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Augmented-Nature

PubChem MCP Server

calculate_descriptors

Compute molecular descriptors and fingerprints for chemical compounds using PubChem CID and descriptor type options. Analyze properties, topological features, and 3D structures for chemical data insights.

Instructions

Calculate comprehensive molecular descriptors and fingerprints

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cidYesPubChem Compound ID (CID)
descriptor_typeNoType of descriptors (default: all)

Implementation Reference

  • The handler function that implements the core logic for the 'calculate_descriptors' tool. It currently returns a placeholder response indicating the feature is not yet implemented.
    private async handleCalculateDescriptors(args: any) {
      return { content: [{ type: 'text', text: JSON.stringify({ message: 'Descriptor calculation not yet implemented', args }, null, 2) }] };
    }
  • Input schema definition for the 'calculate_descriptors' tool, specifying parameters like CID and descriptor type.
    inputSchema: {
      type: 'object',
      properties: {
        cid: { type: ['number', 'string'], description: 'PubChem Compound ID (CID)' },
        descriptor_type: { type: 'string', enum: ['all', 'basic', 'topological', '3d'], description: 'Type of descriptors (default: all)' },
      },
      required: ['cid'],
    },
  • src/index.ts:515-526 (registration)
    Tool registration in the ListTools response, defining name, description, and schema.
    {
      name: 'calculate_descriptors',
      description: 'Calculate comprehensive molecular descriptors and fingerprints',
      inputSchema: {
        type: 'object',
        properties: {
          cid: { type: ['number', 'string'], description: 'PubChem Compound ID (CID)' },
          descriptor_type: { type: 'string', enum: ['all', 'basic', 'topological', '3d'], description: 'Type of descriptors (default: all)' },
        },
        required: ['cid'],
      },
    },
  • src/index.ts:768-769 (registration)
    Dispatch/registration in the main CallToolRequestSchema switch statement, routing to the specific handler.
    case 'calculate_descriptors':
      return await this.handleCalculateDescriptors(args);
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 'comprehensive' but doesn't detail what that entails, such as computational intensity, rate limits, output format, or whether it's a read-only operation. This leaves significant gaps for an AI agent to understand how the tool behaves beyond basic calculation.

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 no wasted words, front-loading the key action and resource. It's appropriately sized for the tool's complexity, making it easy to parse quickly without 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 lack of annotations and output schema, the description is incomplete. It doesn't address behavioral traits, return values, or how it differs from sibling tools, which is crucial for a tool in a crowded molecular analysis context. This leaves the AI agent with insufficient information for effective use.

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 schema already documents both parameters well. The description adds no additional meaning beyond implying 'comprehensive' might relate to 'descriptor_type', but it doesn't clarify syntax or usage details. This meets the baseline for adequate but unenhanced parameter documentation.

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 verb 'calculate' and the resource 'molecular descriptors and fingerprints', making the purpose evident. However, it doesn't differentiate from siblings like 'get_compound_properties' or 'predict_admet_properties', which might also involve molecular analysis, leaving room for ambiguity in tool selection.

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?

No guidance is provided on when to use this tool versus alternatives. With many sibling tools for molecular analysis, the description lacks context on prerequisites, scenarios, or exclusions, making it unclear how it fits into workflows compared to tools like 'analyze_molecular_complexity' or 'get_compound_properties'.

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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