MPC Tally API Server
remote-capable server
The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.
Integrations
Used as the underlying technology for building the API server that interacts with the Tally API
Used as the programming language for building the MCP server that interacts with the Tally API
MPC Tally API Server
A Model Context Protocol (MCP) server for interacting with the Tally API. This server allows AI agents to fetch information about DAOs, including their governance data, proposals, and metadata.
Features
- List DAOs sorted by popularity or exploration status
- Fetch comprehensive DAO metadata including social links and governance information
- Pagination support for handling large result sets
- Built with TypeScript and GraphQL
- Full test coverage with Bun's test runner
Installation
Configuration
- Create a
.env
file in the root directory:
- Get your API key from Tally
⚠️ Security Note: Keep your API key secure:
- Never commit your
.env
file - Don't expose your API key in logs or error messages
- Rotate your API key if it's ever exposed
- Use environment variables for configuration
Usage
Running the Server
Claude Desktop Configuration
Add the following to your Claude Desktop configuration:
Available Scripts
bun run clean
- Clean the build directorybun run build
- Build the projectbun run start
- Run the built serverbun run dev
- Run in development mode with auto-reloadbun test
- Run testsbun test --watch
- Run tests in watch modebun test --coverage
- Run tests with coverage
API Functions
The server exposes the following MCP functions:
list_daos
Lists DAOs sorted by specified criteria.
Parameters:
limit
(optional): Maximum number of DAOs to return (default: 20, max: 50)afterCursor
(optional): Cursor for paginationsortBy
(optional): How to sort the DAOs (default: popular)- Options: "id", "name", "explore", "popular"
License
MIT
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A server that allows AI agents to interact with the Tally API to access DAO governance data, proposals, and metadata using Model Context Protocol (MCP), built with TypeScript and GraphQL.