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uniprot-mcp

uniprot-mcp

by fzlzjerry
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

get_entry

Retrieve a UniProtKB entry by providing an accession number. Select the output format: summary, JSON, FASTA, TXT, or GFF.

Instructions

Fetch one UniProtKB entry.

'summary' returns a clean digest: protein/gene names, organism, length, function, subcellular location, family/domains, key features, PTMs, keywords, and top cross-references (PDB, AlphaFold, Ensembl, RefSeq, InterPro, GO). Use 'json' for the complete record, 'fasta' for the sequence, 'txt' for the flat file, or 'gff' for feature coordinates.

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": {
      "accession": "<accession>"
    },
    "name": "get_entry"
  }
}

Input Schema

NameRequiredDescriptionDefault
accessionYesUniProtKB accession, e.g. 'P38398' or 'P04637'.
formatNo'summary' = curated digest (default); 'json' = full record; 'fasta' = sequence; 'txt' = flat file; 'gff' = features.summary

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations, the description carries full burden. It details what each format returns, but does not explicitly state that the operation is read-only or mention error handling.

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 with two sentences. The first sentence states the purpose, the second explains formats. No unnecessary words.

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 output schema exists and schema coverage is full, the description adequately covers functionality. It could better differentiate from siblings, but is complete for a fetch tool.

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 coverage is 100%, baseline 3. The description adds value by elaborating on the 'format' parameter options, especially the content of 'summary', going beyond the enum names.

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 one UniProtKB entry,' specifying the resource and action. It distinguishes itself from siblings by detailing available output formats.

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 explains when to use each format (summary for digest, json for full record, etc.), but does not contrast with sibling tools like 'get_fasta'.

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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