About thinkrun
ThinkRun is an MCP server and CLI for controlling real Chrome and recording browser sessions for AI coding agents. It packages clicks, console and network activity, narration, and screenshots as structured context, with shareable reports in Markdown or JSON.
Key features
- 01Control real Chrome sessions
- 02Record synchronized browser activity
- 03Capture clicks, console, and network
- 04Generate structured session reports
- 05Share reports as Markdown or JSON
- 06Six portable agent skills
Use cases
- 01Give an agent context for a browser bug
- 02Verify UI changes with before-and-after captures
- 03Browse and extract information programmatically
- 04Create structured UX audit reports
MCP support
ThinkRun exposes browser-control and session-recording capabilities through an MCP server that can be added to MCP clients. A native host enables control of real Chrome, including its existing cookies and sessions.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMEThinkRun — Screen Recorder for AI Coding Agents
Stop screenshotting bugs and typing paragraphs to explain them. ThinkRun records any browser session — or lets your agent record what it built — and turns it into structured context your AI coding agent can act on: every click, the console, network requests, your voice narration, and screenshots, all time-synced. Not just a screenshot. Not just a video.
Works with Claude Code, Cursor, Cline, Windsurf, and any MCP client.
Install
npx @thinkrun/mcp
Or install the CLI globally:
npm install -g @thinkrun/cli
The CLI automatically installs the native host binary, which lets AI tools control Chrome.
Add to your MCP config
{
"mcpServers": {
"thinkrun": {
"command": "npx",
"args": ["@thinkrun/mcp"]
}
}
}
Config location:
- Claude Code:
~/.claude/settings.json - Cursor:
.cursor/mcp.json - Cline: VS Code settings → Cline MCP Servers
Then ask your agent: "navigate to localhost:3000 and screenshot the checkout page" — or record the bug yourself and hand the agent the result.
Why ThinkRun
Other tools give your agent eyes. ThinkRun gives it structured sight — context it can parse in one pass instead of you re-explaining the page.
| ThinkRun | Playwright MCP | |
|---|---|---|
| Records a session into structured, replayable context | ✅ | ❌ drive-only |
| Turns a recording into an AI-ready report (clicks, console, network) | ✅ | ❌ |
| Shareable link, also as LLM-ready Markdown / JSON | ✅ | ❌ |
| Uses your real Chrome — your cookies & sessions | ✅ | ❌ headless only |
| Runs alongside your browser, no profile conflict | ✅ | ❌ fights for Chrome profile |
Agent skills for Claude Code, Cursor, Codex & Gemini CLI
Six portable agent skills ship in this repo, mirrored for every major harness (.claude/skills/, .cursor/skills/, .codex/skills/, .gemini/skills/):
- prove-it — the prove step of a software-factory workflow: named test targets in, a pass/fail table with a screenshot, console and network capture per target out, posted to the PR; any non-pass row sends the change back to build.
- before-after — the ship step: two captures at the same viewport, one
| Before | After |table for the PR, no public paste host. - web-browse — browse the web programmatically: drive a real or cloud browser to navigate, interact, extract, and screenshot.
- ux-audit — walk through a product UI as a real user, screenshot every step, and produce a structured UX report with a prioritized fix list.
- thinkbrowse-cli — drive the browser from shell scripts via the
thinkrunCLI. - thinkbrowse-mcp — drive the browser through the ThinkRun MCP server's tools.
Install without cloning — the repo is served as a live MCP server that auto-updates on every commit:
{ "mcpServers": { "thinkrun-skills": { "url": "https://mcp.skillsovermcp.com/mcp/dundas/thinkrun" } } }
Trigger accuracy is measured, not claimed. Every skill ships a 20-query trigger-eval fixture, and evals/BENCHMARK.md publishes the results: with the six-skill catalog (v4, 2026-09-18), 120/120 on GPT-5.6-terra and Claude Fable 5 and 113/120 on Claude Sonnet 5 (its documented strict-MCP reading, not a crash); the earlier four-skill matrix scored 79–80/80 on 12 of 16 model configurations. Catalog-ablation runs show the browsing skills absorb each other's traffic when installed as a subset, and that prove-it fills a gap rather than duplicating a sibling (before-after folds into prove-it when absent). Reproduce with bun evals/run-eval.ts build.
Manual binary install
If you need to install the native host without the CLI, download the binary for your platform from the latest release and run:
chmod +x thinkbrowse-host-* && ./thinkbrowse-host-* --install
The native host binary keeps the
thinkbrowse-hostfilename for now — it's the same signed binary, unchanged by the rename.
FAQ
How do I give Claude Code (or Cursor) access to my browser?
Add ThinkRun as an MCP server — npx @thinkrun/mcp — and your agent can drive and read a real Chrome session, your cookies and logins included. See "Add to your MCP config" above.
How do I show Cursor a UI bug instead of pasting a screenshot?
Record the bug with ThinkRun. Instead of a flat image, your agent gets a structured artifact — the steps you took, the console errors, the failing network requests, and the DOM state at the moment it broke — so it fixes the actual problem instead of guessing from a picture.
Is there an MCP server that uses my real Chrome cookies and sessions?
Yes. ThinkRun runs against your real Chrome via a native host, so authenticated pages just work — no headless re-login, no separate profile, no fighting your browser for the Chrome profile.
How do I record a browser session for an AI coding agent?
Run npx @thinkrun/mcp (or npm i -g @thinkrun/cli) and record any session — or let the agent record what it built. ThinkRun turns it into an AI-ready report (clicks, console, network, narration, screenshots, all time-synced), available as a shareable link and as LLM-ready Markdown/JSON.
How do I give my AI coding agent context about what went wrong?
Hand it a ThinkRun recording. The structured "what happened" — actions, first bad signal, expected vs actual, and the element state — is exactly the context an agent needs to land a fix on the first try.
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From what the protocol is to installing your first server, these answers cover most first questions.
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