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제작자가 쓴 설명(영어 원문)
Log MyFitnessPal by talking to your AI: search foods with macros, log meals, weight, water and more.
이 세 가지는 절대 하나의 점수로 합치지 않아요. 의견, 측정, 인기는 서로 다른 것이니까요.
이 서버는 아직 쉬운 말로 된 요약을 쓰지 못했어요. 아래는 레지스트리에서 읽어 온 사실이에요.
쓰고 있는 AI 앱을 고른 다음 설정을 복사하세요.
MFP_COOKIE, MFP_USERNAME비밀로 표시된 값은 내 계정의 열쇠예요. 절대 다른 사람과 공유하거나 채팅에 붙여 넣지 마세요.
필요한 것
어떤 앱을 쓰세요?
위에서 앱을 고르세요. 기억해 두었다가 다음부터는 버튼에 “…에 설치”라고 표시해요.
Claude Desktop → Settings → Developer → Edit Config를 열고 claude_desktop_config.json에 이 내용을 붙여 넣으세요
{
"mcpServers": {
"mfp": {
"command": "uvx",
"args": [
"mfp-mcp"
],
"env": {
"MFP_COOKIE": "your-value",
"MFP_USERNAME": "your-value"
}
}
}
}터미널에서 이 명령어를 실행하세요
claude mcp add mfp --env MFP_COOKIE=your-value --env MFP_USERNAME=your-value -- uvx mfp-mcp실행하기 전에 빈 값을 채워 주세요.
프로젝트의 .cursor/mcp.json 또는 ~/.cursor/mcp.json에 붙여 넣으세요
{
"mcpServers": {
"mfp": {
"command": "uvx",
"args": [
"mfp-mcp"
],
"env": {
"MFP_COOKIE": "your-value",
"MFP_USERNAME": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
프로젝트의 .vscode/mcp.json에 붙여 넣으세요
{
"servers": {
"mfp": {
"type": "stdio",
"command": "uvx",
"args": [
"mfp-mcp"
],
"env": {
"MFP_COOKIE": "your-value",
"MFP_USERNAME": "your-value"
}
}
}
}브라우저가 앱을 열지 물어본 다음, 앱이 설정을 보여 주고 확인을 요청해요. 키 값은 비워 두니 직접 입력하세요.
이 서버는 내 컴퓨터에서 실행되는데, ChatGPT는 인터넷에 있는 서버에만 연결할 수 있어요. 다른 앱을 고르세요.
선택한 앱은 이 기기의 쿠키에만 저장돼요. 계정은 필요 없어요.
MFP_USERNAME env이 설정은 제작자의 레지스트리 정보로 만들었어요. README와 다르면 README를 따르세요.
내 컴퓨터에서 실행돼요. 설치하면 AI 앱에 도구 목록이 나타나요.
누구나 볼 수 있는 정보를 점검했고, 코드는 읽지 않았어요. 해당하지 않는 항목은 개수에서 뺐어요. · 2026년 11월 7일 점검
레지스트리 이름이 GitHub 계정 Mason-Levyy 기준으로 확인되었고, 이 계정이 저장소를 소유하고 있어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
아직 GitHub에서 이 저장소를 읽어 오지 않았어요
내 컴퓨터에서 실행되는 서버라 인터넷 엔드포인트가 없어요
내 컴퓨터에서 실행되며, 대신 로컬 설정을 사용해요
내 컴퓨터에서 실행돼요. 도구 목록은 인터넷 엔드포인트가 있는 서버에서만 읽을 수 있어요
레지스트리에서 이 카테고리의 활성 서버 전체와 비교했어요. 스타는 게시자가 저장소를 소유한 경우에만 세요.
해당하는 기본 점검 1개 중 1개를 통과했어요. 코드는 읽지 않았어요. 키나 토큰을 넣기 전에 서버가 어떤 권한을 요구하는지 확인하고, 꼭 필요한 권한만 있는 키를 쓰세요.
입력해야 할 값: MFP_COOKIE
내 컴퓨터에서 실행돼요. AI 앱이 필요할 때 실행하고, 데이터는 제작자의 서버를 거치지 않아요(서버 자체가 온라인 서비스를 호출하는 경우는 제외).
GitHub 저장소는 마지막으로 – 변경됐고, 최신 버전(0.5.0)은 4일 전 레지스트리에 올라왔어요.
Claude Desktop, Claude Code, Cursor, VS Code처럼 MCP를 지원하는 앱에서 쓸 수 있어요. 내 컴퓨터에 Python (uv)도 있어야 해요.
같은 카테고리에는: Context7, Codebase Memory, Exa
같은 카테고리에서 다른 제작자가 만든 서버예요. 스타 순으로 정렬했어요.
카드 보는 법:★ GitHub 스타i세 기둥: 리뷰 · 점검 · 사용 정도i업데이트 = 최신 버전을 레지스트리에 공개한 날i
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제작자의 저장소에서 쓰인 그대로 가져왔어요. PopNx MCP가 검토하거나 보증한 내용이 아니에요. HTML, 이미지, 스크립트는 제거했어요. 링크를 누르면 이 사이트를 벗어나요.
Log MyFitnessPal by talking to your AI.
Quickstart · Tools · Authentication · Changelog
MyFitnessPal MCP is a free, open-source MCP server that connects MyFitnessPal to Claude, Cursor, VS Code, or any MCP client. Log meals by talking, search the food database with macros, track trends, and export your nutrition history, all against your real MyFitnessPal diary.
Published on PyPI as mfp-mcp and in the official MCP Registry as io.github.Mason-Levyy/mfp-mcp.
Unofficial. MyFitnessPal has no public API; this reverse-engineers the
web app's own endpoints. It can break whenever MFP changes their site. Use at
your own risk, with your own account.
MyFitnessPal moved behind Cloudflare + NextAuth, which broke the username/password login that most existing integrations rely on. This server:
uvx mfp-mcp auth
Claude Code
claude mcp add myfitnesspal -- uvx mfp-mcp
Or install it as a plugin:
/plugin install myfitnesspal-mcp --marketplace Mason-Levyy/myfitnesspal-mcp
Claude Desktop (claude_desktop_config.json), Cursor (~/.cursor/mcp.json), Windsurf (~/.codeium/windsurf/mcp_config.json), and Cline (cline_mcp_settings.json) all take the same entry:
{
"mcpServers": { "myfitnesspal": { "command": "uvx", "args": ["mfp-mcp"] } } }
VS Code, Codex CLI, Gemini CLI
VS Code (or use the button above):
code --add-mcp '{"name":"myfitnesspal","command":"uvx","args":["mfp-mcp"]}'
Codex CLI:
codex mcp add myfitnesspal -- uvx mfp-mcp
Gemini CLI:
gemini mcp add myfitnesspal uvx mfp-mcp
Requires uv. Any MCP client that speaks stdio or streamable HTTP works, not just Claude.
Finding this useful? A ⭐ on
GitHub helps other
MyFitnessPal users find it.
This server signs in with your browser's MyFitnessPal session cookie:
https://www.myfitnesspal.com__Secure-next-auth.session-tokenmfp-mcp auth prompt, or on macOS run mfp-mcp auth --clipboard and copy the cookie: it connects as soon as the token reaches the clipboardSessions last 30 days from their last renewal. The server renews the session whenever it builds a client and saves the cookies MyFitnessPal re-issues, so the saved session stays current as long as it's used at least once a month. mfp-mcp auth --check reports whether the saved session still works and whether auto-refresh is set up; it renews and saves the session as it checks and exits 1 when the session needs attention, so running it on a schedule (cron, launchd) keeps an idle session alive and warns before it lapses.
With the autorefresh extra, auth also seeds a persistent headless browser profile. When MyFitnessPal rejects the session mid-call, the server tells your client it is retrying, boots the profile headlessly, lets MyFitnessPal rotate the session token, saves the fresh cookie, and retries the call.
uvx --from 'mfp-mcp[autorefresh]' playwright install chromium
uvx --from 'mfp-mcp[autorefresh]' mfp-mcp auth
Then use the same --from 'mfp-mcp[autorefresh]' form in your client config (e.g. uvx --from 'mfp-mcp[autorefresh]' mfp-mcp).
| Tool | What it does |
|---|---|
fitness_get_day | Nutrition totals, goals and remaining macros, diary entries, the MFP daily note, and feel note for a day |
fitness_search_food | Candidate matches with brand, calories, macros, serving, and ids |
fitness_draft_food | Numbered options with every serving size, filtered/ranked by optional calorie and macro targets |
fitness_log_food | Log a draft option (and serving), a remembered food, or exact ids to the real diary |
fitness_list_food_pins | Remembered query → food/serving choices (local) |
fitness_clear_food_pin | Forget one remembered choice, or all of them |
fitness_delete_food | Remove a diary entry by name match |
fitness_modify_food | Replace an entry (or change its quantity), choosing the replacement like fitness_log_food |
fitness_complete_day | Report whether a diary day is complete, mark it complete ("Complete This Entry"), or reopen it |
fitness_log_weight | Log a weight measurement (updates the same day on re-log) |
fitness_log_water | Add water (cups, fl oz, mL, L) or set the day's total with replace |
fitness_get_exercise | Read the exercise diary (cardio + strength) |
fitness_get_exercise_entries | List cardio and strength entries with each section's columns |
fitness_delete_exercise | Remove an exercise entry by name match (all_matches for multi-row sync cleanup) |
fitness_get_note | Read the MyFitnessPal daily diary note (the "Notes" box) for a day |
fitness_log_note | Write that daily note to MFP (replace, or append a new line) |
fitness_log_feel | Save a subjective "how I feel" note (stored locally, never sent to MFP) |
fitness_get_trends | One metric over a date range: weight, calories_in, protein, carbs, fat |
fitness_bulk_export | Whole date range in one call, including goals and remaining macros |
Food logging is draft-then-confirm, so what lands in your diary never depends on MyFitnessPal's search order:
fitness_draft_food("greek yogurt", min_protein=15, max_calories=150) returns numbered options. Each lists every serving size with calories and macros for the whole entry (serving × quantity) plus a suggested serving; options that meet the targets come first, near misses follow. Call it again with different targets to refine.fitness_log_food(draft_id=..., option=2, serving=1) logs exactly that food and serving, and remembers the choice for that query.fitness_log_food(query="greek yogurt") logs the remembered food and serving without searching.A bare fitness_log_food(query=...) with nothing remembered logs only when exactly one result matches the name exactly; otherwise it logs nothing and returns a draft to choose from. Remembered choices live in the local cache (fitness_list_food_pins, fitness_clear_food_pin). Drafts expire after 24 hours.
fitness_modify_food picks the replacement the same way, before deleting anything: a remembered food or a single exact-name match is used directly; otherwise the entry is left alone and a draft comes back — call fitness_modify_food again with the same query plus draft_id and option.
fitness_log_food, fitness_delete_food, and fitness_modify_food all take a meal argument the same way: breakfast/lunch/dinner/snacks, or the literal name of any meal section currently on your diary — including a renamed default meal or one of the up to two extra meals MyFitnessPal lets you add in Diary Settings. Matching is case-insensitive against your account's current meal labels. If you renamed a default meal, the keywords still work: breakfast/lunch/dinner/snacks fall back to your first through fourth meal, unless that slot now carries a different default name (e.g. lunch won't land in a second meal you renamed to "Dinner"). Any other unrecognized meal raises an error instead of silently logging into the wrong section.
Day summaries and trends read from a local SQLite cache that gap-fills from MyFitnessPal (first call on a fresh install fetches up to 30 days, one request per day).
Water logging reads the day's current total from /food/water, adds the requested quantity, and posts the new total back to the same endpoint. Pass replace=True to set the day's total outright (e.g. to fix a mislogged amount); every call returns previous_ml, so a mistake can be reverted by passing it back as amount with unit="ml" and replace=True. The separate /stats request with a water_logged event is analytics telemetry; it does not persist the water total.
The default transp
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