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BioPython MCP Server

BioPython MCP Server

by kmaneesh
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

get_pmc_url

Retrieve the full URL to a PubMed Central article by providing its PMC identifier, with or without the 'PMC' prefix.

Instructions

Get the URL for a PubMed Central article.

Args: pmc_id: PMC identifier (with or without 'PMC' prefix)

Returns: Full URL to PMC article page

Examples: >>> get_pmc_url("PMC3539452") 'https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3539452/'

>>> get_pmc_url("3539452")
'https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3539452/'

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": {
      "pmc_id": "<pmc_id>"
    },
    "name": "get_pmc_url"
  }
}

Input Schema

NameRequiredDescriptionDefault
pmc_idYes

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.8

TDQS

A4.2/5.0
Behavior3/5

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

With no annotations, the description bears full responsibility. It indicates the tool returns a URL string but does not mention error behavior (e.g., invalid ID, network issues) or confirm it is a read-only operation. Acceptable but incomplete.

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 extremely concise: one sentence for purpose, three short sections (Args, Returns, Examples), and every sentence adds value. No wasted words.

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 simplicity (one parameter, straightforward URL construction), the description fully covers what an agent needs: input flexibility and output format. Output schema exists, so return details are covered.

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 coverage is 0%, so the description provides all parameter information. It explains that pmc_id accepts both 'PMC' prefixed and bare numbers, with examples demonstrating both forms. This adds substantial meaning beyond the schema's 'string' type.

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 starts with 'Get the URL for a PubMed Central article', which clearly identifies the tool's action (get) and resource (URL for PMC article). It stands out from siblings like get_doi_url and pubmed_fetch.

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

Usage Guidelines3/5

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

The description does not explicitly state when to use this tool versus alternatives (e.g., get_doi_url, pubmed_fetch). Usage is implied through examples but lacks exclusions or prerequisites.

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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