WakaTime MCP Server

WakaTime MCP Server

Provides access to WakaTime coding analytics data through MCP tools. Enables querying coding stats, activity summaries, project lists, and time tracking information from your WakaTime account.

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README

WakaTime MCP Server

A Model Context Protocol (MCP) server that provides high-signal coding analytics from your WakaTime data.

  • Direct mode: FastMCP serves Streamable HTTP at http://localhost:8000/mcp
  • Proxy mode: mcp-proxy exposes the server over SSE/HTTP and Caddy adds token auth (recommended for self-hosting)

Tooling / API

Tool Purpose Key arguments
get_coding_stats Detailed stats for a period range (last_7_days, last_30_days, last_6_months, last_year, all_time)
get_summary Activity breakdown for a date/range start_date, end_date, project
get_all_time Total coding time since account creation project (optional)
get_status_bar Current day status (like editor status bar) (none)
list_projects List/search tracked projects query (optional)

Configuration

Configure via environment variables (or a .env file for the self-hosted scripts).

Variable Description Required
WAKATIME_API_KEY Your API key from https://wakatime.com/settings/api-key Yes
MCP_AUTH_KEY Token for auth proxy (proxy/self-hosted mode) Proxy mode
PORT Direct-mode port (default: 8000) No

Development (Direct mode)

  1. Install (uv required)

    git clone https://github.com/dpshade/wakatime-mcp.git
    cd wakatime-mcp
    
    uv sync --no-install-project
    
  2. Run

    WAKATIME_API_KEY="your_wakatime_api_key_here" uv run -- python src/server.py
    
  3. Connect

    • URL: http://localhost:8000/mcp
    • Auth: none

Deployment

Option 1: Self-hosted with auth (recommended)

This mode runs the MCP server with FastMCP’s default stdio transport and uses mcp-proxy to expose it over HTTP:

Internet -> (optional Tailscale Funnel) -> Caddy (auth) -> mcp-proxy -> FastMCP (stdio)
                                   :8770         :8767
  1. Configure

    cp .env.example .env
    # Edit .env: set WAKATIME_API_KEY and a strong MCP_AUTH_KEY
    
  2. Download Caddy (auth proxy)

    curl -L https://github.com/caddyserver/caddy/releases/latest/download/caddy_linux_amd64 -o deploy/caddy
    chmod +x deploy/caddy
    
  3. Start

    ./deploy/start.sh
    
  4. Endpoints

    • Auth proxy (recommended):
      • SSE: http://localhost:8770/sse
      • Streamable HTTP: http://localhost:8770/mcp
    • Internal (no auth; do not expose publicly):
      • SSE: http://localhost:8767/sse
      • Streamable HTTP: http://localhost:8767/mcp

mcp-proxy also exposes a health endpoint at http://localhost:8767/status (and via auth proxy at http://localhost:8770/status).

Systemd (persistent)

./deploy/install-systemd.sh
sudo systemctl enable --now mcp-wakatime mcp-wakatime-auth

Optional: Tailscale Funnel

If you use Tailscale, you can publish the auth proxy port:

tailscale funnel --bg --set-path=/wakatime localhost:8770
tailscale funnel --bg 443 on

Option 2: Docker

Runs mcp-proxy + the server in a container.

cd deploy
docker-compose up -d
  • Endpoint (no auth): http://localhost:8767/sse
  • If you want auth, run Caddy on the host (or add it to your own compose stack) and proxy to 8767.

Option 3: Render

This repo includes render.yaml for deploying the direct Python server.

  • Set environment variable: WAKATIME_API_KEY
  • Your service endpoint will be: https://<your-service>/mcp

Client setup

MCP Inspector

npx @modelcontextprotocol/inspector

Then connect using:

  • Direct mode: http://localhost:8000/mcp (Streamable HTTP)
  • Proxy mode: http://localhost:8770/sse (SSE)

Poke / other hosted clients (proxy mode)

Use the auth proxy SSE endpoint and send MCP_AUTH_KEY via one of:

  • Authorization: Bearer <MCP_AUTH_KEY>
  • X-API-Key: <MCP_AUTH_KEY>
  • Api-Key: <MCP_AUTH_KEY>

Security notes

  • Generate a strong auth key:
    openssl rand -hex 32
    
  • Never expose the unauthenticated mcp-proxy port (8767) to the public internet.

License

MIT

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