claude-engineering-coach
An MCP server plugin for Claude Code that analyzes local AI session logs to provide coaching on coding patterns, tool usage, and productivity insights via tools and slash commands.
README
claude-engineering-coach
A native Claude Code plugin that coaches you on your AI-assisted coding —
without leaving the Claude Code terminal. Get usage summaries, anti-pattern
coaching, tool comparisons, and flow analysis via MCP tools and /coach:*
slash commands. (It can still read Codex / OpenCode / Copilot sessions too, but it
runs inside Claude Code.)
Local-only · read-only · zero telemetry.
Reuses the analytics core of Microsoft's AI Engineering Coach — but that is a VS Code / GitHub Copilot extension. This one is built for Claude Code: it ships as a Claude Code plugin, so the coaching lives where you already work. MIT-licensed. Not affiliated with, sponsored by, or endorsed by Microsoft. See
NOTICE.
What it does
It reads your on-disk AI session logs (e.g. ~/.claude/projects/**/*.jsonl) and
turns them into actionable coaching:
/coach:summary— sessions, output, and your top anti-patterns/coach:improve— prioritized, evidence-backed recommendations/coach:compare— your AI tools side-by-side (sessions, LOC, models, cancel rates)/coach:flow— deep-work scores, best hours, session continuity
Claude can also call the underlying tools on its own — just ask "how was my coding this week, and what should I improve?"
Nothing leaves your machine: the server parses your logs in-process, redacts secrets before any output reaches the model, and never writes to your session files.
Install
Requires Node ≥ 18 (the bundled MCP server runs with node). No npm install
needed — the server bundle and rule assets are committed.
Easiest — install straight from GitHub (no local path)
In an interactive Claude Code session:
/plugin marketplace add nnhhoang/claude-engineering-coach
/plugin install coach@devempower-coach
/reload-plugins
Here marketplace add points at the GitHub repo (owner/repo), so there is
no folder path to fill in. The marketplace name devempower-coach is read from
.claude-plugin/marketplace.json; you use it in the install coach@devempower-coach
step. Choose a scope when prompted (Local is fine for yourself).
Local dev — clone and load directly
git clone https://github.com/nnhhoang/claude-engineering-coach.git
cd claude-engineering-coach
claude --plugin-dir .
The . means "this folder" — nothing to fill in. Loads the plugin (commands +
MCP server) for that session only.
Note: an earlier draft showed
/plugin marketplace add /path/to/claude-engineering-coach. That/path/to/...was just a placeholder for "wherever you cloned it" — the two methods above avoid it entirely (one usesowner/repo, the other uses.).
Verify
/mcp
You should see the coach server connected with 13 tools. Then run:
/coach:summary
MCP tools (13)
coach_summary, coach_activity, coach_credits, coach_codeProduction,
coach_flow, coach_patterns, coach_insights, coach_wellbeing,
coach_workflows, coach_harnessComparison, coach_sessions,
coach_contextHealth, and coach_reload (re-read logs after new sessions).
When no date range is given, tools default to the last 90 days. Pass
fromDate / toDate (ISO YYYY-MM-DD) to widen or narrow.
How it works
core/ vendored analytics (parsers, analyzers, 45 rule + 10 metric .md)
└─ formatters.ts pure formatter functions
mcp/
├─ tool-defs.ts 12 tools (+ 90-day default + secret redaction)
├─ analyzer-cache.ts lazy, cached Analyzer over parseAllLogs(findLogsDirs())
├─ server.ts MCP stdio server (list / call / reload)
└─ dist/server.mjs committed esbuild bundle (+ rules/ + metrics/ assets)
commands/ /coach:summary · improve · compare · flow
.claude-plugin/ plugin.json + marketplace.json
.mcp.json registers the bundled "coach" server
The analytics engine is reused verbatim from upstream (it was already VS Code-free).
Only the integration layer (mcp/) and packaging are new.
Rebuild after changing mcp/** or re-vendoring core/
npm install # first time only
npm run build # → mcp/dist/server.mjs (+ copies rule/metric assets)
npm test # core-smoke, tool-defs, analyzer-cache, server.e2e
The build commits its output (mcp/dist/) so the plugin runs on a fresh clone
with only node.
Attribution & license
This project vendors the analytics core of
microsoft/ai-engineering-coach
(MIT). Vendored files under core/ keep their original Microsoft copyright
headers; see NOTICE and VENDOR.md for the exact upstream commit.
Licensed under the MIT License. Not affiliated with Microsoft.
推荐服务器
Baidu Map
百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
Playwright MCP Server
一个模型上下文协议服务器,它使大型语言模型能够通过结构化的可访问性快照与网页进行交互,而无需视觉模型或屏幕截图。
Magic Component Platform (MCP)
一个由人工智能驱动的工具,可以从自然语言描述生成现代化的用户界面组件,并与流行的集成开发环境(IDE)集成,从而简化用户界面开发流程。
Audiense Insights MCP Server
通过模型上下文协议启用与 Audiense Insights 账户的交互,从而促进营销洞察和受众数据的提取和分析,包括人口统计信息、行为和影响者互动。
VeyraX
一个单一的 MCP 工具,连接你所有喜爱的工具:Gmail、日历以及其他 40 多个工具。
graphlit-mcp-server
模型上下文协议 (MCP) 服务器实现了 MCP 客户端与 Graphlit 服务之间的集成。 除了网络爬取之外,还可以将任何内容(从 Slack 到 Gmail 再到播客订阅源)导入到 Graphlit 项目中,然后从 MCP 客户端检索相关内容。
Kagi MCP Server
一个 MCP 服务器,集成了 Kagi 搜索功能和 Claude AI,使 Claude 能够在回答需要最新信息的问题时执行实时网络搜索。
e2b-mcp-server
使用 MCP 通过 e2b 运行代码。
Neon MCP Server
用于与 Neon 管理 API 和数据库交互的 MCP 服务器
Exa MCP Server
模型上下文协议(MCP)服务器允许像 Claude 这样的 AI 助手使用 Exa AI 搜索 API 进行网络搜索。这种设置允许 AI 模型以安全和受控的方式获取实时的网络信息。