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cxg-census-mcp

cxg-census-mcp

by MaxMLang
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

aggregate_expression

Compute per-gene expression statistics grouped by cell type or other categories, with ontology-aware filters for organism, tissue, disease, and more.

Instructions

Per-gene expression stats by group; caps → export_snippet if over.

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>",
      "gene_ids": "<gene_ids>"
    },
    "name": "aggregate_expression"
  }
}

Input Schema

NameRequiredDescriptionDefault
filtersYes
gene_idsYes
group_byNocell_type
aggregationsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.2

TDQS

C2.4/5.0
Behavior2/5

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

With no annotations, the description must disclose behavioral traits. It mentions capping and redirection to export_snippet, which is useful. However, it omits critical details such as whether the tool is read-only, performance characteristics, or how results are truncated. The single behavioral disclosure is insufficient.

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

Conciseness3/5

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

The description is extremely short (two fragments) and lacks structure. While it is concise, it sacrifices essential information. Important details are missing, making it too minimal for an agent to use effectively.

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

Completeness1/5

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

Given the tool's complexity—nested filter objects, multiple parameters, no output schema—the description is severely incomplete. It does not explain filtering logic, available aggregations, grouping options, output format, or the capping threshold. An agent cannot infer correct usage from this description alone.

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?

The input schema has 0% description coverage and four top-level parameters (filters, gene_ids, group_by, aggregations), all with nested structures. The description fails to explain any of these parameters, their purposes, or how they influence results. It adds no semantic value beyond the schema itself.

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

Purpose4/5

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

The description states 'Per-gene expression stats by group' which clearly indicates aggregation of gene expression data across groups. The reference to 'caps → export_snippet if over' hints at a truncation behavior. However, it does not explicitly differentiate from sibling tools like census_summary or gene_coverage, which may also compute statistics.

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 provides no guidance on when to use this tool versus alternatives. It mentions a fallback to export_snippet but does not specify prerequisites, conditions for capping, or scenarios where other tools would be more appropriate.

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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