Skip to main content
Glama
Nutrition MCP
by ronkommoji

Related Servers

Alternatives to Nutrition MCP

No user-submitted related servers found.

    Related Servers

    • F
      license
      Not graded
      quality
      C
      maintenance
      Offline MCP server for logging workouts, tracking dietary macros, and retrieving daily summaries, all stored in local SQLite. Enables fitness tracking via natural language in MCP-compatible clients.
      -
    • F
      license
      A
      quality
      D
      maintenance
      A local, JSON-first calorie and protein tracker for agents and shell workflows, providing a CLI and MCP server for meal tracking, goal management, and summaries with SQLite storage.
      11
      -
    • A
      license
      A
      quality
      A
      maintenance
      Unofficial, self-hosted MCP server that connects Claude or ChatGPT to your own FatSecret food diary. It drafts entries from a description, a plate photo or a nutrition label, saves them only after you confirm, and changes or removes entries the same way. It also reads a day or several weeks against your calorie and macro targets.
      2
      5
      147 PyPI
      6
      MIT
    • A
      license
      Not graded
      quality
      D
      maintenance
      A Model Context Protocol (MCP) server that connects AI assistants to your MyFitnessPal data, enabling reading food diaries, nutrition goals, weight measurements, and more via MFP's web scraping.
      MIT
    • F
      license
      Not graded
      quality
      B
      maintenance
      An MCP server that turns an LLM into a nutrition assistant with persistent, database-backed memory, enabling conversational food logging with structured confirmation, accurate macro tracking, and multi-user support.
      -
    • A
      license
      Not graded
      quality
      D
      maintenance
      MCP server for personal nutrition tracking, enabling users to log meals with calories and macros, water intake, body weight, set goals, and import food diaries from other apps through natural language.
      44 npm
      MIT