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STRING: Get links to interaction evidence pages

string_interaction_evidence

Retrieve direct STRING evidence page links for protein-protein interaction pairs, showing experimental, publication, and database support. Use when an evidence URL is needed, not to judge support.

Instructions

Retrieves direct links to STRING evidence pages for protein–protein interaction pairs.

Use this tool only when a STRING evidence page/link is needed. To determine whether an interaction is supported, use string_interactions_query_set.

It returns URLs linking to STRING’s evidence pages, which display the underlying data sources (experimental results, publications, and curated databases) supporting each predicted interaction.
A URL can be generated even for unsupported pairs; the URL is not itself an interaction verdict. The returned page lets the user explore functional, physical, and regulatory relationship views through its tabs.

Parameters:

identifier_a: Query protein identifier (Protein A)
identifiers_b: One or more target protein identifiers (Protein B), separated by %0d
species: NCBI taxonomy ID (e.g. 9606 for human or 10090 for mouse)
network_type: Set to physical for physical evidence or regulatory for directed regulatory evidence.

Typical user questions that should trigger this tool:

"Can you show me the STRING evidence for this interaction?"
"Show me the details supporting this interaction."
"What supports the interaction between TP53 and MDM2?"
"Where can I find the STRING evidence for this pair?"

Input Schema

TableJSON Schema

Name	Required	Description
`species`	No	NCBI/STRING taxon (e.g. 9606 for human, or STRG0AXXXXX for uploaded genomes).
`identifier_a`	Yes	Protein A identifier.
`network_type`	No	Set physical for physical-interaction evidence or regulatory for directed regulatory evidence. Omit for the functional interaction evidence page.
`identifiers_b`	Yes	One or more protein B identifiers, separated by %0d.

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.13.0Sep 30, 2026

TDQS

A4.6/5.0

Behavior4/5

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

No annotations exist, so the description carries the burden — and it does real work by warning that a URL can be generated even for unsupported pairs and is not itself an interaction verdict, plus describing what the linked page shows (experimental results, publications, curated databases). It does not cover auth needs, rate limits, or error behavior, so it is strong but not complete.

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?

Core routing rule and the unsupported-pair caveat are front-loaded in the first lines, then parameters, then triggers. The four example questions are somewhat redundant with the usage rule and add length, but they are skimmable and not misleading.

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

Completeness5/5

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

For a 4-parameter link-generator with an output schema, the description supplies the alternative tool, the semantic caveat about non-verdict URLs, parameter formats, and trigger scenarios. Nothing an agent needs to call it correctly is missing.

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

Parameters4/5

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

Schema coverage is already 100%, so the baseline is 3; the description adds usable context by giving concrete species examples (9606 human, 10090 mouse) and restating the %0d separator convention. It slightly under-describes network_type by naming only `physical` and `regulatory` and omitting the functional/omit behavior that the schema documents.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a precise verb+resource (retrieves links to STRING evidence pages for protein–protein interaction pairs) and explicitly distinguishes itself from the sibling `string_interactions_query_set`, which resolves support status. An agent can tell the two apart without opening either schema.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Gives an explicit inclusion rule ('use this tool only when a STRING evidence page/link is needed') and names the alternative for support determination. The sample trigger questions reinforce the intended routing with concrete user phrasings.

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

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