jk-mcp-mls
MCP server that gives Claude live access to Major League Soccer data — teams, matches, standings, rosters, and schedule-strength analytics — via the ESPN public API.
README
jk-mcp-mls
MCP server that gives Claude live access to Major League Soccer data — teams, matches, standings, rosters, and schedule-strength analytics — via the ESPN public API.
Table of Contents
- Overview
- Features
- Requirements
- Installation
- Usage
- Configuration
- Claude Code
- Claude Desktop
- Docker
- Development
- Contributing
- License
Overview
AI assistants like Claude are knowledgeable, but they have a hard cutoff date — they cannot tell you today's MLS standings, last night's scores, or which teams are currently in a playoff position. This project fixes that.
It is an MCP server — a plugin that gives Claude direct access to live MLS data: scores, standings, rosters, and derived schedule-strength analytics. Once installed, you can ask Claude natural-language questions about Major League Soccer and get accurate, up-to-date answers. No subscription, no API key, and no programming required to use it.
This is the v1 scaffold — it wraps the ESPN public API only. Richer sources (mlssoccer.com's Opta-powered feed, official CMS award articles, Leagues Cup, U.S. Open Cup, Concacaf Champions Cup) are on the roadmap.
Features
The v1 surface is eleven read-only, idempotent tools split across two tiers.
ESPN-backed (8)
| Tool | Description |
|---|---|
get_teams |
List all 30 MLS clubs with IDs and abbreviations |
get_team |
Details for a specific team |
get_roster |
Team's active roster — jersey, position, age, citizenship |
get_scoreboard |
Match scores for a single day, a date range, or the current matchweek |
get_team_schedule |
Every match for a team in the current season — past + upcoming |
get_match_details |
One match's full details — score, venue, attendance, goals, cards, subs |
get_standings |
Current standings grouped by Eastern and Western Conferences |
get_news |
Recent MLS news articles |
Derived analytics (3)
Pure functions over live standings + team schedules, exposing schedule-strength context the raw table does not.
| Tool | Description |
|---|---|
get_strength_of_schedule |
Team's average opponent points-per-game across matches already played |
get_results_by_opponent_tier |
Team's W-L-T split across current top / middle / bottom standings tiers |
get_adjusted_points_per_game |
Team's raw PPG alongside an opponent-quality-adjusted PPG |
Roadmap
Not in v1; probed and shown to be viable at the ESPN API:
- Leagues Cup (
concacaf.leagues.cup), U.S. Open Cup (usa.open), Concacaf Champions Cup, Campeones Cup - Player leaderboards and team season aggregates once a stable MLS Opta feed is identified
- Award articles via
mlssoccer.comCMS - Playoff bracket for the MLS Cup Playoffs
Requirements
Installation
git clone https://github.com/jedi-knights/jk-mcp-mls.git
cd jk-mcp-mls
uv sync
Usage
Run the server in stdio mode (the default — used by Claude Code and Claude Desktop):
uv run python -m mls.server
Run in HTTP mode (for networked or deployed access):
MCP_TRANSPORT=streamable-http uv run python -m mls.server
Example prompts
Standings, scores, rosters:
- Who is leading the MLS Eastern Conference right now?
- Show me every MLS result from this past weekend.
- Who is on Atlanta United's roster?
- When does LAFC play next?
Schedule strength:
- Which MLS team has played the toughest schedule so far?
- Show me Atlanta United's record against the current top 5 teams.
- Compare Inter Miami and Seattle Sounders on adjusted points-per-game.
Configuration
All configuration is via environment variables. None are required for local use.
| Variable | Default | Description |
|---|---|---|
MCP_TRANSPORT |
stdio |
Transport mode: stdio or streamable-http |
HOST |
0.0.0.0 |
Bind address (HTTP transport only) |
PORT |
8000 |
TCP port (HTTP transport only) |
MCP_PATH |
/mcp/mls |
URL path (HTTP transport only) |
API_HOST |
https://site.api.espn.com |
ESPN API base URL |
LOG_LEVEL |
INFO |
DEBUG, INFO, WARNING, or ERROR |
MCP_TRACING_ENABLED |
unset | Bootstrap the OpenTelemetry SDK |
MCP_AUTH_ENABLED |
unset | Require RS256 bearer tokens on streamable-http |
MCP_AUTH_ISSUER_URL |
unset | Auth-server origin (required when auth is on) |
MCP_AUTH_RESOURCE_URL |
unset | This server's public URL for the aud claim |
Claude Code
Install from your local clone globally so the server is available in every project:
claude mcp add --scope user mls -- uv run --directory /path/to/jk-mcp-mls python -m mls.server
Replace /path/to/jk-mcp-mls with the absolute path to your clone. Verify with claude mcp list.
Drop --scope user to register only for the current project, or commit a .mcp.json to the repo root for collaborators:
{
"mcpServers": {
"mls": {
"command": "uv",
"args": ["run", "--directory", "/path/to/jk-mcp-mls", "python", "-m", "mls.server"]
}
}
}
Claude Desktop
Add the following to your Claude Desktop configuration file.
Location:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json - Windows:
%APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"mls": {
"command": "uv",
"args": [
"run",
"--directory", "/path/to/jk-mcp-mls",
"python", "-m", "mls.server"
]
}
}
}
If uv is not on Claude Desktop's PATH, use the absolute path (which uv will show it). Fully quit and relaunch Claude Desktop after saving — a window close is not enough.
Docker
Build the image:
docker build -t jk-mcp-mls:latest .
Run in stdio mode (for MCP clients that spawn a subprocess):
docker run -i --rm jk-mcp-mls:latest
Run in HTTP mode:
docker run --rm -p 8000:8000 \
-e MCP_TRANSPORT=streamable-http \
jk-mcp-mls:latest
Development
Install
uv sync
Invoke tasks
All common workflows are invoke tasks. Run uv run inv --list to see everything.
| Task | Alias | Description |
|---|---|---|
uv run inv lint |
inv l |
Run ruff linter and format check |
uv run inv lint --fix |
inv l --fix |
Auto-fix lint violations and reformat |
uv run inv test |
inv t |
Run the full test suite |
uv run inv coverage |
inv v |
Run tests with coverage report (threshold: 90%) |
uv run inv check-complexity |
inv cc |
Check cyclomatic complexity (max 7) |
uv run inv build |
inv b |
Build wheel and sdist into dist/ |
uv run inv build-image |
inv bi |
Build the Docker image |
uv run inv clean |
inv c |
Remove build and coverage artifacts |
Project structure
src/mls/
├── server.py # entry point, transport selection, logging setup
├── adapters/
│ ├── inbound/
│ │ ├── mcp_adapter.py # FastMCP server, health endpoints, tool registration
│ │ ├── formatters.py # domain → LLM-readable text
│ │ ├── authorization.py # inbound authz port implementations
│ │ └── tools/
│ │ ├── espn.py # 8 ESPN-backed tools
│ │ └── analytics.py # 3 schedule-strength analytics tools
│ └── outbound/
│ ├── espn_adapter.py # ESPN HTTP client
│ ├── parsers.py # ESPN JSON → domain models
│ ├── retry_adapter.py # transient-failure retry decorator
│ └── caching_adapter.py # in-process TTL cache
├── application/
│ ├── service.py # MLSService — use cases, orchestration
│ ├── _helpers.py # input validation
│ └── _analytics_helpers.py # pure math for schedule-strength tools
├── domain/
│ ├── models.py # Team, Match, Standing (with conference), etc.
│ └── exceptions.py # MLSNotFoundError, UpstreamAPIError
├── ports/
│ ├── inbound.py # Authorizer protocol
│ └── outbound.py # MLSAPIPort protocol
├── observability/ # OpenTelemetry bootstrap (opt-in)
└── security/ # JWKS token verifier
The dependency direction flows inward: adapters → ports → domain. Nothing in domain/ imports from adapters or a framework.
Contributing
- Fork the repository and clone your fork
- Create a feature branch:
git checkout -b feature/your-feature - Make your changes following the existing patterns (hexagonal architecture, TDD, conventional commits)
- Verify the full check suite passes:
uv run inv lint && uv run inv check-complexity && uv run inv coverage - Open a pull request against
main
All CI checks (lint, complexity, tests, coverage ≥ 90%) must pass before merge.
License
MIT — see LICENSE.
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