Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者提供的说明(英文原文)
Mines your Claude Code and Cursor sessions into evidence-based CLAUDE.md / AGENTS.md rules.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"context-autopilot": {
"command": "npx",
"args": [
"-y",
"context-autopilot"
]
}
}
}在终端中运行这条命令
claude mcp add context-autopilot -- npx -y context-autopilot粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"context-autopilot": {
"command": "npx",
"args": [
"-y",
"context-autopilot"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"context-autopilot": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"context-autopilot"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日
注册名称已通过 GitHub 账户 ChiragBachani 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(0.6.0)于4个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。
同一分类中有:Spec Driven Development, Remote Desktop Commander, Agent Data Tools: Utilities
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
103 tools: JSON repair, CSV, hashes, cron, dates, units, validators. 25 free calls.
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
Automated context collection for coding agents. Mines your real agent sessions — every instruction you repeated, every correction you made, every tool call you rejected — and distills them into CLAUDE.md / AGENTS.md rules you approve.
Part of The Context Layer.
Run in your terminal (it's a plain CLI — don't paste this into a chat):
$ npx context-autopilot scan
Scanned 3 session(s) for ~/projects/my-app Found 26 signal(s):
[CORRECTION] ×2 across 2 session(s) (score 9) "There are still so many buttons that dont work, like the publish…" [REPEATED] ×4 across 3 session(s) (score 10) "Do not reference the legacy directory. Only work within…"
$ npx context-autopilot distill
[1/8] Perform click-and-type tests before reporting UI work complete (confidence: high)
$ npx context-autopilot apply
Every session starts blank, so you re-teach your agent the same conventions — and when you forget, it repeats the same mistakes. Hand-writing context files works but nobody keeps them current. And naive auto-generation is worse: research on LLM-generated context files found they *reduce* task success and raise cost, because repo scans produce generic filler.
Context Autopilot takes a third path: evidence. Your session history is a literal record of what the agent got wrong and what you said to fix it. Autopilot mines that record and only proposes rules your own words support — each one shipped with the quotes that justify it.
ctxlayer scan parses your local Claude Code transcripts (~/.claude/projects) and Cursor sessions and extracts three signal types: instructions repeated across sessions, corrections after the agent went wrong, and rejected tool calls. Runs 100% locally.ctxlayer distill sends the signals (not your history) through Claude — via your existing claude CLI, no API key needed — and gets back imperative, project-specific rules with evidence and confidence ratings.ctxlayer apply walks you through each proposal. Accepted rules land in a managed block:<!-- ctxlayer:begin -->
Hand-written content is never touched; re-runs update the block idempotently. Rules are written to both CLAUDE.md and AGENTS.md, so Claude Code, Cursor, Copilot, Codex, and every AGENTS.md-aware agent benefits.
npm install -g context-autopilot # or use npx, no install
| Command | What it does |
|---|---|
ctxlayer projects | List projects with observable session history (Claude Code + Cursor) |
ctxlayer scan | Mine signals from this project's sessions |
ctxlayer distill | Distill signals into proposals (.ctxlayer/proposals.json) |
ctxlayer promote | Scan every project's saved memory (auto-memory + CLAUDE.md) for rules that belong in your global ~/.claude/CLAUDE.md; --dry-run lists candidates without calling a model |
ctxlayer apply | Review proposals interactively; write accepted ones |
ctxlayer check | Fast, model-free: how many new signals since the last distill? --hook prints a nudge only past --threshold (default 3), else stays silent |
ctxlayer stale | Find context-file references the repo has outgrown — missing files, removed npm scripts. Exits 1 on findings, so it drops straight into CI |
ctxlayer export | Export distilled entries as Agent Operating Procedure JSON |
ctxlayer distill --global
Project context files hold repo conventions — but some feedback is about *you*: "explain things in plain English", "don't build while I'm brainstorming", "run independent work in parallel". Global mode mines all your projects across all your tools for exactly that, and maintains a managed block in your personal ~/.claude/CLAUDE.md, so every future session in every project starts already knowing how you like to work. Rules that mention a specific project are excluded by design — those belong in the project's own context file.
ctxlayer promote
Where global mode mines your *session transcripts*, promote mines the memory your agents have already written down: each project's auto-memory files (~/.claude/projects/ /memory/) and each repo's CLAUDE.md/AGENTS.md. Rules about how you work — or rules duplicated in two or more projects — are proposed for your global ~/.claude/CLAUDE.md, generalized and with the source files as evidence. Additive only: project files are read, never edited. Anything already covered globally is filtered before the model is even called.
Options: --project , --global, --source claude-code|cursor|all, --model , --min-score , --yes, --json.
Cursor session mining reads Cursor's local SQLite storage via Node's built-in node:sqlite (Node 22+; on older Node the Cursor source is skipped gracefully).
/plugin marketplace add chiragbachani/context-autopilot
/plugin install context-autopilot@the-context-layer
Then ask Claude to "update project context from my session history" — or don't ask at all: the plugin ships a SessionStart hook that runs ctxlayer check (fast, no model call) when a session begins. If enough new signals have accumulated since the last distillation, Claude gets a nudge to offer distillation at a natural pause. No new signals → complete silence.
{
"mcpServers": { "context-autopilot": { "command": "npx", "args": ["-y", "-p", "context-autopilot", "ctxlayer-mcp"] } } }
Exposes list_observable_projects, scan_context_signals, distill_context_proposals, distill_global_context, promote_to_global, apply_context_proposals, and find_stale_context.
The approval loop closes entirely inside chat: distill tools return each proposal with its evidence and instruct the agent to ask you which to accept; apply_context_proposals then writes exactly the titles you approved, remembers the ones you rejected (never re-proposed), and leaves the rest pending. No tool ever touches a context file without your explicit decision.
How is this different from Claude Code's `/insights`? /insights is the same core observation — instructions you repeat belong in CLAUDE.md — shipped as a personal usage *report*: an HTML page with suggestions you copy-paste by hand, Claude Code only. Context Autopilot is the pipeline version: it also mines Cursor history, attaches your verbatim quotes as evidence to every rule, runs an explicit approve/reject flow, writes accepted rules into managed blocks in both CLAUDE.md *and* AGENTS.md (so Codex/Copilot/Cursor benefit), maintains a global cross-project rules file, and adds a CI staleness check. Fully open source and local.
How is this different from Claude Code's auto-memory? Auto-memory captures what the model notices *live, in the moment*, in one harness. Autopilot is retroactive and systematic: it mines months of existing history across tools, and finds cross-session patterns (you said it 6× in 4 sessions) that no single live session can see.
Everything runs on your machine. Transcripts are parsed locally; only the extracted signals (short quotes of your own instructions) are sent to the model you already use for coding. Nothing is uploaded anywhere else, ever.
Coding agents are chapter one. The engine is source-agnostic — it distills *observations of work* into Agent Operating Procedures (AOPs):
--global); staleness detection (ctxlayer stale)MIT © The Context Layer