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Kartha-AI

MCP Server for Google Cloud Healthcare API

by Kartha-AI

get-drug-info

Retrieve detailed drug information using its generic name with a tool designed for FHIR-based digital health solutions, enabling efficient clinical workflows and pre-authorization processes.

Instructions

Get Drug details by a generic name

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
genericNameYes

Implementation Reference

  • The primary handler for the 'get-drug-info' tool. It extracts the genericName from arguments, caches the result using CacheManager, fetches drug information by calling searchGenericName, and returns the JSON-formatted drug data.
    async getDrug(args: any, cache: CacheManager) {
      const { genericName} = args
      const cacheKey = cache.createKey('interactions', { genericName: genericName});
      
      const drug = await cache.getOrFetch(
        cacheKey,
        () => this.searchGenericName(genericName)
      );
    
      return {
        content: [{
          type: 'text',
          text: JSON.stringify(drug, null, 2)
        }]
      };
    }
  • The input schema and metadata definition for the 'get-drug-info' tool, specifying genericName as required string input.
    {
      name: 'get-drug-info',
      description: 'Get Drug details by a generic name',
      inputSchema: {
        type: 'object',
        properties: {
          genericName: { type: 'string' },
        },
        required: ['genericName']
      }
    },
  • Registration and dispatch for 'get-drug-info' tool in the handleCall switch statement, delegating to FDA.getDrug method.
    case "get-drug-info":
      return await this.fdaApi.getDrug(request.params.arguments,this.cache);
  • Supporting helper function that performs the actual FDA API query for drugs matching the generic name and returns the results.
    async searchGenericName(genericName: string): Promise<Generics[]> {
      const url = new URL(this.baseUrl);
      url.searchParams.append('search', `generic_name:"${genericName}"`)
      
      const response = await fetch(url);
      const data = await response.json() as FDAResponse;
    
      return data.results;
    }
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 states the action ('Get Drug details') but doesn't describe what 'details' include, whether it's a read-only operation, error handling, or any limitations (e.g., rate limits, data freshness). This is a significant gap for a 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 with zero waste. It's front-loaded with the core purpose, making it easy to scan. Every word contributes directly to understanding the tool's function.

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 (a lookup tool with no annotations, 0% schema coverage, and no output schema), the description is incomplete. It doesn't explain return values, error cases, or behavioral traits, leaving the agent with insufficient context to use the tool effectively beyond basic invocation.

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

Parameters2/5

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

The schema has 0% description coverage, so the description must compensate. It mentions 'genericName' as the lookup method but doesn't explain what constitutes a valid generic name (e.g., format, examples, case sensitivity) or what happens if the name isn't found. This adds minimal value beyond the schema's structure.

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 ('Get') and resource ('Drug details'), specifying the lookup method ('by a generic name'). It distinguishes from siblings like search-pubmed or search-trials by focusing on drug details retrieval rather than broader searches. However, it doesn't explicitly differentiate from get_medications_history or get_patient_medications, which might also involve drug information.

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 prerequisites (e.g., needing a valid generic name), exclusions, or comparisons to sibling tools like search-pubmed for broader drug research. Usage is implied only by the name and description, lacking explicit context.

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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