Progressive in-context technical coaching in your AI agent — one local, free lesson per task.
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io.github.UltimaPhoenix/devcoach is an MCP server that progressive in-context technical coaching in your AI agent — one local, free lesson per task. Its tool list has not been published yet over stdio, sse and http, requires no API key, and scores 85/100 on MCPpedia's security, maintenance and efficiency rubric.
Config is the same across clients - only the file and path differ.
{
"mcpServers": {
"devcoach": {
"args": [
"-y",
"devcoach",
"mcp"
],
"type": "stdio",
"command": "npx"
}
}
}Are you the author?
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Progressive in-context technical coaching in your AI agent — one local, free lesson per task.
This server supports HTTP transport. Be the first to test it - help the community know if it works.
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No known CVEs.
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Stay sharp while your AI does the work.
devcoach connects to Claude Code, Claude Desktop, Gemini CLI (beta), Codex CLI (beta), Cursor, Windsurf, and other MCP-compatible tools. When your agent finishes a task, devcoach teaches you one thing from it that you don't know yet: it keeps a map of what you already know precisely so it can skip it, and pitches each lesson at your level — no generic tutorials, no repeated topics, nothing to open.
Everything runs locally. No data leaves your machine. One SQLite file at ~/.devcoach/coaching.db.
Built on the official Model Context Protocol TypeScript SDK, Node's embedded
node:sqlite, Hono (web dashboard), and Commander (CLI). Requires Node.js ≥ 24.
AI agents now write much of our code — which makes it easy to ship more while understanding less. devcoach turns the tasks your agent finishes into short, in-context lessons on what you don't know yet, so you keep learning as you go. The deeper bet: as AI grows more capable, the scarce skill becomes validating what it produces — and that ability only survives if you keep practicing it.
flowchart TD
A([Task completed]) --> B{"stop-hook:<br/>paced + rate limit ok?"}
B -->|not yet| Z(["Silent — counter +1"])
B -->|due| C["Cue: activate the devcoach skill"]
subgraph skill["devcoach skill"]
C --> D{"Technical work?"}
D -->|no| S[skip_lesson]
D -->|yes| E[Select topic & depth]
E --> G[log_lesson]
G --> F[Print lesson card]
end
S --> Y(["Silent — pacing re-armed"])
F --> H(["Done — counter reset"])
F -.->|prompts| U(["You: ✅ / 💡 / ❌"])
→ Full decision flow: session startup · lesson selection · depth calibration
Everything stays on your machine. No telemetry, no accounts, no calls home. Just one SQLite file.
devcoach runs locally — a stdio MCP server that stores everything in ~/.devcoach/coaching.db on the machine where your agent runs. It works in Claude Code, Claude Desktop, Gemini CLI (beta), and Codex CLI (beta), but not on claude.ai web (which only supports hosted/remote connectors).
Requires Node.js ≥ 24 (devcoach uses the embedded node:sqlite module, available only from Node 24 onward).
Pick by how you like to work — each section is self-contained (install and connect):