protein-tools-mcp

Overview Schema Source Related Servers Discussions Admin

read_fasta

Parse FASTA files or raw text to extract one or more sequence records, returning sequences, types, and metadata for downstream protein analysis.

Instructions

Read one or more sequences from a FASTA file or text.

Accepts a FASTA file path (is_file=True) or raw FASTA text (is_file=False). Returns the full parsed records including sequences, types, and metadata.

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": {
      "source": "<source>"
    },
    "name": "read_fasta"
  }
}

Input Schema

Name	Required	Description	Default
`source`	Yes
`is_file`	No
`normalize`	No
`sequence_index`	No

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 20, 2026

TDQS

B3.2/5.0

Behavior3/5

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

No annotations are provided, so the description carries the full behavioral burden. It discloses that input can be a path or raw text and that it returns parsed records with sequences/types/metadata, but says nothing about error behavior (e.g. malformed FASTA), how 'normalize' affects parsing, or what happens with sequence_index. For a read-only tool the risk is low, but the disclosure is thin.

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?

Three short sentences with no filler, and the key distinction (file path vs. raw text) is front-loaded. Efficiently sized for the tool's complexity.

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

Completeness3/5

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

An output schema exists, so the description need not detail return values, and it sensibly does not. But with 4 parameters at 0% schema coverage and no annotations, the description leaves normalize and sequence_index unexplained, which is a real gap for correct invocation.

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?

Schema description coverage is 0%, so the description must compensate for all four parameters. It explains 'source' and 'is_file' (path vs. text), but 'normalize' and 'sequence_index' are never mentioned in the schema or the description, leaving half the parameters semantically opaque.

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?

States a specific verb (Read) and resource (sequences from a FASTA file or text), and clarifies the two input modes. It does not differentiate itself from related siblings like fasta_stats or detect_sequence_type, but the core purpose is unambiguous.

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?

Usage is implied by the is_file=True/False duality, which tells the agent which mode to pick for a path vs. raw text. However, there is no explicit guidance on when to use this tool versus siblings such as fasta_stats, detect_sequence_type, or sequence_from_pdb, and no exclusions are stated.

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