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cxg-census-mcp

cxg-census-mcp

by MaxMLang
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

list_datasets

Find and list datasets from the CZ CELLxGENE Census using filters for organism, cell type, tissue, and more, sorted by cell count.

Instructions

List datasets matching a structured filter, sorted by cell count.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "filters": "<filters>"
    },
    "name": "list_datasets"
  }
}

Input Schema

NameRequiredDescriptionDefault
filtersYes
limitNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

C2.8/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It only mentions sorting by cell count, omitting information about read-only nature, pagination, response format, or any side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

While extremely concise, the description is under-specified for the tool's complexity. It fails to earn its place by omitting critical context, making it more of a vague statement than an informative guide.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the nested input schema, no output schema, and many sibling tools, the description is incomplete. It does not explain what a structured filter entails or how to construct it, leaving the agent under-informed for successful invocation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, yet the description adds no parameter-level details. 'Structured filter' is vague and does not clarify the complex nested schema, leaving the agent to infer parameter usage from the schema alone.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('List datasets'), the resource ('datasets'), and key details ('matching a structured filter, sorted by cell count'). It effectively distinguishes the tool from siblings like count_cells and aggregate_expression by focusing on listing with sorting.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives no guidance on when to use this tool versus alternatives, nor does it mention any prerequisites or exclusions. It provides no context about when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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