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drug_interactions

Check drug-drug interaction signals from FDA adverse event co-reports. Returns co-reported reactions and signal strength.

Instructions

Check drug-drug interaction signals from FDA adverse event co-reports. Returns co-reported reactions and signal strength. Source: OpenFDA FAERS (public domain).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
drugsYesArray of 2-5 drug names to check for interactions

Implementation Reference

  • Input schema for drug_interactions tool: accepts an array of 2-5 drug names to check for interactions.
      schema: {
        drugs: z.array(z.string()).min(2).max(5).describe('Array of 2-5 drug names to check for interactions'),
      },
    },
  • src/tools.js:124-132 (registration)
    Registration of the drug_interactions tool as part of the MCP_TOOLS array. It has name, description, price, endpoint, and Zod schema.
    {
      name: 'drug_interactions',
      description: 'Check drug-drug interaction signals from FDA adverse event co-reports. Returns co-reported reactions and signal strength. Source: OpenFDA FAERS (public domain).',
      price: '$0.03',
      endpoint: '/agent/v1/drugs/interactions',
      schema: {
        drugs: z.array(z.string()).min(2).max(5).describe('Array of 2-5 drug names to check for interactions'),
      },
    },
  • Generic handler that forwards the drug_interactions request to the remote API endpoint /agent/v1/drugs/interactions via fetch, passing the params as JSON body. All tools use this same generic handler.
    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?

No annotations are present, so the description must fully disclose behavioral traits. While it mentions the data source (OpenFDA FAERS, public domain), it does not discuss rate limits, data staleness, scope (adverse event co-reports vs. clinical interactions), or whether the tool is read-only. This lack of transparency is a significant gap.

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 concise, consisting of two sentences that front-load the core action and provide essential context. No unnecessary words.

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?

Given the tool's simplicity (one parameter, no nested objects, no output schema), the description is adequate but incomplete. It lacks details on the output format, any error handling, or usage limitations. While it covers the basic purpose, agents may need additional information to use it 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 schema already provides a clear description for the 'drugs' parameter (array of 2-5 drug names). The description adds general context about the data source but does not enhance understanding of the parameter beyond what the schema offers. With 100% schema coverage, baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: checking drug-drug interaction signals from FDA adverse event co-reports. It specifies the output (co-reported reactions and signal strength) and distinguishes itself from sibling tools like drug_lookup or drug_enrich by focusing on interactions.

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, nor any limitations or prerequisites. The description only states what it does, leaving the agent without context for selecting it appropriately.

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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