reach the prompt.\n\n**Getting bodies back**\n\nStripped blocks are stored in `.vicem/ledger.json`. Vicem registers a lightweight stdio MCP server (one that talks to Cursor over standard input and output rather than a network port) in `~/.cursor/mcp.json`, with an optional `.cursor/rules/vicem.mdc` rule. When the agent needs to read or edit a skeletonized function, it calls `vicem_rehydrate_node` and pulls back only those lines.\n\n**Carrying state into a new chat**\n\nVicem can also snapshot the workspace: it copies `state.vscdb` plus the `-wal` and `-shm` files to a temp file (so it never locks a running Cursor window), adds your git diff and recent terminal output, and writes a `BATON.md` handoff file you can use to start a fresh chat without re-explaining.\n\n**Trying it**\n\nThe code is at github.com/RAKKUNN/vicem. `npx vicem-cli gui` launches a local three-column web GUI, and a browser sandbox runs at rakkunn.github.io/vicem.\n\nThe developer built it for long sessions on larger codebases. The token savings and the explanation of the slowdown are the developer's own; the source gives no speed measurement.","category":"Workflow","slug":"vicem-swaps-unchanged-function-bodies-for-one-line-stubs-to-slim-agent-m-633ea1","url":"https://cursorhq.ai/guides/vicem-swaps-unchanged-function-bodies-for-one-line-stubs-to-slim-agent-m-633ea1/","relayUrl":"https://relaygrid.com/publications/pivot-cursor/stories/633ea1f3-ccdd-4279-99b0-490dd30577ff","imageUrl":"https://media.pivotnews.ai/brands/cursor-hq/articles/vicem-swaps-unchanged-function-bodies-for-one-line-stubs-to-slim-agent-m-633ea1/13d5362447afa6e3-56073ef165789f7d/web_hero.webp","imageAlt":"A row of document stacks, with one full stack and several others compressed into thin placeholders by metal spacer plates.","createdAt":"2026-10-29T00:20:09.117Z"},{"id":"e9e0ebc4-2dbe-4f7f-b238-896f0f17f3a1","title":"Track Cursor CLI tasks and approvals across repos from one dashboard","dek":"Denly, a web dashboard for coding agents, runs Cursor's CLI (the command-line interface, a text-based way to run the agent from a terminal) on your own machine and collects whatever needs a human decision in one place.","bodyMd":"Denly gathers the work that is waiting on you across several projects: plans to approve, questions from agents, failures and PRs ready for review. Its Cursor integration drives Cursor's CLI on your own machine, according to its developer's forum post. The CLI is the command-line interface, the text-based way to run the Cursor agent from a terminal. The tool also supports other coding-agent CLIs, so different projects can use different providers.\n\n**How the workflow runs**\n\n1. Submit a task for a project.\n2. Review the agent's proposed plan and approve it.\n3. Let the agent build and run the checks configured for that repository.\n4. Review the resulting PR, then request changes or merge.\n\n**Who it is aimed at**\n\nThe developer pitches Denly at people using Cursor across several repositories and asks for feedback on whether the workflow helps. The part the developer says they are focusing on now is coordinating work across projects and keeping track of where a person needs to step in.\n\n**Limits to know**\n\n- The runner makes outbound requests to the control service, so no port needs to be opened on your machine.\n- Your machine must be awake and online for tasks to execute.\n- Selected plans, transcripts and other content can be uploaded, so local execution does not mean everything stays local.\n- Denly has a free plan and paid tiers. You use your own agent account, with its existing limits and charges.\n\nThe developer's post links a product page at denly.dev and an illustrated demo walkthrough with sample tasks.","category":"Ecosystem","slug":"track-cursor-cli-tasks-and-approvals-across-repos-from-one-dashboard-e9e0eb","url":"https://cursorhq.ai/guides/track-cursor-cli-tasks-and-approvals-across-repos-from-one-dashboard-e9e0eb/","relayUrl":"https://relaygrid.com/publications/pivot-cursor/stories/e9e0ebc4-2dbe-4f7f-b238-896f0f17f3a1","imageUrl":"https://media.pivotnews.ai/brands/cursor-hq/articles/track-cursor-cli-tasks-and-approvals-across-repos-from-one-dashboard-e9e0eb/aecba402adeae18f-570bf920197284f3/web_hero.webp","imageAlt":"A metallic central hub with four cables connecting to four separate workstation towers, representing the coordination of multiple coding tasks in one location.","createdAt":"2026-10-28T19:11:12.546Z"},{"id":"0f97b24d-6df1-42d8-abb5-e096c1f17ea9","title":"Write a pull request prompt as a Cursor custom command in a markdown file","dek":"A markdown file in a commands folder inside the cursor folder holds a prompt that asks for a PR with a descriptive title and the GitHub CLI.","bodyMd":"Cursor custom commands are markdown files in a `commands` folder inside the cursor folder, each holding a prompt. The walkthrough's example is a command for making pull requests.\n\nA few terms in plain language:\n\n- **Markdown file:** a plain-text file, ending in `.md`, that uses simple formatting symbols.\n- **Pull request (PR):** a proposal to merge your code changes into a project so others can review them.\n- **Prompt:** the written instructions you give Cursor's AI.\n- **Command:** here, a named markdown file that holds a prompt you have written down.\n- **GitHub CLI:** GitHub's command-line tool, which can create pull requests from the terminal.\n\n**How to set it up**\n\n1. In the cursor folder, create a new folder named `commands`.\n2. Inside it, add a markdown file. The example uses `pr.md`, but the file can be named whatever you want.\n3. Put the prompt in the file. The example reads: \"Your job is to create a PR with a descriptive title. Always use the GitHub CLI.\"\n\nThe prompt text is free-form, so you decide what goes in it. The walkthrough notes you could also add specific rules or commit guidelines to the same file.\n\n**What the example shows**\n\nThe example keeps a pull request prompt in a `pr.md` file inside the `commands` folder. That prompt asks for a PR with a descriptive title and says to always use the GitHub CLI.\n\nThe source covers only the file setup and the example prompt. It does not show how the command is then invoked.","category":"Workflow","slug":"write-a-pull-request-prompt-as-a-cursor-custom-command-in-a-markdown-fil-0f97b2","url":"https://cursorhq.ai/guides/write-a-pull-request-prompt-as-a-cursor-custom-command-in-a-markdown-fil-0f97b2/","relayUrl":"https://relaygrid.com/publications/pivot-cursor/stories/0f97b24d-6df1-42d8-abb5-e096c1f17ea9","imageUrl":"https://media.pivotnews.ai/brands/cursor-hq/articles/write-a-pull-request-prompt-as-a-cursor-custom-command-in-a-markdown-fil-0f97b2/ce519ee6e9295810-7821bc6d791aef8f/web_hero.webp","imageAlt":"A metal cartridge with etched markings is shown being inserted into a slot on the side of a larger, modular hardware device.","createdAt":"2026-10-28T08:39:32.458Z"}]}