Skip to main content
Glama

foldseek_search_sequence

Identify similar protein structures and sequences by running FoldSeek easy-search with a FASTA query and the ProstT5 model.

Instructions

Run FoldSeek easy-search with a FASTA query and configured ProstT5 model.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modelNoprostt5-q4_0-gguf
evalueNo
threadsNo
use_gpuNo
databaseNoafdb_uniprot50_minimal
max_hitsNo
fasta_pathNo
fasta_textNo
sensitivityNo
output_modesNo
alignment_typeNo
timeout_secondsNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

The description is minimal and does not disclose behavioral traits beyond the basic action. No annotations are provided, so the description carries the full burden. There is no mention of prerequisites, side effects, auth needs, or performance considerations. A score of 2 indicates significant missing transparency.

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

Conciseness3/5

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

The description is a single short sentence, which is concise but lacks structure. It is not overly verbose, but it sacrifices completeness. A score of 3 reflects that it is adequately concise but not well-structured for an AI agent to parse efficiently.

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

Completeness1/5

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

Given the tool has 12 parameters, no schema descriptions, and no annotations, the description is severely incomplete. It does not explain what FoldSeek easy-search does, how the query is processed, what the return format is (despite having an output schema), or any other contextual information. This is inadequate for an AI agent to use effectively.

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?

With 0% schema description coverage, the description must add extensive parameter meaning. However, it only mentions 'FASTA query' (vaguely covering fasta_path/fasta_text) and 'configured ProstT5 model' (covering the model parameter). The other 10 parameters (evalue, threads, database, etc.) are completely undocumented. This is insufficient.

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 states the action (Run) and resource (FoldSeek easy-search) with a FASTA query and ProstT5 model. This is clear enough, but it does not differentiate from sibling tool foldseek_search_structure, which likely searches by structure instead of sequence. A 5 would require explicit differentiation.

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 like foldseek_search_structure or foldseek_validate_environment. The agent is left to infer from the name. This is a significant gap.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/AltriaPendragon49/foldseek-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server