Sleeper MCP Server

A Machine Context Protocol (MCP) server for integrating Sleeper fantasy sports data with Goose AI. This server implements the MCP specification to provide structured access to Sleeper's API data.

Overview

The Sleeper MCP Server acts as a bridge between Goose AI and the Sleeper Fantasy Sports platform, implementing the Model Context Protocol (MCP) for seamless integration.

Features:

Structured access to fantasy sports data via MCP
Rate-limited API access
Data caching and optimization
OpenAPI documentation
MCP-compliant function specifications

Installation

# Clone the repository
git clone https://github.com/yourusername/sleeper-mcp.git
cd sleeper-mcp

# Install dependencies using Poetry
poetry install

# Start the server
poetry run uvicorn src.main:app

Integration with Goose

The Sleeper MCP server integrates with Goose in two ways:

Start the server:

poetry run uvicorn src.main:app

Use with Goose:

a. Via session:

goose session --with-extension "uvicorn src.main:app"

b. Via single command:

goose run --with-extension "uvicorn src.main:app" -t "your instructions"

Available functions:

get_user(identifier: str) - Get user information
get_user_leagues(user_id: str, season: str) - Get leagues for a user
get_league(league_id: str) - Get league details
get_league_rosters(league_id: str) - Get league rosters
get_league_users(league_id: str) - Get league users
get_nfl_state() - Get NFL season state

MCP Protocol Implementation

This server implements the Model Context Protocol (v2024-11-05) which includes:

Initialization Phase:
- Server capability discovery
- Protocol version negotiation
- Feature negotiation
Operation Phase:
- Function discovery and invocation
- Resource access
- Error handling
Security:
- Rate limiting
- Error reporting
- Access controls

Development

Project Structure

sleeper-mcp/
├── docs/
│   ├── openapi.yaml        # API specification
│   └── sleeper_api_raw.html # Raw API documentation
├── src/
│   ├── api/               # API endpoints
│   ├── models/            # Data models
│   ├── mcp/              # MCP protocol implementation
│   ├── services/         # Business logic
│   └── config/           # Configuration
├── tests/                # Test suites
├── pyproject.toml        # Project dependencies
├── README.md            # This file
└── TODO.md             # Development tasks

Running Tests

poetry run pytest

Development Server

poetry run uvicorn src.main:app --reload

Security Considerations

As per MCP specification:

No authentication required (read-only API)
Rate limiting enforced (1000 requests/minute)
No sensitive data exposure
Clear error reporting

API Documentation

OpenAPI documentation: /docs
Raw API documentation: /docs/sleeper_api_raw.html
MCP capabilities: /capabilities

License

[Add your chosen license]

Acknowledgments

Sleeper API Team
Model Context Protocol Specification
Goose AI Team

This server cannot be installed

security - not tested

license - not found

quality - not tested

How are these scores calculated?

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.

A server that integrates Sleeper fantasy sports data with Goose AI through the Machine Context Protocol (MCP), providing structured access to fantasy league information.

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