BioPython MCP Server

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multiple_sequence_alignment

Align multiple biological sequences using ClustalW or other algorithms to identify conserved regions and evolutionary relationships.

Instructions

Perform multiple sequence alignment.

Args: sequences: List of sequences to align algorithm: Alignment algorithm to use (default: 'clustalw')

Returns: Dictionary containing alignment results

Note: This is a placeholder that demonstrates the structure. Full implementation would require external tools like MUSCLE or Clustal Omega.

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": {
      "sequences": "<sequences>"
    },
    "name": "multiple_sequence_alignment"
  }
}

Input Schema

Name	Required	Description	Default
`sequences`	Yes
`algorithm`	No		clustalw

Output Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.8Feb 5, 2026

TDQS

B3.1/5.0

Behavior3/5

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

Without annotations, the description must disclose behavior. It notes this is a placeholder requiring external tools, which is transparent. However, it lacks details on side effects, performance, or 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.

Conciseness4/5

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

The description is well-structured with Args/Returns/Note sections. It is concise, though the first sentence is redundant with the name. Overall efficient.

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 context signals (low schema coverage, no enums, output schema exists but not shown), the description provides basic info but is incomplete. The placeholder note indicates it's not fully functional, reducing completeness for an AI agent.

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

Parameters3/5

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

Schema coverage is 0%, so description adds meaning: 'sequences: List of sequences to align' and 'algorithm: Alignment algorithm to use (default: 'clustalw')'. This clarifies purpose but does not specify sequence format or algorithm options.

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 the tool performs multiple sequence alignment, a specific operation on sequences. It distinguishes from sibling tools like pairwise_align (pairwise) and build_phylogenetic_tree (post-alignment). However, it does not elaborate on the exact output or scope.

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. The note about requiring external tools hints at limitations but does not explicitly compare to sibling tools or advise on selection criteria.

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