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STRING Database MCP Server

by org.string-db

STRING: Help / FAQ

string_help

Provides explanatory text for STRING features and limitations.

Use this tool when the user question involves:

  • What is STRING is or how to use the tool (how_to_use_string, cytoscape)

  • functionality not available via MCP tools (e.g. GSEA, regulatory networks, large datasets).

  • meaning of the lines in the network (line_colors)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
topicNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed2 schema fields changed
    • removedInput schema / $defs
      Removed value: -{
-  "HelpTopic": {
-    "enum": [
-      "gsea",
-      "large_input",
-      "cytoscape",
-      "scores",
-      "missing_proteins",
-      "missing_species",
-      "proteome_annotation",
-      "regulatory_networks",
-      "how_to_use_string",
-      "line_colors",
-      "version_and_citation"
-    ],
-    "type": "string"
-  }
-}
    • changedInput schema / properties / topic / anyOf
      Previous value: -[
-  {
-    "anyOf": [
-      {
-        "$ref": "#/$defs/HelpTopic"
-      },
-      {
-        "type": "null"
-      }
-    ],
-    "description": "Optional. Help topic to display. If omitted, returns the available topics."
-  },
-  {
-    "type": "null"
-  }
-]New value: +[
+  {
+    "anyOf": [
+      {
+        "enum": [
+          "gsea",
+          "large_input",
+          "cytoscape",
+          "scores",
+          "missing_proteins",
+          "missing_species",
+          "proteome_annotation",
+          "regulatory_networks",
+          "how_to_use_string",
+          "line_colors",
+          "version_and_citation"
+        ],
+        "type": "string"
+      },
+      {
+        "type": "null"
+      }
+    ],
+    "description": "Optional. Help topic to display. If omitted, returns the available topics."
+  },
+  {
+    "type": "null"
+  }
+]
  2. First observed

TDQS

A4.7/5.0
Behavior4/5

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

With no annotations, the description carries the full burden. It explains the tool returns explanatory text and gives context on the type of content covered. It doesn't mention side effects (none expected for a help tool) or details about behavior when the topic is omitted, but the schema covers that, so the description adds reasonable transparency.

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

Conciseness5/5

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

The description is concise and front-loaded with the purpose, followed by a tight bulleted list of usage scenarios. Every sentence earns its place, and the structure makes it easy to scan. Minor typo ('What is STRING is') does not detract from clarity.

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?

Given the tool is a simple help/FAQ tool with an output schema and a single optional parameter, the description provides sufficient context: what it does, when to use it, and examples of relevant topics. It is complete for its complexity.

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?

The schema describes the 'topic' parameter as optional and notes the behavior when omitted. The tool description adds semantic value by grouping example topics (how_to_use_string, cytoscape, line_colors) into meaningful categories, helping the agent map user questions to appropriate parameter values.

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?

The description clearly states the tool provides explanatory text for STRING features and limitations, which is a specific verb+resource. It distinguishes from sibling tools by positioning itself as a help/FAQ tool rather than a data retrieval tool, and reinforces this with example topics.

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?

Explicitly states 'Use this tool when the user question involves:' and lists three distinct scenarios, including guidance for functionality not available via MCP tools. This clearly differentiates when to use this tool versus alternatives.

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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TDQS

A3.6/5.0
Disambiguation2/5

Several tool pairs have overlapping purposes: string_network_link and string_visual_network both return network URLs with nearly identical behavior, and string_all_interaction_partners vs string_interactions_query_set both query interactions, differing subtly in scope. The enrichment/annotation tools also share boundaries, making it difficult for agents to disambiguate without reading detailed descriptions.

Naming Consistency3/5

All tools share the 'string_' prefix, but the pattern is inconsistent: some are verb-first (create_file, resolve_proteins), some are noun-first (interactions_query_set, network_link), and some are bare nouns (enrichment, homology). This mixed convention reduces predictability.

Tool Count4/5

At 17 tools, the server is slightly above the ideal range, but it covers a broad domain: interactions, networks, enrichment, annotation, homology, species resolution, and sequence search. The count is justified by the complexity of the STRING database.

Completeness4/5

The tool set covers core STRING workflows: querying interactions, constructing networks, computing enrichment, retrieving annotations, identifying homologs, mapping IDs, and exporting data. Minor gaps exist (e.g., direct edge-list tables and intricate interaction score details), but the overall surface is robust.

Resources