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cxg-census-mcp

cxg-census-mcp

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github.comScience & Education0Updated 15w ago

About cxg-census-mcp

cxg-census-mcp lets research agents query the CZ CELLxGENE Discover Census with ontology-aware filters and traceable results. It focuses on single-cell atlas exploration without hosting or mirroring the data.

Key features

  1. 01Ontology-aware term resolution
  2. 02Cell counts and expression aggregation
  3. 03Dataset and Census version inspection
  4. 04Query cost caps and tier routing
  5. 05Provenance and attribution on responses

Use cases

  1. 01Compare cell composition across cohorts
  2. 02Explore gene expression in single-cell data
  3. 03Resolve tissue and disease terms
  4. 04Export query snippets for analysis

MCP support

Exposes Census query and inspection tools, documentation resources, and workflow prompts to MCP clients. It supports progress and cancellation notifications.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"maxmlang-cxg-census": {
"command": "uvx",
"args": [
"cxg-census-mcp"
]
}
}
}
Run commanduvx cxg-census-mcp

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
pypicxg-census-mcp0.1.2

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

cxg-census-mcp

PyPI PyPI downloads CI License: MIT Python Ruff Checked with mypy pre-commit MCP Status: alpha Last commit

An MCP server that lets LLM agents query the CZ CELLxGENE Discover Census single-cell atlas without lying about it — ontology-aware filters, cost caps, full provenance + attribution on every response. Drop it into Cursor / Claude Desktop / Claude Code and ask questions like "Visualize the cell-type composition of the human lung" in plain English.

demo

Independent / unaffiliated. Not affiliated with, endorsed by, or sponsored by the Chan Zuckerberg Initiative (CZI), EMBL-EBI, the U.S. Census Bureau, or anyone else. "CELLxGENE" is a CZI mark; references here are descriptive (nominative) use only.

No warranty. MIT-licensed source, "as is". Research/exploration tool — not a clinical or diagnostic instrument. Always verify results before publication. See LICENSE for the full trademark and content attribution notice, and SECURITY.md for the threat model and known-issues policy.

Alpha (v0.1.2). CHANGELOG.md

Demos

Healthy vs COVID-19 lung, side-by-side. Two parallel queries, the disease_multi_value_v7 schema-drift rewrite kicks in for the COVID cohort, attribution from both contributing dataset sets surfaces in the same chat turn.

https://github.com/user-attachments/assets/c836f225-5075-4643-87aa-70d311bc5fd2

Cell-type composition of human lung in one query. Free-text "lung" resolved to UBERON:0002048, routed through tissue_general, every CURIE labeled, all in a single Tier-0 call.

https://github.com/user-attachments/assets/b0e10ca7-e46b-4e5f-ae63-11949d328c4d

(Videos render on GitHub. On PyPI they appear as bare URLs — head to the GitHub README to watch.)

More prompts in docs/example-questions.md.

Architecture at a glance

                 ┌──────────────────────────────────────────────┐
   MCP client    │   tools/        thin MCP wrappers, no logic  │
   (Claude,  ─►  │     │                                        │
    Cursor,      │     ▼                                        │
    Code, …)     │   planner/      FilterSpec → QueryPlan,      │
                 │     │           cost estimate, tier routing  │
                 │     ▼                                        │
                 │   ontology/     OLS4 + hint overlay,         │
                 │     │           CL/UBERON/MONDO expansion    │
                 │     ▼                                        │
                 │   execution/    Tier 0  facet counts         │
                 │     │           Tier 1  chunked obs scan     │
                 │     │           Tier 2  expression aggregate │
                 │     │           Tier 9  refuse → snippet     │
                 │     ▼                                        │
                 │   clients/      OLS4 (HTTPS) + Census/SOMA   │
                 │                                              │
                 │   caches/       OLS, facet, plan, filter LRU │
                 │   models/       Response envelope w/         │
                 │                 attribution + provenance     │
                 └──────────────────────────────────────────────┘
                                    │
                                    ▼
                       ┌────────────────────────┐
                       │ EBI OLS4 (ontology)    │
                       │ CZ CELLxGENE Census    │
                       │ (CC BY 4.0 data)       │
                       └────────────────────────┘

Full architecture notes: docs/architecture.md. Tool reference: docs/tool-reference.md. Example questions: docs/example-questions.md.

Install

From PyPI (recommended):

uv tool install "cxg-census-mcp[census]"
cxg-census-mcp                       # speaks MCP over stdio

Or with pip:

pip install "cxg-census-mcp[census]"

Without the [census] extra you get mock mode (deterministic fixtures) — handy for offline demos and verifying your MCP client config without pulling tiledbsoma's ~1 GB of native deps.

From source (for development):

git clone https://github.com/MaxMLang/cxg-census-mcp
cd cxg-census-mcp
uv sync --extra dev --extra census
uv run cxg-census-mcp

MCP client config

Cursor (~/.cursor/mcp.json) and Claude Desktop (~/Library/Application Support/Claude/claude_desktop_config.json on macOS) both expect the same shape. Cleanest is uvx once installed from PyPI:

{
  "mcpServers": {
    "cxg-census": {
      "command": "/absolute/path/to/uvx",
      "args": ["--from", "cxg-census-mcp[census]", "cxg-census-mcp"]
    }
  }
}

Use the absolute path to uvx (which uvx from your shell). MCP clients spawn the server in a non-interactive subprocess that doesn't source your shell rc, so a bare "uvx" will fail with No such file or directory.

If you cloned from source instead, point at the checkout:

{
  "mcpServers": {
    "cxg-census": {
      "command": "/absolute/path/to/uv",
      "args": ["--directory", "/path/to/cxg-census-mcp", "run", "cxg-census-mcp"]
    }
  }
}

Claude Code:

claude mcp add cxg-census -- /absolute/path/to/uvx --from "cxg-census-mcp[census]" cxg-census-mcp

Quit + relaunch your client (⌘Q on macOS — closing the window isn't enough) and the server should show up in the MCP panel with 13 tools.

Tools (13 total)

Workflow: census_summary, get_census_versions, count_cells, list_datasets, gene_coverage, aggregate_expression, preview_obs, export_snippet, get_server_limits.

Inspection: resolve_term, expand_term, term_definition, list_available_values.

Plus MCP resources (markdown docs at cxg-census-mcp://docs/{slug}), prompts (census_workflow, disambiguation), and cooperative progress / cancellation notifications. Details in docs/tool-reference.md.

Configuration

All env vars use the CXG_CENSUS_MCP_ prefix. Most useful:

VariableDefaultPurpose
CXG_CENSUS_MCP_CENSUS_VERSIONstableCensus release to pin
CXG_CENSUS_MCP_CACHE_DIRplatformdirs defaultDisk cache root
CXG_CENSUS_MCP_MOCK_MODE0If 1, never opens a real Census handle
CXG_CENSUS_MCP_LOG_LEVELWARNINGstdlib log level

Full list and validation: src/cxg_census_mcp/config.py.

Development & operations

Quick loop:

make install-all                 # uv sync --extra dev --extra census
make lint typecheck test         # ruff + mypy + pytest (mock mode)
make cov                         # tests + coverage HTML in ./htmlcov
make audit                       # pip-audit on locked production deps

Operational tasks (cache pre-warm, schema diff, container build, metrics dump, plan-cache vacuum, weekly hint/facet refresh) live in the Makefile and are documented in docs/operational-playbook.md.

Documentation index

TopicWhere
System architecturedocs/architecture.md
Tool referencedocs/tool-reference.md
Example agent questionsdocs/example-questions.md
Ontology resolutiondocs/ontology-resolution.md
Schema-drift handlingdocs/schema-drift-format.md
Census version pinningdocs/version-pinning.md
Progress / cancellationdocs/progress-and-cancellation.md
Error modeldocs/error-model.md
Known limitationsdocs/limitations.md
Ops runbookdocs/operational-playbook.md
ChangelogCHANGELOG.md

License & attribution

Source code: MIT. The MIT license covers only the code in this repository, not the upstream data, ontologies, or third-party trademarks.

  • Data. Tool responses are derived (filtered/aggregated) from the CZ CELLxGENE Discover Census, distributed by the Chan Zuckerberg Initiative under CC BY 4.0. Every response carries an attribution field; downstream users must preserve attribution and indicate that changes were made.
  • Ontologies are fetched via EBI Ontology Lookup Service (OLS4) from CL, UBERON, MONDO, EFO, HANCESTRO, and others; each carries its own license.
  • Trademarks ("CELLxGENE", "Cursor", "Claude", "Anthropic", "Model Context Protocol", …) belong to their respective owners. Use here is descriptive only and does not imply affiliation.

This project is a client of the CZ CELLxGENE Discover Census; it does not host, mirror, or redistribute Census data.

Full notice in LICENSE.

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