Skip to main content
Yanked

This release has been yanked by its maintainers, and will be ignored by installers, except when explicitly specified.

Fartlek

A coach's morning report from your Garmin data, for any LLM via MCP.

Every other Garmin MCP server hands the LLM a filing cabinet of raw JSON — one night of sleep is ~52K tokens, one activity stream ~155K. The model can't read it, so it skims and improvises. Fartlek does the synthesis server-side: computed sports-science metrics (CTL/ATL/TSB, ACWR, monotony, calibrated training load), personal baselines with significance floors, safety alerts — delivered as compact, verdict-first reports the model can actually reason about.

The token contract (v0.1): calling every tool in the catalog once, at default arguments, costs under 9K tokens — a sixth of one raw Garmin sleep payload. Excluding the garmin_raw escape hatch, the whole synthesis surface sums to under 4K. Hard caps are enforced per response by the renderer, with disclosed truncation.

Status: v0.1 (Phase 1). 8 synthesis tools; the trend suite (weekly review, multi-week load, fitness/race outlook, recovery audit) ships with v0.2. Design: docs/DESIGN.md · plan: ROADMAP.md · contributors: docs/HANDOFF.md.

The tools

Tool What it answers Cap
garmin_brief "How am I today — can I train hard?" Fused GREEN/AMBER/RED verdict vs your own baselines 600
garmin_activities Browse the log, get activity IDs 1,300
garmin_activity One session in depth: reps, fade, comparison to your most similar past session 1,000–4,000
garmin_athlete Reference card: zones, PRs, goal, data coverage 600
garmin_set_profile Tell it your goal race / phase / availability (local only) 200
garmin_log Log RPE, wellness, illness/injury — the athlete outranks the sensors 120
garmin_sync Force refresh / deepen history backfill 150
garmin_raw Bounded, compacted escape hatch to named raw sources 5,000

First call on a fresh install runs the cold start automatically (~30 API calls, ≈1 minute): 180 days of history, warm CTL/ATL from day 0, then background sleep/HRV backfill.

Quickstart

Install with either:

# uv (recommended) — runs without cloning
uvx fartlek-mcp

# or pipx
pipx install fartlek-mcp

Or clone and run from source (requires Python ≥ 3.12 and uv):

git clone https://github.com/matisdsp/fartlek && cd fartlek
uv sync

# One-time Garmin login (email/password + MFA if enabled).
# Credentials are never stored; OAuth tokens go to ~/.fartlek/tokens/.
uv run fartlek auth

# Optional but recommended: warm the local store now instead of on first use
uv run fartlek sync --nights 60

uv run fartlek doctor   # check everything is healthy

Then point your MCP client at the server.

Any MCP-compatible client works — the server speaks standard JSON-RPC over stdio, so it is client-agnostic. The snippets below are just the per-client config formats; Claude Desktop, Claude Code, Cursor, Continue, Cline, Windsurf, Zed, VS Code (Copilot Chat), and Gemini CLI all work. The universal invocation is uvx fartlek-mcp.

Claude Code — from this directory, .mcp.json is picked up automatically. From anywhere else:

claude mcp add fartlek -- uvx fartlek-mcp

Claude Desktop — claude_desktop_config.json:

{
  "mcpServers": {
    "fartlek": {
      "command": "uvx",
      "args": ["fartlek-mcp"]
    }
  }
}

Cursor — .cursor/mcp.json, same command/args block as above.

Continue / Cline / Windsurf / Zed — same pattern: wherever the client keeps its MCP server list, add a fartlek entry with command: "uvx", args: ["fartlek-mcp"]. Most editors adopt the Claude Desktop format verbatim.

Any other stdio MCP client — invoke the server binary directly:

fartlek-mcp          # speaks JSON-RPC over stdin/stdout

Ask things like "can I go hard today?", "analyze my last run", "how did I sleep this week?" — and tell it how sessions felt: your reported RPE and illness notes gate the readiness verdict.

Docker

Build and run locally:

docker build -t fartlek-mcp .
# Tokens and store are persisted in ./fartlek-data on the host
mkdir -p fartlek-data
docker run -i --rm -v "$PWD/fartlek-data:/data" fartlek-mcp

For fartlek auth, run it interactively once to populate the volume, then use the image as the MCP server:

docker run -it --rm -v "$PWD/fartlek-data:/data" --entrypoint fartlek fartlek-mcp auth

CLI

Command What it does
fartlek auth one-time Garmin Connect login (MFA supported), tokens stored locally
fartlek sync [--nights N] manual sync (tier 0+1, optional N-night sleep/HRV backfill)
fartlek doctor check tokens, Garmin connectivity, local store health
fartlek accounts list local accounts
fartlek export [dir] export the store (consistent SQLite snapshot + CSV per table)
fartlek reset wipe all local tokens and data (asks confirmation)

Environment: GARMINTOKENS overrides the token location, FARTLEK_HOME the data directory (default ~/.fartlek).

Releasing to PyPI (maintainers)

Releases are published via trusted publishing (OIDC) — no API tokens anywhere.

  1. On pypi.org → Account settings → Publishing → add a GitHub publisher:
    • PyPI project name: fartlek-mcp · owner: matisdsp · repo: fartlek
    • Workflow: release.yml · environment: pypi
  2. Bump version in pyproject.toml, commit, then tag and push:
git tag v0.1.0 && git push origin v0.1.0

The release workflow builds, runs tests, and uploads to PyPI. A published version can't be overwritten — to fix a mistake, bump to the next patch (0.1.1).

Privacy

Local-first: stdio transport, your credentials and health data never leave your machine. The server only talks to Garmin's API with your own tokens, sequentially and rate-limited. fartlek export gives you everything; fartlek reset removes everything.

License & trademark

MIT. Fartlek is an independent open-source project, not affiliated with, endorsed by, or sponsored by Garmin Ltd. "Garmin" is used only to describe compatibility with Garmin Connect data.

Metadata

Release files for fartlek-mcp 0.2.2

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Built distribution (wheel)

Table of built distributions (wheels) for fartlek-mcp 0.2.2
File Interpreter ABI Platform
fartlek_mcp-0.2.2-py3-none-any.whl Python 3 none any Details

Release files / fartlek_mcp-0.2.2-py3-none-any.whl

Download URL fartlek_mcp-0.2.2-py3-none-any.whl
Size 201.8 kB
Tags Python 3
SHA-256 checksum
How to use checksums
0645734e296b7ae80b1ebefb90f993752c046f8a4937ef2b9fe4cc682cb0e87b
BLAKE2b-256 checksum
How to use checksums
2412929c920f80420d2078fe73aed0fec955ea0553a5f91463217bbc2c6a2e23
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via uv/0.11.32 {"installer":{"name":"uv","version":"0.11.32","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

Security for fartlek-mcp 0.2.2

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page