Mastra

npm install @mastra/core @mastra/mcp dotenv

import "dotenv/config";
import { MCPClient } from "@mastra/mcp";

export const twexapiMcp = new MCPClient({
  servers: {
    twexapi: {
      url: new URL("https://api.twexapi.io/mcp"),
      requestInit: {
        headers: {
          "x-api-key": process.env.TWEXAPI_API_KEY!,
        },
      },
    },
  },
});

import { Agent } from "@mastra/core/agent";
import { openai } from "@ai-sdk/openai";
import { twexapiMcp } from "./mcp";

const tools = await twexapiMcp.listTools();

export const twexapiAgent = new Agent({
  name: "twexapi-agent",
  instructions: `
    You help users interact with X/Twitter through Twexapi MCP.
    Always call explore before twexapi_request.
    Preserve tweet_id, user_id, route_used, has_more, and next_cursor.
    Ask for approval before read_only: false actions.
  `,
  model: openai("gpt-4o-mini"),
  tools,
});

const result = await twexapiAgent.generate(
  "Search recent X posts about AI infrastructure. Return compact JSON with route_used, tweets, has_more, and next_cursor."
);

console.log(result.text);

Use Twexapi MCP to search recent X posts about "AI infrastructure".
Call explore first, then twexapi_request.
Return JSON with route_used, tweets[{tweet_id,text,author_username,created_at}], has_more, next_cursor, and top accounts.

export const mcp = new MCPClient({
  servers: {
    twexapi: {
      url: new URL("https://api.twexapi.io/mcp"),
      requestInit: {
        headers: { "x-api-key": process.env.TWEXAPI_API_KEY! },
      },
    },
    twexapiDocs: {
      url: new URL("https://docs.twexapi.io/mcp"),
    },
  },
});