# CZ CELLxGENE Census

> Use this tool when you need to analyze and query large single-cell RNA-seq datasets, such as those from the Chan Zuckerberg Initiative's data atlas, to gain insights into cell types, gene expression, and dataset metadata. It solves problems related to data exploration, filtering, and visualization, and provides outputs including cell counts, gene expression profiles, and dataset lists. Use CZ CELLxGENE Census when working with single-cell RNA-seq data to streamline your analysis workflow and obtain reliable results with full provenance.

Canonical page: https://skillsregistry.net/skills/maxmlang-cxg-census  
JSON: https://api.skillsregistry.net/v1/skills/maxmlang-cxg-census

## Description

CZ CELLxGENE Census is an unaffiliated community MCP server for querying the Chan Zuckerberg Initiative's single-cell RNA-seq data atlas. It provides 13 tools including cell counting, gene expression aggregation, dataset listing, and ontology resolution with cost caps and full provenance on every response. Published on PyPI and actively maintained.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-09-28

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/maxmlang-cxg-census)
- **Repository:** <https://github.com/maxmlang/cxg-census-mcp>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "maxmlang-cxg-census"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/maxmlang-cxg-census` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/maxmlang-cxg-census/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt