Trillian MCP
Enables natural language queries of astronomical data across multiple archives (Gaia, 2MASS, image holdings) via the Trillian platform, allowing users to search catalogs and find images by sky coordinates.
README
Trillian MCP
Ask an AI about the sky. This is a Model Context Protocol server for Trillian, a platform for discovery and analysis across large, multi-archive astronomical datasets. Connect it to Claude (or any MCP client) and plain questions become live queries against real survey data — catalogs and image holdings, ultraviolet through infrared.
The demos below are replays of real sessions; every number and identifier is a genuine response from the live API.
A real session: finding the Crab Pulsar
One question — "What do we know about the sky at the Crab Nebula?" — and the model, given only these six tools, identifies the Crab Pulsar's optical counterpart in Gaia by matching its proper motion to the literature value, then diagnoses the invisible synchrotron nebula from corrupted 2MASS photometry flags. This is the unedited output of an actual session (full transcript):
Which images cover this spot?
One query, three archives, ultraviolet through infrared — every file addressed by a stable SciDD identifier that resolves to its home archive:
It will not guess your units
Sexagesimal coordinates without units are ambiguous, and a wrong guess is a wrong field on the sky. The server returns a structured question instead of an assumption — the model relays it, the user decides:
Tools
| Tool | What it does |
|---|---|
gaia_edr3_cone_search |
Cone search the Gaia EDR3 source catalog |
gaia_edr3_lookup |
Look up a single Gaia EDR3 source by source_id |
two_mass_cone_search |
Cone search the 2MASS All-Sky point source catalog |
two_mass_lookup |
Look up a single 2MASS source by designation |
file_cone_search |
Find image files overlapping a sky region, across datasets |
filename_search |
Find files by filename fragment |
Coordinates accept astronomer-friendly strings (83.633d, 05h34m32s,
-23:20:36); inputs are normalized and validated against JSON schemas before
any request reaches the API. Ambiguous input produces a structured
clarification error rather than a guess.
The datasets exposed here — Gaia EDR3, 2MASS, and image holdings including GALEX GR6, 2MASS, and WISE — are a demonstration slice of the platform's index, not its full extent.
Installation
Requires Python ≥ 3.10.
git clone https://github.com/demitri/trillian_mcp.git
cd trillian_mcp
pip install -r requirements.txt
Register with Claude Code:
claude mcp add trillian -- python3 /path/to/trillian_mcp/server.py
or add to any MCP client's server configuration:
{
"mcpServers": {
"trillian": {
"command": "python3",
"args": ["/path/to/trillian_mcp/server.py"]
}
}
}
Then ask about the sky.
Trying it without an MCP client
python3 demo_cli.py gaia-edr3-cone-search --ra "83.633d" --dec="+22.0145d" --radius "3m"
python3 demo_tests.py # sanity checks against the live API
About Trillian
Trillian organizes astronomical data spatially rather than by mission or archive: one interface over files that remain distributed across their home archives (MAST, IPAC, and others), backed by a metadata index of tens of millions of files. Its development has been supported by a NASA Astrophysics Data Analysis Program grant, an AWS Open Data resource award, and the Mozilla Science Lab. This MCP server is a thin, public layer over its REST API.
Regenerating the demos
The demo animations are scripted replays built from captured live responses (no screen recording involved):
sh demos/render.sh # rebuilds casts and renders SVGs (needs node for npx)
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