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cxg-census-mcp

cxg-census-mcp

by MaxMLang
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

export_snippet

Execute a stored query plan to export single-cell data as AnnData, observation-only, or aggregate results. Use a call_id from a prior response.

Instructions

Runnable Python for a stored plan; pass call_id from a prior response.

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": {
      "call_id": "<call_id>"
    },
    "name": "export_snippet"
  }
}

Input Schema

NameRequiredDescriptionDefault
call_idYes
intentNoanndata

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

C2.1/5.0
Behavior2/5

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

No annotations are provided, so the description must disclose behavioral traits. It mentions 'Runnable Python' hinting at code execution, but does not confirm whether the tool is read-only or destructive, or describe any side effects, authentication needs, or rate limits.

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?

The description is a single sentence, which is concise, but it is under-specified and fails to provide necessary information. It is not effectively front-loaded with key details.

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 lack of output schema and annotations, the description should compensate but does not explain what the tool returns, its side effects, or how to correctly use the parameters. Context is incomplete for effective usage.

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

Parameters1/5

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

Schema description coverage is 0% and the description only mentions call_id, ignoring the intent parameter entirely. The description adds no meaning beyond the schema, which already provides enum choices for intent. For a tool with 2 parameters, this is insufficient.

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

Purpose3/5

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

The description states 'Runnable Python for a stored plan' and mentions passing a call_id from a prior response, which gives a general idea of executing a stored plan. However, it does not specify what 'export' means in terms of output or how it differs from siblings like 'aggregate_expression' or 'count_cells'.

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 implies that the tool should be used after obtaining a call_id from a prior response, but it does not provide explicit guidance on when to use this tool versus alternatives, or state any prerequisites or conditions.

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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