mcp-phish

mcp-phish

Combines phish.net and phish.in APIs into twelve tools for setlists, songs, jam-charts, reviews, and audio.

Category
Visit Server

README

mcp-phish

CI License: MIT Python MCP

An MCP server that wraps the api.phish.net v5 and phish.in v2 APIs behind a single typed tool surface. Twelve tools across setlists, songs, jam-charts, reviews, and audio. Every response is shaped through frozen Pydantic models so the wire format stays stable across upstream API drift.

Built on FastMCP with Streamable HTTP transport. Designed to run on a trusted LAN or behind a Tailscale ACL — there is no built-in MCP-level auth.

Why

Today the Phish.net + phish.in ecosystem is a small set of unmaintained wrappers and one-off scripts. Nobody combines the two cleanly. mcp-phish gives any MCP-aware client (Claude Code, Claude Desktop, custom agents) a focused, well-typed surface area for the questions phans actually ask: setlist for a date, song debut and gap, audio URL for a track, jam-chart hits for a tour.

Source can change (live API → cached → vault). The Pydantic shapes returned to MCP clients never do.

Quick start

docker run --rm \
  -p 3705:3705 \
  -e STUB_MODE=true \
  ghcr.io/pete-builds/mcp-phish:latest

The server starts in stub mode by default. It returns realistic mock data and requires no network access or API key. Register it with Claude Code:

claude mcp add phish --transport http --scope user --url http://localhost:3705/mcp

Then ask Claude: "What was the setlist on 12/30/95?" and you should get back Madison Square Garden with the Mike's > Simple > Weekapaug groove.

To talk to the real APIs, register a free key at api.phish.net/keys/ and flip stub mode off:

docker run --rm \
  -p 3705:3705 \
  -e STUB_MODE=false \
  -e PHISHNET_API_KEY=<your-key> \
  ghcr.io/pete-builds/mcp-phish:latest

Tool reference

Tool Source What it does
search_shows phish.net Search shows by year + venue + city/state/country.
get_show phish.net Full show: setlist, ratings, reviews count, venue.
recent_shows phish.net N most recent shows, most-recent-first.
search_songs phish.net Search the song catalog by title fragment.
get_song phish.net One song record: debut, last play, gap, total.
song_history phish.net Every performance of a song, most-recent-first.
jam_chart phish.net Editorially flagged notable jams.
get_reviews phish.net User reviews for a show.
get_audio phish.in Track list + MP3 URLs + durations for a show.
get_track phish.in One audio track by id.
search_audio_tracks phish.in Every recorded version of one song slug.
health meta Server status, throttle state, cache stats.

Every tool returns a JSON string with the standard envelope:

{"data": <typed payload>}

or, on failure:

{
  "error": "human-readable message",
  "code": "UPSTREAM_DOWN | NOT_FOUND | INVALID_INPUT | RATE_LIMITED | INTERNAL",
  "details": { "...": "..." }
}

The Pydantic models in src/mcp_phish/models.py (ShowSummary, Show, SetlistEntry, Song, Performance, NotableJam, Review, Track, ShowAudio, Health) are the public contract. They are frozen with extra="forbid" so any upstream drift becomes a validation error rather than a silent shape change.

Stub mode vs real mode

Mode When to use Behavior
Stub (STUB_MODE=true, default) Development, demos, no API key yet Realistic mock payloads for a small set of canonical shows (12/30/95 MSG, 11/17/97 Denver, 12/31/24 MSG). Every tool returns the same Pydantic shape it would in real mode.
Real (STUB_MODE=false) Production with a phish.net API key Talks HTTPS to api.phish.net v5 and phish.in v2. Requires PHISHNET_API_KEY; PHISHIN_API_KEY is optional.

Switching modes is a config change, not a code change. Same twelve tools, same response shapes.

Caching

mcp-phish keeps an opaque key-value cache on disk (/data/phish-cache.db, aiosqlite) keyed by (endpoint, params_hash). A single TTL governs every entry (CACHE_TTL_SECONDS, default 86400 = 24h). On a hit, no upstream call is made.

This cache is not a normalized data store. It just holds raw JSON responses to keep us under the upstream rate limits and to make repeated LLM-driven exploration fast. Treat it as ephemeral.

Throttling

Every upstream call passes through a per-instance token bucket with a configurable steady-state rate:

Variable Default Notes
THROTTLE_PHISHNET_RPS 5 api.phish.net v5 requests per second.
THROTTLE_PHISHIN_RPS 10 phish.in v2 requests per second.

The bucket is in-process. Multiple containers do not coordinate. Token state is exposed in health() so a Claude Code session can see what's left.

Configuration

All configuration is read from environment variables (and a .env file when present). Pydantic validates at startup and fails fast on invalid values.

Variable Type Default Required Notes
STUB_MODE bool true no When false, real-mode credentials are required.
PHISHNET_API_KEY string "" only in real mode Free at api.phish.net/keys/.
PHISHIN_API_KEY string "" no Optional; raises rate caps.
PHISHNET_BASE_URL string https://api.phish.net/v5 no Override for testing.
PHISHIN_BASE_URL string https://phish.in/api/v2 no Override for testing.
CACHE_DB_PATH string /data/phish-cache.db no aiosqlite file path.
CACHE_TTL_SECONDS int 86400 no 24h default.
THROTTLE_PHISHNET_RPS float 5.0 no Per-second steady rate.
THROTTLE_PHISHIN_RPS float 10.0 no Per-second steady rate.
MCP_HOST string 0.0.0.0 no Bind address.
MCP_PORT int 3705 no Listen port.
LOG_LEVEL enum INFO no One of DEBUG, INFO, WARNING, ERROR, CRITICAL.
LOG_FORMAT enum json no json for production, text for local dev.

A complete example lives in .env.example.

MCP client setup

Claude Code

claude mcp add phish --transport http --scope user --url http://<host>:3705/mcp

Claude Desktop

{
  "mcpServers": {
    "phish": {
      "transport": "streamable-http",
      "url": "http://<host>:3705/mcp"
    }
  }
}

Generic config

Streamable HTTP at http://<host>:3705/mcp. Any MCP client supporting the Streamable HTTP transport can connect.

Architecture

+---------------------+     Streamable HTTP     +---------------------+
|  MCP Client         |  -------------------->  |  mcp-phish          |
|  (Claude Code, etc) |  <--------------------  |  (FastMCP server)   |
+---------------------+                         +----+--------------+-+
                                                     |              |
                                                     |              |
                                                     v              v
                                          +----------+--+   +-------+--------+
                                          | api.phish.net|   | phish.in/api/v2|
                                          |     v5       |   |                |
                                          +--------------+   +----------------+

                                                     ^
                                                     |
                                          +----------+----------+
                                          | aiosqlite KV cache  |
                                          |  /data/phish-cache  |
                                          +---------------------+

mcp-phish is a thin async proxy with a small cache: it translates MCP tool calls into upstream REST calls, caches raw responses for the configured TTL, and projects them into the public Pydantic shape. It does not store any state beyond that cache. It does not call any cloud services other than the two phish APIs.

Security notes

  • Run mcp-phish on a trusted LAN, on Tailscale, or behind a reverse proxy with auth. The server itself does not authenticate MCP clients.
  • API keys live only in the container's environment. They are never logged, never echoed in responses, and never written to disk.
  • The container runs as UID 1000, no shell, no home directory, with a read-only root filesystem (/tmp is tmpfs) and no-new-privileges.
  • The /data cache volume is the only writable path.
  • Python deps install with pip --require-hashes from a hash-locked requirements.lock. The base image will be pinned by digest before the first tagged release.
  • Published images are multi-arch (amd64/arm64) with build provenance and SBOM via docker/build-push-action.

For vulnerability reports, see SECURITY.md.

Development

Requires Python 3.13+ and Docker.

# Clone + install dev deps
git clone https://github.com/pete-builds/mcp-phish.git
cd mcp-phish
python -m venv .venv && source .venv/bin/activate
pip install --require-hashes -r requirements-dev.lock
pip install -e . --no-deps

# Run the test suite
pytest

# Lint and format
ruff check src tests
ruff format src tests

# Type check (mypy strict)
mypy src/mcp_phish

# Run the server locally in stub mode
python -m mcp_phish.server

# Or build the image yourself
cp docker-compose.example.yml docker-compose.yml
docker compose up --build

Updating dependencies

The requirements.lock and requirements-dev.lock files are hash-pinned. Edit the matching .in file then regenerate:

uv pip compile requirements.in --output-file requirements.lock --generate-hashes --python-version 3.13
uv pip compile requirements-dev.in --output-file requirements-dev.lock --generate-hashes --python-version 3.13

Dependabot opens weekly PRs for requirements.in-level updates, the Docker base image, and GitHub Actions versions.

Roadmap

This server is Phase 1 of a larger Phish data project. The Pydantic contract documented above will stay byte-identical across the future phases.

  • Phase 2 — Postgres vault + nightly ETL hydration.
  • Phase 3 — vault-backed read path for this MCP. Hot-window fallthrough reads recent shows live; older reads come from the vault.
  • Phase 4 — setlist-prediction game (separate repo).
  • Phase 5 — chat + dashboard UI over MCP (separate repo).

Phase status lives at https://github.com/pete-builds/mcp-phish/issues.

Acknowledgments

Thanks to the phish.net and phish.in operators for keeping the corpus public and machine-accessible. This wrapper is unaffiliated with either project. Please respect their rate limits and terms of service.

License

MIT.

Contributing

Issues and pull requests welcome. Before opening a PR:

  1. Make sure ruff check, ruff format --check, and mypy src/mcp_phish are clean.
  2. Add or update tests; keep coverage at 80% or above.
  3. Run pytest locally and confirm the suite passes.
  4. Update CHANGELOG.md under an [Unreleased] heading.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured