aiprox-mcp

Instructions

Implementation Reference

• src/index.ts:269-324 (handler)

  The handler logic for the 'find_agent' tool, which matches the task to a capability and queries the registry.

  case "find_agent": {
    const { task, preferred_rail } = args as any;
  
    // Search by capability keywords
    const capabilityMap: Record<string, string> = {
      "ai inference": "ai-inference",
      "language model": "ai-inference",
      "claude": "ai-inference",
      "gpt": "ai-inference",
      "polymarket": "market-data",
      "prediction market": "market-data",
      "market analysis": "market-data",
      "image": "image-generation",
      "web search": "web-search",
    };
  
    let capability: string | undefined;
    const taskLower = task.toLowerCase();
    for (const [keyword, cap] of Object.entries(capabilityMap)) {
      if (taskLower.includes(keyword)) {
        capability = cap;
        break;
      }
    }
  
    const agents = await listAgents(capability, preferred_rail);
  
    if (!agents.length) {
      return {
        content: [
          {
            type: "text",
            text: `No agents found for: "${task}"\n\nBrowse the full registry: ${AIPROX_URL}/registry.html`,
          },
        ],
      };
    }
  
    const best = agents[0];
    return {
      content: [
        {
          type: "text",
          text: [
            `🤖 Best match for: "${task}"`,
            ``,
            formatAgent(best),
            ``,
            `To invoke this agent, call its endpoint directly:`,
            `${best.endpoint}`,
          ].join("\n"),
        },
      ],
    };
  }

• src/index.ts:60-76 (registration)

  The registration of the 'find_agent' tool, including its schema definition.

  {
    name: "find_agent",
    description:
      "Find the best agent for a specific task. Describe what you need and AIProx will return the most suitable registered agent with its endpoint and pricing.",
    inputSchema: {
      type: "object",
      properties: {
        task: {
          type: "string",
          description:
            "What you need (e.g. 'AI inference paid with Bitcoin', 'Polymarket analysis', 'image generation')",
        },
        preferred_rail: {
          type: "string",
          description:
            "Preferred payment rail (bitcoin-lightning or solana-usdc). Optional.",
        },