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BioPython MCP Server

BioPython MCP Server

by kmaneesh
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Hybrid

fetch_uniprot

Retrieve a protein sequence from UniProt using an accession or ID. Choose output format: FASTA, text, or XML. Ideal for sequence analysis workflows.

Instructions

Fetch a protein sequence from UniProt.

Args: uniprot_id: UniProt accession or ID format: Output format - 'fasta', 'txt', 'xml' (default: 'fasta')

Returns: Dictionary containing the UniProt record

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": {
      "uniprot_id": "<uniprot_id>"
    },
    "name": "fetch_uniprot"
  }
}

Input Schema

NameRequiredDescriptionDefault
uniprot_idYes
formatNofasta

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.8

TDQS

A4.2/5.0
Behavior4/5

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

No annotations are provided, so the description carries the full burden. It discloses that the tool fetches a sequence and returns a dictionary, and it lists parameter options. However, it does not detail error handling or potential failures.

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 succinctly structured with Args/Returns sections, no redundant information, and every sentence is informative. It is front-loaded with the core purpose.

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

Completeness4/5

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

Given the tool's simplicity and the presence of an output schema, the description is largely complete. It covers the purpose, parameters, and return format. Missing are details on input validation or error conditions, but these are acceptable gaps for a basic fetcher.

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

Parameters4/5

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

Schema description coverage is 0%, but the description explains both parameters: uniprot_id as the accession/ID and format with allowed values ('fasta', 'txt', 'xml') and default. This meaningfully supplements the bare schema.

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 'Fetch a protein sequence from UniProt', specifying a unique resource (UniProt) and action. This distinguishes it from siblings like fetch_genbank (GenBank) and fetch_pdb_structure (PDB).

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 implies usage for retrieving UniProt sequences but does not explicitly compare to alternatives like fetch_sequence_by_id or state when not to use it. Guidance is implicit rather than explicit.

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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