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search_similar_compounds

Find chemically similar compounds in PubChem using Tanimoto similarity. Input a SMILES string to discover molecules with structural resemblance for research and analysis.

Instructions

Find chemically similar compounds using Tanimoto similarity

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
smilesYesSMILES string of the query molecule
thresholdNoSimilarity threshold (0-100, default: 90)
max_recordsNoMaximum number of results (1-10000, default: 100)

Implementation Reference

  • The handler function for 'search_similar_compounds' tool. Validates input using isValidSmilesArgs, performs POST request to PubChem similarity search endpoint with SMILES, threshold, and maxRecords, returns JSON response.
    private async handleSearchSimilarCompounds(args: any) {
      if (!isValidSmilesArgs(args)) {
        throw new McpError(ErrorCode.InvalidParams, 'Invalid similarity search arguments');
      }
    
      try {
        const threshold = args.threshold || 90;
        const maxRecords = args.max_records || 100;
    
        const response = await this.apiClient.post('/compound/similarity/smiles/JSON', {
          smiles: args.smiles,
          Threshold: threshold,
          MaxRecords: maxRecords,
        });
    
        return {
          content: [
            {
              type: 'text',
              text: JSON.stringify(response.data, null, 2),
            },
          ],
        };
      } catch (error) {
        throw new McpError(
          ErrorCode.InternalError,
          `Failed to search similar compounds: ${error instanceof Error ? error.message : 'Unknown error'}`
        );
      }
    }
  • src/index.ts:441-453 (registration)
    Registration of the 'search_similar_compounds' tool in the ListToolsRequestSchema response, including name, description, and input schema.
    {
      name: 'search_similar_compounds',
      description: 'Find chemically similar compounds using Tanimoto similarity',
      inputSchema: {
        type: 'object',
        properties: {
          smiles: { type: 'string', description: 'SMILES string of the query molecule' },
          threshold: { type: 'number', description: 'Similarity threshold (0-100, default: 90)', minimum: 0, maximum: 100 },
          max_records: { type: 'number', description: 'Maximum number of results (1-10000, default: 100)', minimum: 1, maximum: 10000 },
        },
        required: ['smiles'],
      },
    },
  • JSON Schema for input validation of the tool: requires 'smiles', optional 'threshold' (0-100) and 'max_records' (1-10000).
    inputSchema: {
      type: 'object',
      properties: {
        smiles: { type: 'string', description: 'SMILES string of the query molecule' },
        threshold: { type: 'number', description: 'Similarity threshold (0-100, default: 90)', minimum: 0, maximum: 100 },
        max_records: { type: 'number', description: 'Maximum number of results (1-10000, default: 100)', minimum: 1, maximum: 10000 },
      },
      required: ['smiles'],
    },
  • Helper validation function isValidSmilesArgs used in the handler to check input parameters matching the schema.
    const isValidSmilesArgs = (
      args: any
    ): args is { smiles: string; threshold?: number; max_records?: number } => {
      return (
        typeof args === 'object' &&
        args !== null &&
        typeof args.smiles === 'string' &&
        args.smiles.length > 0 &&
        (args.threshold === undefined || (typeof args.threshold === 'number' && args.threshold >= 0 && args.threshold <= 100)) &&
        (args.max_records === undefined || (typeof args.max_records === 'number' && args.max_records > 0 && args.max_records <= 10000))
      );
    };
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions the method ('Tanimoto similarity') but lacks details on what the tool returns (e.g., list of compounds with scores), performance characteristics (e.g., speed, database scope), or limitations (e.g., requires valid SMILES). This is a significant gap for a search tool with no 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 with zero waste. It's front-loaded with the core purpose and method, making it easy to parse. Every word earns its place without redundancy or unnecessary elaboration.

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 chemical similarity search tool with no annotations and no output schema, the description is incomplete. It doesn't explain return values (e.g., what data is included in results), error handling, or practical constraints. This leaves gaps for an AI agent to understand how to interpret and use the tool effectively.

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 input schema has 100% description coverage, providing clear details for all parameters (smiles, threshold, max_records). The description adds no additional parameter semantics beyond what's in the schema, such as explaining Tanimoto similarity in context or default behaviors. Baseline 3 is appropriate since the schema does the heavy lifting.

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 tool's purpose: 'Find chemically similar compounds using Tanimoto similarity.' It specifies the verb ('Find'), resource ('chemically similar compounds'), and method ('Tanimoto similarity'). However, it doesn't explicitly differentiate from sibling tools like 'search_compounds' or 'substructure_search,' which might offer alternative search methods.

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. It doesn't mention sibling tools like 'search_compounds' (which might be broader) or 'substructure_search' (which uses a different matching method), nor does it specify prerequisites or exclusions. Usage is implied by the description but not explicitly stated.

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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