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Official STRING Database MCP Server

STRING: Resolves protein identifiers to metadata

string_resolve_proteins

Resolve protein identifiers into annotated STRING metadata: gene symbols, descriptions, sequences, domains, species, and STRING IDs. Translate raw gene or UniProt IDs into readable entries.

Instructions

Maps one or more protein identifiers to their corresponding STRING metadata, including: gene symbol, description, sequence, domains, species, and internal STRING ID.

This method is useful for translating raw identifiers into readable, annotated protein entries.

Example input: "TP53%0dSMO"

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
speciesNoNCBI taxonomy ID (e.g. 9606 for human) or STRING genome ID (e.g. STRG0AXXXXX for uploaded genomes).
proteinsYesOne or more input protein identifiers (gene symbols, UniProt IDs, etc.), separated by carriage return (%0d).
show_sequenceNoInclude sequences. Use only if the user requests sequence data.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.13.0

TDQS

A3.6/5.0
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 the output content (metadata fields) and includes an input example, but it does not explicitly state that the operation is read-only, whether it has rate limits, or any authentication requirements. The gaps are moderate for a query tool.

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 short, front-loaded, and structured into three brief sentences. The example input duplicates a schema example slightly, but overall it is efficient and easy to parse.

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 the tool's moderate complexity, full schema description coverage, and the presence of an output schema, the description is nearly complete for selection and invocation. It lacks explicit sibling differentiation, but the purpose and return metadata are sufficiently described.

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 description coverage is 100%, so the input schema already documents all three parameters in detail. The description only restates that one or more protein identifiers are accepted and gives an example that duplicates the schema example. It adds no meaningful parameter semantics beyond what the schema provides, so the baseline score of 3 applies.

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 a specific verb and resource: 'Maps one or more protein identifiers to their corresponding STRING metadata.' It also enumerates the metadata types returned, making the tool's purpose clear. However, it does not explicitly differentiate itself from sibling tools such as string_sequence_search or string_functional_annotation.

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 provides clear usage context: 'useful for translating raw identifiers into readable, annotated protein entries.' This tells an agent when the tool is appropriate. It does not, however, mention when not to use it or name alternative sibling tools for overlapping tasks.

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