Skip to main content

Beeminder MCP Server

Project description

MCP Beeminder Server

This project implements a Model Context Protocol (MCP) server for interacting with the Beeminder API.

Beeminder MCP Server

What is MCP?

The Model Context Protocol (MCP) is an open protocol that standardises how applications provide context to Large Language Models (LLMs). It acts like a "USB-C port for AI applications" - providing a standardised way to connect AI models to different data sources and tools.

MCP follows a client-server architecture where:

  • MCP Hosts: Programs like Claude Desktop or IDEs that want to access data through MCP
  • MCP Clients: Protocol clients that maintain 1:1 connections with servers
  • MCP Servers: Lightweight programs that expose specific capabilities through the standardised protocol
  • Local Data Sources: Your computer's files, databases, and services that MCP servers can securely access
  • Remote Services: External systems available over the internet that MCP servers can connect to

What is Beeminder?

Beeminder is a tool for overcoming akrasia (acting against your better judgment) by combining:

  • Quantified self-tracking
  • Visual feedback via a "Bright Red Line" (BRL) showing your commitment path
  • Financial stakes that increase with each failure
  • Flexible commitment with a 7-day "akrasia horizon"

This server implementation provides MCP-compatible access to Beeminder's API, allowing AI assistants to help users manage their Beeminder goals, datapoints, and other related functionality.

Features

The server provides access to core Beeminder functionality including:

  • Goal management (create, read, update, delete)
  • Datapoint management (create, read, delete)
  • User information retrieval
  • Support for all Beeminder goal types:
    • Do More ("hustler")
    • Odometer ("biker")
    • Weight Loss ("fatloser")
    • Gain Weight ("gainer")
    • Inbox Fewer ("inboxer")
    • Do Less ("drinker")

Running locally with the Claude Desktop app

Prerequisites

You'll need your Beeminder API key and username to run the server. To get your API key:

  1. Log into Beeminder
  2. Go to https://www.beeminder.com/api/v1/auth_token.json

You'll also need uv installed. See the uv docs for installation instructions. You can use something else but you'll need to change the command in the claude_desktop_config.json file.

Manual Installation

  1. Clone this repository.
  2. Add the following to your claude_desktop_config.json file:
  • On MacOS: ~/Library/Application\ Support/Claude/claude_desktop_config.json
  • On Windows: %APPDATA%/Claude/claude_desktop_config.json
"mcpServers": {
  "beeminder": {
    "command": "uv",
    "args": [
      "--directory",
      "/path/to/repo/mcp-beeminder",
      "run",
      "mcp-beeminder"
    ],
    "env": {
        "BEEMINDER_API_KEY": "YOUR_BEEMINDER_API_KEY,
        "BEEMINDER_USERNAME": "YOUR_BEEMINDER_USERNAME"
    }
  }
}
  1. Install and open the Claude desktop app.
  2. Try asking Claude to do a read/write operation of some sort to confirm the setup (e.g. list your Beeminder goals). If there are issues, use the Debugging tools provided in the MCP documentation here.

Acknowledgements

Thanks to @ianm199 for his beeminder-client package, on which this project is based.

And obviously thanks to the Beeminder team for building such a great product!

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

iflow_mcp_mcp_beeminder-0.1.0.tar.gz (203.6 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

iflow_mcp_mcp_beeminder-0.1.0-py3-none-any.whl (13.4 kB view details)

Uploaded Python 3

File details

Details for the file iflow_mcp_mcp_beeminder-0.1.0.tar.gz.

File metadata

File hashes

Hashes for iflow_mcp_mcp_beeminder-0.1.0.tar.gz
Algorithm Hash digest
SHA256 383a59889c65d81de31d68fc79a5e55e2bc29b8b297b440e9d57e1b9645afee3
MD5 40521dd6283624672edf37d0428c953e
BLAKE2b-256 5a21b666a83194066730ba32d99338e0a661b09d79d3a2bad0e9ac8789e057a8

See more details on using hashes here.

File details

Details for the file iflow_mcp_mcp_beeminder-0.1.0-py3-none-any.whl.

File metadata

File hashes

Hashes for iflow_mcp_mcp_beeminder-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 b600b38889e554a4ec3d5a6174912b8ef1ab6cfd469cbbd218e1f21a299908a1
MD5 51f65091466b0e4f087636cbfac35b00
BLAKE2b-256 2d73f328fb9d1d13012d5d4a111cd34a77b398e52a64102eb299596aece1be4a

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page