Sleeper MCP Server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Sleeper MCP Serverget my fantasy league rosters for the 2024 season"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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
Related MCP server: nfl-mcp
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:appIntegration with Goose
The Sleeper MCP server integrates with Goose in two ways:
Start the server:
poetry run uvicorn src.main:appUse 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 informationget_user_leagues(user_id: str, season: str)- Get leagues for a userget_league(league_id: str)- Get league detailsget_league_rosters(league_id: str)- Get league rostersget_league_users(league_id: str)- Get league usersget_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 tasksRunning Tests
poetry run pytestDevelopment Server
poetry run uvicorn src.main:app --reloadSecurity 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:
/docsRaw API documentation:
/docs/sleeper_api_raw.htmlMCP capabilities:
/capabilities
License
[Add your chosen license]
Acknowledgments
Sleeper API Team
Model Context Protocol Specification
Goose AI Team
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Resources
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