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Augmented-Nature

PubChem MCP Server

search_bioassays

Search for biological assays by target protein, gene name, or data source using PubChem MCP Server. Retrieve detailed bioassay data to support chemical and biological research.

Instructions

Search for biological assays by target, description, or source

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
max_recordsNoMaximum number of results (1-1000, default: 100)
queryNoGeneral search query
sourceNoData source (e.g., ChEMBL, NCGC)
targetNoTarget protein or gene name

Implementation Reference

  • The main handler function for the 'search_bioassays' tool. It currently returns a placeholder response indicating that the bioassay search is not yet implemented.
    private async handleSearchBioassays(args: any) {
      return { content: [{ type: 'text', text: JSON.stringify({ message: 'Bioassay search not yet implemented', args }, null, 2) }] };
    }
  • Input schema for the 'search_bioassays' tool, specifying optional parameters: query, target, source, and max_records.
    inputSchema: {
      type: 'object',
      properties: {
        query: { type: 'string', description: 'General search query' },
        target: { type: 'string', description: 'Target protein or gene name' },
        source: { type: 'string', description: 'Data source (e.g., ChEMBL, NCGC)' },
        max_records: { type: 'number', description: 'Maximum number of results (1-1000, default: 100)', minimum: 1, maximum: 1000 },
      },
      required: [],
    },
  • src/index.ts:575-588 (registration)
    Registration of the 'search_bioassays' tool in the ListToolsRequestSchema response, including name, description, and input schema.
    {
      name: 'search_bioassays',
      description: 'Search for biological assays by target, description, or source',
      inputSchema: {
        type: 'object',
        properties: {
          query: { type: 'string', description: 'General search query' },
          target: { type: 'string', description: 'Target protein or gene name' },
          source: { type: 'string', description: 'Data source (e.g., ChEMBL, NCGC)' },
          max_records: { type: 'number', description: 'Maximum number of results (1-1000, default: 100)', minimum: 1, maximum: 1000 },
        },
        required: [],
      },
    },
  • src/index.ts:780-781 (registration)
    Dispatch logic in the CallToolRequestSchema handler that routes calls to the 'search_bioassays' tool to its handler function.
    case 'search_bioassays':
      return await this.handleSearchBioassays(args);
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the search action but fails to describe key traits like whether it's read-only, if there are rate limits, authentication needs, pagination behavior, or what the output format looks like. This is a significant gap for a search tool with zero annotation coverage.

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 a single, efficient sentence that front-loads the core purpose without unnecessary words. Every part of the sentence contributes directly to understanding the tool's function, making it highly concise and well-structured.

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

Completeness2/5

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

Given the complexity of a search tool with 4 parameters, no annotations, and no output schema, the description is incomplete. It lacks details on behavioral traits, usage context, and output expectations, which are crucial for an AI agent to invoke the tool correctly and interpret results. The high schema coverage doesn't compensate for these gaps.

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?

The description lists searchable fields ('target, description, or source'), which partially maps to the input schema parameters (target, source, query). However, with 100% schema description coverage, the schema already documents all parameters thoroughly, so the description adds minimal value beyond what's in the structured data. The baseline score of 3 reflects adequate but not enhanced parameter semantics.

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 clearly states the action ('Search for biological assays') and the searchable fields ('by target, description, or source'), which is specific and informative. However, it doesn't explicitly differentiate from sibling tools like 'search_by_target' or 'search_compounds', which might have overlapping functionality, preventing a perfect score.

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?

The description provides no guidance on when to use this tool versus alternatives, such as 'search_by_target' or 'search_compounds' from the sibling list. It lacks context about use cases, exclusions, or prerequisites, leaving the agent to infer usage based on the tool name alone.

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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