
Coach Mcp
io.github.snoozelieb由 GitHub 帳號 snoozelieb 發布v1.4.0更新於 Nov 7, 2026
Adaptive AI training coach MCP server backed by Garmin Connect
概覽
本機 MCP 伺服器,讓助理以 Garmin Connect 的真實資料擔任訓練教練,開立受負荷與傷害規則約束的訓練計畫。
- 可以做什麼
- 讀取 Garmin 資料:體能指標、各項運動歷史、強度、準備度、個人紀錄與活動區間
- 規劃訓練:每週計畫、多週訓練方案、課表預覽、週期化階段,並把結構化訓練推送到手錶
- 管理運動員資料:個人檔案、FTP 與閾值配速、基準與體能歷史更新、新手引導
- 處理賽事、肌力訓練與傷害,包括傷害診斷與狀態更新
- 保存教練記憶:決策、運動員回饋、異常處理與待核准提案
- 產生簡報與簽到,並提供規劃、回顧與教練準則的提示詞與資源
- 適用情境
- 適合已在 Garmin Connect 記錄訓練、希望助理依實際歷史開立計畫、遵守負荷與傷害限制,並在多次對話間記住過去教練決策的耐力運動愛好者。
- 執行需求
- 透過 uvx 或 pip 在本機執行(需 Python 3.12+),也可從原始碼執行。需要免費的 Garmin Connect 帳號,並設定環境變數 GARMIN_EMAIL 與 GARMIN_PASSWORD;可選用 COACH_DATA_DIR 指定資料存放位置。需要 Claude Code、Claude Desktop 或 Cursor 等 MCP 用戶端,且須先以安裝精靈建立運動員檔案,規劃類工具才能使用。
安裝
在 SourceWeft 中
- 開啟 儀表板中的 Coach Mcp,將其新增到工作區。
- 為需要使用其工具的對話啟用該服務。
Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。
其他 MCP 客戶端
參照 儲存庫 中的啟動說明。
README
coach-mcp
An opinionated AI training coach as an MCP server. It pulls your real data from Garmin Connect and prescribes with authority — science-based load management (ACWR), code-enforced injury gates (the server rejects plans that violate an active injury restriction, no matter what the LLM says), and persistent coaching memory so decisions, rationale, and your adaptation patterns survive between conversations. It will tell you "no" when your enthusiasm exceeds your capacity.
All health data and credentials stay on your machine — see Security & Privacy.
Quickstart
You need Python 3.12+, a free Garmin Connect account, and an MCP client (Claude Code, Claude Desktop, or Cursor).
Option A: uvx (recommended)
No install step — your MCP client runs the server on demand:
Jump to Connect your MCP client and use uvx as
the command.
Option B: from source
Connect your MCP client
The server needs two environment variables: GARMIN_EMAIL and
GARMIN_PASSWORD. Optional: COACH_DATA_DIR (where your coaching data lives);
COACH_TOKEN_DIR, COACH_TRANSPORT and COACH_CODE_MODE are covered under
Security & Privacy and Advanced.
From a source checkout, a .env file works too.
To run the server or the helpers from a terminal, set the two variables in that shell first. PowerShell and bash quote differently:
Claude Code
Or in .mcp.json (Claude Code expands ${VAR} from your shell environment,
so a committed file holds no secret):
Running from source instead: claude mcp add coach-mcp -- python /full/path/to/coach-mcp/server.py
Claude Desktop
In claude_desktop_config.json (Settings → Developer → Edit Config):
Cursor
In .cursor/mcp.json (project) or ~/.cursor/mcp.json (global):
If you installed with pip install garmin-coach-mcp instead of uvx, use
"command": "garmin-coach-mcp" with no args in any of the blocks above.
First run
-
Create your profile. Run the interactive wizard (installed copies have the console script; a source checkout can run the script):
Until a profile exists the server runs in setup mode: plan, program and push writes answer
setup_requiredand name the data directory they looked in.It creates your athlete profile, training config, and empty plan/memory files in the data directory. Alternatively, create the two required files by hand and let the coach fill in the rest via conversation:
-
Pull your Garmin baseline. In your MCP client, say:
"Run refresh_athlete_baseline and set up my training."
The coach pulls your name, weight, age, HR data, and training capacity from Garmin, then starts the onboarding conversation — goals, constraints, injury history, race calendar.
-
Garmin MFA / expired session. Garmin logins are token-cached. If tools start returning
AUTH_REQUIRED, recover with:It does a fresh credential login, prompts for the MFA code if Garmin asks, and saves new tokens. Restart the MCP server afterwards.
How it works
- Snapshot first — every coaching conversation starts from
get_coaching_snapshot(): current time context, 7-day week grid (rest days explicit), fitness metrics, plan adherence, open anomalies, injuries, sleep gate. - Load hierarchy before prescribing — overall ACWR (injury gate, 0.8–1.3 sweet spot), then sport-specific ACWR (spike detection), then sport-specific CTL (race readiness).
- Hard gates are code, not vibes —
update_weekly_planandpush_plan_to_garminreject sessions that violate an active injury's restricted activities, and every non-rest session must carry apurposeor the save is refused. Multi-week programs (training_program) are rejected if their starting capacity contradicts your actual history. - Grounded in what you've actually done — prescriptions are anchored to
your demonstrated per-sport capacity from recent sessions, not template
numbers; a weekly plan that outruns that history comes back with
grounding_warnings. - Curiosity with memory — planned-vs-actual anomalies (missed session, type mismatch, activity on a rest day) register once with a lifecycle (open → asked → resolved); the coach asks you what happened instead of silently assuming.
- Everything persists — decisions, approvals, adaptation patterns, and season lifecycle (race debriefs, phase transitions) live in local JSON and carry across sessions.
MCP surface
52 tools — you don't call them directly; the coach uses them during conversation:
Every tool carries MCP annotations (read-only / destructive / idempotent / open-world), enforced by tests.
6 prompts: weekly_planning, morning_brief, injury_assessment,
week_review, onboarding, race_program.
6 resources: coach://athlete/profile, coach://plan/current,
coach://config/training, coach://coaching/decisions, coach://context/now,
coach://coaching/doctrine (the long-form coaching doctrine).
Security & Privacy
Everything stays on your machine:
- Credentials:
GARMIN_EMAIL/GARMIN_PASSWORDlive in your MCP client config or a local.env. Garmin OAuth tokens are cached in a local token store (.garth/in a source checkout, a per-usergarmin-tokensdirectory for installed copies; override withCOACH_TOKEN_DIR). - Health data: all coaching data (profile, plans, fitness history, sleep, coaching memory) is local JSON in your data directory. There is no backend, no telemetry, no analytics.
- What leaves your machine: requests to Garmin's own API (your credentials/tokens, sent only to Garmin); whatever your MCP client sends to its LLM as part of the conversation; optional public web-page fetches when the coach researches a race, injury, or exercise. Nothing else: the FastMCP startup banner that would check PyPI for updates is disabled.
- Single athlete per data directory by design. For multiple athletes, run
separate server instances with separate
COACH_DATA_DIRs.
See SECURITY.md for details and how to report issues.
Data directory
Resolution order: COACH_DATA_DIR env var → data/ in a source checkout → a
per-user data directory (created on first run for installed packages). The
only file shipped with the package is methodology.json (safety rules, race
templates, personas); everything personal is created locally and never
committed.
Advanced
Architecture
coach/server.py registers tools from the coach/ package (11 tool modules, pure
parsers, a typed pydantic storage layer, CTL/ATL/ACWR fitness math, a Garmin
client with token-first auth, and a workout builder that pushes structured
workouts to your watch). The project went through a five-phase modernization —
auth rebuild, schema layer, hard gates, sectioned snapshot, packaging — whose
full history and rationale live in
docs/UPGRADE_ROADMAP.md. Development conventions
are in CLAUDE.md.
Acknowledgements
All Garmin Connect access — login, MFA, token handling, activity and health data, and workout upload — runs on python-garminconnect by Ron Klinkien (@cyberjunky) and its contributors (MIT). coach-mcp wouldn't exist without it.
License
來源:README.md,提交 7fb4163
工具
0版本歷史
2- v1.3.0Oct 26, 2026
- v1.0.0Sep 16, 2026
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