Context7
Up-to-date docs for AI agents
Descripción del creador (original en inglés)
Log MyFitnessPal by talking to your AI: search foods with macros, log meals, weight, water and more.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
MFP_COOKIE, MFP_USERNAMELos valores marcados como secretos son llaves de tu cuenta. Nunca los compartas ni los pegues en un chat.
Necesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"mfp": {
"command": "uvx",
"args": [
"mfp-mcp"
],
"env": {
"MFP_COOKIE": "your-value",
"MFP_USERNAME": "your-value"
}
}
}
}Ejecuta esto en tu terminal
claude mcp add mfp --env MFP_COOKIE=your-value --env MFP_USERNAME=your-value -- uvx mfp-mcpCompleta los valores vacíos antes de ejecutarlo.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"mfp": {
"command": "uvx",
"args": [
"mfp-mcp"
],
"env": {
"MFP_COOKIE": "your-value",
"MFP_USERNAME": "your-value"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"mfp": {
"type": "stdio",
"command": "uvx",
"args": [
"mfp-mcp"
],
"env": {
"MFP_COOKIE": "your-value",
"MFP_USERNAME": "your-value"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
MFP_USERNAME envEsta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 7 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub Mason-Levyy, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
Debes completar: MFP_COOKIE
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (0.5.0) llegó al registro hace 4 días.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Python (uv) en tu computadora.
En la misma categoría: Context7, Codebase Memory, Exa
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
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Connect AI agents to Exa for web search, content fetching, and multi-step research.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
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
Solo se muestra el principio; lee el resto en el repo