⏱️ speedrun-mcp
A Model Context Protocol server for speedrun.com — let an AI assistant query games, categories, leaderboards, world records, players and their personal bests, and (with an API key) submit and moderate runs.
"What's the current Super Mario 64 16-star world record, and who holds it?"
Built on speedrun.com's official REST API. The read tools need no account or API key — add a key (see Authenticated features) to unlock identity reads and, optionally, run submission and moderation. Results come back as compact, model-friendly JSON (player ids resolved to names, durations formatted, subcategory variables labeled).
Example
Ask "the SM64 16-star world record?" and the model calls get_world_record,
which returns resolved JSON. An excerpt:
{
"game_name": "Super Mario 64",
"category_name": "16 Star",
"world_record": {
"players": ["Suigi"],
"time": "14m 35.5s",
"date": "2023-03-22",
"video": "https://youtu.be/1_vkwkniHuI"
}
}
Tools
| Tool | What it does |
|---|---|
search_games |
Fuzzy-search games by name → ids & abbreviations |
get_game |
A game's details plus its categories (and optionally levels) |
list_categories |
A game's categories (Any%, 120 Star, …) with rules |
list_variables |
Subcategory/filter variables and their value ids |
list_platforms / list_regions |
Platform / region ids for the platform/region leaderboard filters |
get_leaderboard |
A ranked leaderboard (top N; filter by variable / platform / region / timing) |
get_world_record |
The current #1 run for a game/category, plus any runs tied for first |
get_game_records |
Every category's records for a game in one call (defaults to world records) |
search_series |
Fuzzy-search game series (e.g. Mario, Zelda) |
get_series |
A series' details and the games it contains |
search_users |
Find players by username (partial, fuzzy match) |
get_user_personal_bests |
A player's PBs across all games |
get_run |
Details of a single run |
list_runs |
Runs filtered by player / game / category / status / examiner |
list_unverified_runs |
A game's runs awaiting verification (the moderation queue) |
whoami |
The profile that owns your API key (only shown when a key is set) |
list_notifications |
Your speedrun.com notifications (only shown when a key is set) |
A typical flow: search_games → list_categories (and list_variables for
subcategories) → get_leaderboard / get_world_record. Use list_platforms /
list_regions when you need an id for the platform / region filters.
With write tools enabled (see below), submit_run, verify_run, reject_run,
set_run_players and delete_run are also available.
Result scope and provenance
Search tools, list_runs, list_unverified_runs, and list_notifications return
an object with results, returned, offset, limit, has_more, and
next_offset. This replaces their earlier bare-list output. Pass next_offset
as offset to continue with the same filters. has_more: null means the API
omitted pagination metadata, so completeness is unknown. get_series.games
uses the same envelope; continue with game_offset.
pagination_note explains the continuation evidence: an API next-page link
can lead to an empty page and does not establish a total result count.
get_game_records follows all pages. Notifications scan up to scan_limit
source records and report scanned; an empty unread result is not evidence of
no unread notifications when has_more is true or unknown.
Run rows preserve account/guest identity in player_details, all video links
in videos, and separate source commentary in video_text. Personal-best rows
include game/category IDs, level, and raw variable choices. Variable details and
subcategory maps are keyed by variable ID to avoid collisions between names.
Leaderboard applied_filters includes the API's system filters and resolved
variables; requested_filters separately records the call's filters, including
historical dates. A missing requested timing is marked unavailable rather than
replaced by the primary time. Each displayed time identifies its source field.
returned_runs and omitted_from_response count rows from the fetched response,
not the full leaderboard.
Write errors that leave completion uncertain explicitly warn against automatic retries. A success response that cannot be parsed preserves its HTTP status and resource location when supplied.
Install & run
Requires Python 3.10+.
# from PyPI
pipx install speedrun-mcp # or: uv tool install speedrun-mcp
# from source
git clone https://github.com/williamcodes/speedrun-mcp
cd speedrun-mcp
pip install -e .
The server speaks MCP over stdio:
speedrun-mcp # console script
python -m speedrun_mcp # equivalent
Use with Claude Desktop / Claude Code
Add to your MCP client config (e.g. claude_desktop_config.json):
{
"mcpServers": {
"speedrun": {
"command": "speedrun-mcp"
}
}
}
If you installed from source into a virtualenv, point command at that
interpreter, e.g. "command": "/path/to/.venv/bin/speedrun-mcp".
For Claude Code:
claude mcp add speedrun -- speedrun-mcp
# with authenticated features (optional):
claude mcp add speedrun \
-e SPEEDRUN_API_KEY=your-key-here \
-e SPEEDRUN_ENABLE_WRITES=1 \
-- speedrun-mcp
One-click install in Claude Desktop
Each GitHub release
ships a speedrun-mcp-<version>.mcpb bundle. Download it and open it with
Claude Desktop (double-click, or Settings → Extensions → Install from file).
Claude Desktop installs Python and the dependencies itself; nothing else is
needed. The extension settings expose the optional API key and the writes
toggle described below.
Authenticated features
An API key is entirely optional. With no key, the server exposes only the public read tools (leaderboards, games, players, the moderation queue) and works exactly as described above — no account required. Adding your key unlocks more:
| Set this env var | Effect |
|---|---|
SPEEDRUN_API_KEY |
Puts the server in read-only authenticated mode. Adds the identity reads — whoami (the profile your key belongs to) and list_notifications. The write tools (submit_run, verify_run, reject_run, set_run_players, delete_run) also become visible, but stay disabled — calling one returns a message telling you to enable writes. Until a key is set, none of these are advertised at all. |
SPEEDRUN_ENABLE_WRITES=1 |
Switches to read-write mode: arms the write tools so they actually submit/moderate. Requires SPEEDRUN_API_KEY (moderation also needs a moderator key). Off by default — submitting and rejecting/deleting are real, permanent actions on real leaderboards, so opt in deliberately. |
Read-only is the default. Just adding a key never changes anything on speedrun.com — you get identity reads, and everything keeps working perfectly. If a write tool is invoked while writes are off, it doesn't silently fail; it returns:
This server is in read-only mode, so this write action is disabled. To allow run submission and moderation, set the environment variable SPEEDRUN_ENABLE_WRITES=1 (alongside SPEEDRUN_API_KEY) and restart the server.
So the way to switch to read-write mode is always discoverable from the error itself.
Getting your API key
- Log in to speedrun.com.
- Go to your account settings.
- In the left-hand nav, find the Developers section and click API Key.
- Copy the key shown there.
Treat the key like a password — anyone who has it can act as you on speedrun.com. If it ever leaks, regenerate it from that same page.
Using your key
Add the key to your MCP client config under env. It is read only from the
environment — never passed as a tool argument — so it can't leak into the
model's context or transcripts. Add SPEEDRUN_ENABLE_WRITES=1 only when you want
writes to actually run; with the key alone you stay safely read-only.
{
"mcpServers": {
"speedrun": {
"command": "speedrun-mcp",
"env": {
"SPEEDRUN_API_KEY": "your-key-here",
"SPEEDRUN_ENABLE_WRITES": "1"
}
}
}
}
Or with Claude Code:
claude mcp add speedrun -e SPEEDRUN_API_KEY=your-key-here -- speedrun-mcp
# add -e SPEEDRUN_ENABLE_WRITES=1 as well if you want the write tools
Keep the key out of version control — put it in your client config or a local,
git-ignored .env, never in a committed file. All tools carry MCP read-only /
destructive hints so clients can flag the write and moderation actions.
Local environment file
Copy .env.example to .env and fill in the settings you need.
The template leaves the API key empty and disables writes. Git ignores .env.
The server reads exported environment variables and does not load .env
automatically. To load your local file and start the server from a shell:
set -a
. ./.env
set +a
speedrun-mcp
Notes & limits
- Reads need no key; writes are opt-in. Leaderboards, games, players and the
moderation queue are open reads. Run submission and moderation need
SPEEDRUN_API_KEYandSPEEDRUN_ENABLE_WRITES(see above). - Rate limit: speedrun.com allows 100 requests/minute per IP and responds with HTTP 420 when exceeded; the client surfaces a clear error if you hit it.
- Game and category arguments accept either an id (
o1y9wo6q) or an abbreviation (sm64). For precise subcategory leaderboards (e.g.16 Star), discover the variable/value ids withlist_variablesand passvariables={variable_id: value_id}. - Errors are explanatory. Invalid ids/filters raise an error that includes
speedrun.com's own message — e.g. passing a
levelto a full-game category returns "The selected category is for full-game runs, but a level was selected."
Output shape
- Times reflect the leaderboard's sort timing. When you pass
timing(realtime/realtime_noloads/ingame), the reportedtime/time_secondsmatch that ranking, not the game's default timing. get_leaderboardreturnsreturned_runs(the number of runs returned, bounded bytopand ties — not the full board size) and arunslist with resolved player names, formatted times, and labeled subcategories.get_world_recordreturnsworld_record(the place-1 run, ornullif the board is empty) plustied(a list of any other runs sharing first place).get_user_personal_bestsreturnsreturned(how many came back, capped bylimit) andtotal_available(the player's true PB count), plus thepersonal_bestslist with game/category names and resolved players.
Development
The package uses a flat src/speedrun_mcp/ layout:
client.pyhandles HTTP requests, API errors, and pagination.format.pyconverts API payloads into tool results without network access.server.pyowns MCP tools, configuration, and the shared client's lifecycle.__main__.pyprovides thepython -m speedrun_mcpentry point.__init__.pyexposesmcpon demand, so importing the client or format helpers does not initialize the server.
Tests live in tests/. Unit tests cover each layer; package and MCP protocol
tests cover imports and startup. test_live.py contains the live API checks,
selected with the network marker.
pip install -e ".[dev]"
pre-commit install
# The checks run by CI:
ruff check .
ruff format --check .
mypy
pytest -m "not network"
# Apply safe lint fixes and formatting locally:
ruff check --fix .
ruff format .
# Optional: include live API tests.
pytest
# Build the Claude Desktop bundle (needs Node for npx):
npx -y @anthropic-ai/mcpb validate manifest.json
npx -y @anthropic-ai/mcpb pack . speedrun-mcp.mcpb
Releasing
Bump the version in pyproject.toml, server.json and manifest.json (a test
checks they agree), tag v<version>, and publish a GitHub release. The release
workflow then runs CI, publishes the wheel to PyPI, attaches the .mcpb bundle
to the release, and publishes the new version to the
MCP registry with both the PyPI
package and the bundle listed. Registry auth uses GitHub OIDC, so no token is
stored; PyPI verifies ownership through the mcp-name comment at the top of
this README.
Ruff checks source and tests for common bugs, security issues, async mistakes,
overly complex functions, and pytest mistakes. It also sorts imports and formats
Python code. Tests may use assert; the other lint rules apply to both source
and tests. Print and debugger statements are rejected because the server uses
stdout for the MCP protocol.
Ruff is pinned to the same version in the dev dependencies, its required-version
setting, and pre-commit. Update all three together. The hooks apply safe lint fixes
and formatting before running mypy; CI checks without changing files.
License
MIT
Release files for speedrun-mcp 0.3.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| speedrun_mcp-0.3.3.tar.gz | 49.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| speedrun_mcp-0.3.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 78.5 kB
Release files / speedrun_mcp-0.3.3.tar.gz
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|---|---|
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| Uploaded via |
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