# College Football Data

> Use this tool when you need to access comprehensive college football statistics, analyze team performance, or generate insights on historical trends. It provides a natural language interface for querying game results, team records, player stats, and advanced metrics, with robust error handling and optimized API usage. Ideal for sports analysts, researchers, and fans, it enables use cases such as game prediction, player evaluation, and historical performance comparisons.

Canonical page: https://skillsregistry.net/skills/lenwood-college-football-data  
JSON: https://api.skillsregistry.net/v1/skills/lenwood-college-football-data

## Description

This College Football Data MCP server, developed by Chris Leonard, provides AI assistants with access to comprehensive college football statistics via the College Football Data API. Built with Python and leveraging libraries like httpx and pydantic, it offers a natural language interface for querying game results, team records, player stats, rankings, and advanced metrics. The server implements robust error handling, rate limiting, and caching to optimize API usage. By abstracting the complexities of data retrieval and analysis, it enables AI systems to generate insights on team performance, analyze historical trends, and compare statistics across seasons. This implementation is particularly valuable for sports analysts, researchers, and fans seeking in-depth college football data analysis, facilitating use cases such as game prediction, player evaluation, and historical performance comparisons.

## Trust

- **Trust score (0–1):** 0.97
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** monitoring
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/lenwood-college-football-data)
- **Repository:** <https://github.com/lenwood/cfbd-mcp-server>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "lenwood-college-football-data"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/lenwood-college-football-data` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/lenwood-college-football-data/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt