About Statbotics
Statbotics MCP Server gives AI assistants and other MCP clients access to FIRST Robotics Competition statistics and predictions through the Statbotics API. It covers teams, events, matches, and season-level trends, with responses validated by Zod schemas.
Key features
- 01Retrieve team EPA ratings and win rates
- 02Query event details and predictions
- 03Access match predictions and results
- 04Get team-level event and match statistics
- 05Query year-over-year data from 2002 onward
- 06Validate responses with Zod schemas
Use cases
- 01Compare FRC teams' historical performance
- 02Review predictions and team data for an event
- 03Analyze match predictions alongside results
- 04Track statistical trends across seasons
MCP support
The MCP server exposes Statbotics API tools for querying FRC team, season, event, and match data. MCP clients can call these tools without a Statbotics API key.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
14Saved tool list · updated 2w ago
| Parameter | Type | Required | Description |
|---|---|---|---|
| year | integer | Yes | Four-digit year (2002 onwards) |
Details
From the project READMEStatbotics MCP Server
A Model Context Protocol (MCP) server that provides access to the Statbotics API for FIRST Robotics Competition statistical data and predictions. Enables AI assistants and other MCP clients to retrieve FRC team EPA ratings, event predictions, and match analytics.
Features
- Team Statistics: Get EPA ratings, win rates, and historical performance for FRC teams
- Event Data: Access event details, predictions, and team performance at events
- Match Analytics: Retrieve match predictions, results, and team-level match statistics
- Year-over-Year Data: Query statistical trends from 2002 to the current year
- Type Safety: All responses validated with Zod schemas
- No API Key Required: Statbotics API is freely accessible
Installation
npm (Recommended)
npm install -g @withinfocus/statbotics-mcp-server
Docker
Pull the image from GitHub Container Registry:
docker pull ghcr.io/withinfocus/statbotics-mcp-server:latest
Or build locally:
git clone https://github.com/withinfocus/statbotics-mcp-server.git
cd statbotics-mcp-server
docker build -t statbotics-mcp-server .
Usage
With npm
Add to your MCP client configuration (e.g., Claude Desktop):
{
"mcpServers": {
"statbotics": {
"command": "npx",
"args": ["-y", "@withinfocus/statbotics-mcp-server"]
}
}
}
With Docker
Add to your MCP client configuration:
{
"mcpServers": {
"statbotics": {
"command": "docker",
"args": [
"run",
"--rm",
"-i",
"--init",
"ghcr.io/withinfocus/statbotics-mcp-server:latest"
]
}
}
}
Available Tools
Year Tools (2 tools)
Query season-level statistical data.
Tools: get_year, get_years
Team Tools (2 tools)
Access team profiles and EPA ratings.
Tools: get_team, get_teams
Team Year Tools (2 tools)
Get team statistics for specific seasons.
Tools: get_team_year, get_team_years
Event Tools (2 tools)
Query event details and predictions.
Tools: get_event, get_events
Team Event Tools (2 tools)
Get team performance at specific events.
Tools: get_team_event, get_team_events
Match Tools (2 tools)
Retrieve match data and predictions.
Tools: get_match, get_matches
Team Match Tools (2 tools)
Get team-level match statistics.
Tools: get_team_match, get_team_matches
Quick Examples
Get team information
// Get team EPA ratings and statistics
get_team(team: 86)
// Get team's performance in a specific year
get_team_year(team: 86, year: 2024)
Analyze an event
// Get event statistics
get_event(event: "2024flor")
// Get all team performances at an event
get_team_events(event: "2024flor")
Get match data
// Get match predictions and results
get_match(match: "2024flor_qm20")
// Get team's performance in a match
get_team_match(team: 86, match: "2024flor_qm20")
Contributing
Contributions are welcome! See CONTRIBUTING.md for development setup, testing guidelines, and how to add new tools.
Related Links
- Statbotics - FRC statistical analysis
- Statbotics API Documentation - Official API docs
- Model Context Protocol - MCP specification
- FIRST Robotics Competition - Official FRC site
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.