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just-prs-mcp

just-prs-mcp

by dna-seq
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

Search PGS scores

search_scores
Read-onlyIdempotent

Search polygenic scores in the PGS Catalog by free text, matching IDs, traits, and score names. Optionally filter by genome build to get relevant matches.

Instructions

Search the PGS Catalog for polygenic scores by free text.

Case-insensitive substring match across PGS ID, score name, reported trait, and EFO trait. Optionally filter to a genome build (GRCh37 / GRCh38, harmonized cross-build scores included). Returns up to limit matches with their key metadata.

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": {
      "query": "<query>"
    },
    "name": "search_scores"
  }
}

Input Schema

NameRequiredDescriptionDefault
limitNo
queryYes
genome_buildNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.5.0
  2. Removedv0.2.0
  3. First observedv0.1.0

TDQS

A4.8/5.0
Behavior5/5

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

Annotations already indicate read-only and idempotent behavior, but the description adds key behavioral details: case-insensitivity, substring matching, fields searched, handling of genome builds with harmonized cross-build scores, and the limit on returned matches. This significantly enriches the static annotation information.

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

Conciseness5/5

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

The description is concise, front-loaded with the main purpose, and every sentence adds value. It covers behavior, parameters, and edge cases in three sentences without redundancy.

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

Completeness5/5

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

Given the tool's moderate complexity and zero parameter descriptions in the schema, the description covers all relevant aspects: search semantics, optional filters, special handling (cross-build), and result limits. An output schema exists, so return format details are unnecessary.

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

Parameters5/5

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

Schema description coverage is 0%, yet the description compensates by explaining all three parameters: 'free text' for query, 'filter to a genome build (GRCh37 / GRCh38, harmonized cross-build scores included)' for genome_build, and 'up to limit matches' for limit. It adds meaning far beyond the bare types.

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 tool 'Search the PGS Catalog for polygenic scores by free text', providing a specific verb and resource. It further distinguishes by listing exact match fields (PGS ID, score name, reported trait, EFO trait) and optional filtering, differentiating it from sibling search tools like search_traits.

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

Usage Guidelines4/5

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

The description gives clear context on how the search behaves (case-insensitive substring match) and when filters apply, but does not explicitly mention when not to use it or name alternative tools. The context is sufficient for basic usage without explicit exclusions.

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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