BioPython MCP Server

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fetch_sequence_by_id

Fetch a biological sequence from NCBI databases by providing a sequence identifier and database name (e.g., nucleotide, protein). Requires email for NCBI compliance.

Instructions

Fetch a sequence from NCBI database by ID.

Args: db: Database name ('nucleotide', 'protein', etc.) seq_id: Sequence identifier email: Email address for Entrez (required by NCBI)

Returns: Dictionary containing sequence information

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": {
      "db": "<db>",
      "seq_id": "<seq_id>"
    },
    "name": "fetch_sequence_by_id"
  }
}

Input Schema

Name	Required	Default
`db`	Yes
`seq_id`	Yes
`email`	No	user@example.com

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.8Feb 5, 2026

TDQS

C2.7/5.0

Behavior2/5

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

No annotations provided, so the description carries full burden. It does not disclose side effects, error behavior, or authentication needs. The return type is mentioned but no details on edge cases like missing IDs.

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

Conciseness4/5

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

Concise with clear docstring format separating Args and Returns. No unnecessary text, but could be slightly more compact.

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

Completeness2/5

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

Given the complexity (3 parameters, no enums, output schema exists), the description is incomplete. It lacks usage context, error handling, and differentiation from many sibling tools. The output schema may help but is not shown.

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

Parameters2/5

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

The schema has 0% description coverage, so the description must compensate. It briefly explains each parameter (db, seq_id, email) but lacks details like valid database names, ID formats, or the effect of the default email. Minimal value added beyond names.

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 clearly states it fetches a sequence from NCBI by ID, using a specific verb and resource. However, it does not distinguish from sibling tools like fetch_genbank or entrez_fetch, which also fetch sequences.

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?

No guidance on when to use this tool versus alternatives. It does not mention prerequisites, required NCBI account, or rate limits. The only usage hint is that email is required by NCBI, but no further context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.