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drug_lookup

Retrieve drug label data, adverse events, and diagnosis codes using brand or generic names from OpenFDA.

Instructions

Look up drug information including label data, adverse events, and related diagnosis codes. Source: OpenFDA (public domain).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
drugNameYesDrug name (brand, generic, or substance — min 2 chars)
searchFieldNoSearch field (default: brand_name)

Implementation Reference

  • Zod schema and configuration for the 'drug_lookup' tool. Defines input parameters (drugName string, optional searchField enum), the OpenFDA endpoint '/agent/v1/drugs/lookup', description, and per-call price of $0.01.
    // --- Drug Intelligence (OpenFDA — free, no license) ---
    {
      name: 'drug_lookup',
      description: 'Look up drug information including label data, adverse events, and related diagnosis codes. Source: OpenFDA (public domain).',
      price: '$0.01',
      endpoint: '/agent/v1/drugs/lookup',
      schema: {
        drugName: z.string().describe('Drug name (brand, generic, or substance — min 2 chars)'),
        searchField: z.enum(['brand_name', 'generic_name', 'product_ndc', 'substance_name']).optional().describe('Search field (default: brand_name)'),
      },
    },
  • src/index.js:19-61 (registration)
    The generic tool registration loop in createMcpServer(). For each MCP_TOOLS entry (including drug_lookup), it registers an MCP tool via s.tool(...) with a dynamic handler that POSTs request params to the tool's endpoint URL. This is where 'drug_lookup' gets registered with the MCP server.
    for (const tool of MCP_TOOLS) {
      s.tool(tool.name, tool.description, tool.schema, async (params) => {
        const toolDef = getToolByName(tool.name);
        if (!toolDef) {
          return { content: [{ type: 'text', text: `Unknown tool: ${tool.name}` }], isError: true };
        }
        try {
          const response = await fetch(`${API_BASE_URL}${toolDef.endpoint}`, {
            method: 'POST',
            headers: {
              'Content-Type': 'application/json',
              ...(API_KEY && { 'X-API-Key': API_KEY }),
              'X-Agent-ID': 'mcp-client',
              'User-Agent': '@mymedi-ai/mcp-server/1.2.1',
            },
            body: JSON.stringify(params),
          });
          if (response.status === 402) {
            const paymentInfo = await response.json();
            return {
              content: [{ type: 'text', text: JSON.stringify({
                error: 'payment_required',
                message: `This tool costs ${toolDef.price} per call. Register at ${API_BASE_URL}/bot-marketplace/register for an API key with 10 free starter credits, or pay per call with on-chain USDC (no signup) via the x402 protocol.`,
                price: toolDef.price, register: `${API_BASE_URL}/bot-marketplace/register`, ...paymentInfo,
              }, null, 2) }], isError: true,
            };
          }
          if (!response.ok) {
            const error = await response.json().catch(() => ({ message: response.statusText }));
            return { content: [{ type: 'text', text: JSON.stringify({ error: true, status: response.status, ...error }, null, 2) }], isError: true };
          }
          const data = await response.json();
          const creditsSpent = response.headers.get('X-Credits-Spent');
          const creditsRemaining = response.headers.get('X-Credits-Remaining');
          if (creditsSpent) {
            data._billing = { creditsSpent: parseInt(creditsSpent, 10), creditsRemaining: creditsRemaining ? parseInt(creditsRemaining, 10) : undefined, priceUSD: toolDef.price };
          }
          return { content: [{ type: 'text', text: JSON.stringify(data, null, 2) }] };
        } catch (err) {
          return { content: [{ type: 'text', text: JSON.stringify({ error: true, message: err.message, hint: 'Ensure MCP_API_BASE_URL and MCP_API_KEY environment variables are set.' }, null, 2) }], isError: true };
        }
      });
    }
Behavior2/5

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

With no annotations, the description must fully disclose behavioral traits. It mentions the source and data categories but omits rate limits, data freshness, read-only nature, or error behavior. Minimal 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?

Two sentences, front-loaded with purpose, then source. No unnecessary words. Efficiently conveys core functionality.

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

Completeness3/5

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

Adequate for a lookup tool with two well-documented parameters and no output schema, but lacks context on limitations, authentication, or what happens on missing data.

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 coverage is 100%, so the baseline is 3. The description adds no additional parameter meaning beyond what the input schema already provides (e.g., min chars, default search field).

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 provides drug information including label data, adverse events, and diagnosis codes. It distinguishes the general lookup function from more specific sibling tools like drug_interactions, but does not explicitly differentiate.

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 on when to use this tool versus alternatives like drug_enrich or drug_rxnorm. No exclusions or prerequisites are mentioned, only the data source (OpenFDA).

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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