Observability

export LANGFUSE_PUBLIC_KEY="pk-lf-..."
export LANGFUSE_SECRET_KEY="sk-lf-..."
# Optional:
export LANGFUSE_HOST="https://cloud.langfuse.com"

import { MCPAgent } from "@mcp-use/agent";
import { MCPClient } from "@mcp-use/client";
import { ChatOpenAI } from "@langchain/openai";

const client = new MCPClient({
  mcpServers: {
    filesystem: {
      command: "npx",
      args: [
        "-y",
        "@modelcontextprotocol/server-filesystem",
        "/path/to/allowed/files",
      ],
    },
  },
});

const agent = new MCPAgent({
  llm: new ChatOpenAI({ model: "gpt-4o" }),
  client,
  maxSteps: 30,
});

const result = await agent.run({
  prompt: "Analyze the sales data",
});

console.log(result);
await agent.flush();
await agent.close();

import { MCPAgent } from "@mcp-use/agent";
import { MCPClient } from "@mcp-use/client";

const agent = new MCPAgent({
  llm,
  client,
  maxSteps: 30,
});

agent.setMetadata({
  agent_id: "customer-support-agent-01",
  version: "v2.0.0",
  environment: "production",
  customer_id: "cust_12345",
});

agent.setTags(["customer-support", "high-priority", "beta-feature"]);

const result = await agent.run({
  prompt: "Process customer request",
});

import { CallbackHandler } from "langfuse-langchain";
import { MCPAgent } from "@mcp-use/agent";

const customHandler = new CallbackHandler({
  publicKey: "pk-lf-custom",
  secretKey: "sk-lf-custom",
  baseUrl: "https://custom-langfuse.com",
});

const agent = new MCPAgent({
  llm,
  client,
  callbacks: [customHandler],
});

const agent = new MCPAgent({
  llm,
  client,
  observe: false,
});