mcp-server-personal
Personal-assistant MCP server for managing personal data including calendar events, emails (read/label only), and contacts via local files or Gmail IMAP.
README
mcp-server-personal
Personal-assistant MCP server for personal data. Part of the personal-assistant
project; built with FastMCP + Starlette + streamable-http, with per-domain
register_tools_* modules.
MCP endpoint: http://localhost:8002/mcp
Tools
| Tool | Backend | Config needed |
|---|---|---|
get_calendar_events(start, end) / add_calendar_event(...) |
local data/calendar.ics |
no |
list_emails(n, unread_only) / read_email(id) / label_email(id, label) |
Gmail IMAP + app password | IMAP creds |
add_contact / mark_contacted / list_contacts_dates() |
local SQLite | no |
Todos and long-term preference memory live in the main app, not in this server. Email is read + label only — sending is deliberately not an MCP tool; drafts go through the assistant's approval card and a separate gated send path.
Run
cp .env.example .env # fill IMAP creds if you want email tools
uv sync
uv run src/run.py
Inspect tools:
npx @modelcontextprotocol/inspector
# connect to http://localhost:8002/mcp (streamable-http)
# if ENABLE_AUTH=true, add header: Authorization: Bearer <MCP_AUTH_TOKEN>
Test with the AI agent (LangChain agent over this server's tools):
export OPENAI_API_KEY=sk-... # or set it in .env
uv run ai_agent.py # example question
uv run ai_agent.py "add lunch with Alex to my calendar this Saturday at noon"
ai_agent.py automatically sends the bearer token from MCP_AUTH_TOKEN when set.
Authentication
The MCP endpoint is protected by a static bearer token (Starlette
AuthenticationMiddleware + PersonalAuthBackend in src/auth/auth.py):
ENABLE_AUTH=true+MCP_AUTH_TOKEN=<random>in.env— clients must sendAuthorization: Bearer <token>; anything else gets401.ENABLE_AUTH=false— open access (local development).
Generate a token with openssl rand -hex 24.
Observability
- Tracing: OpenTelemetry spans per request (
ENABLE_TRACE;TRACE_SPAN_TYPE=localprints to console,otlpexports to a collector). - Logging: console + rotating file (
app.log, 1 MB x 3) viaLOG_LEVELandLOG_PATH. All tool failures are logged with tracebacks — start withgrep WARNING app.log/grep ERROR app.logwhen a tool misbehaves.
Tests
uv run pytest tests -v
Docker
docker build -t mcp-server-personal .
docker run --rm -p 8002:8002 --env-file .env mcp-server-personal
Multi-stage build, non-root user, prod dependencies only; state
(calendar.ics, personal.db, logs) lives in /app/data.
CI/CD
.github/workflows/ci.yaml— on PRs and pushes tomain:uv sync+pytest, then a Docker build (no push)..github/workflows/cd.yaml— manual (workflow_dispatch): builds and pushesghcr.io/<owner>/mcp-server-personal:<version>using the built-inGITHUB_TOKEN, with atest/prodenvironment choice.
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