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1. Installation

First install the traceAI package to access the observability framework 
pip install traceAI-mcp
You also need to install the orchestration package that will utilize the MCP server.For example, if you are using the OpenAI MCP server, you need to install the traceAI-openai-agents package.
pip install traceAI-openai-agents

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2. Set Environment Variables

Set up your environment variables to authenticate with both FutureAGI and OpenAI. 
import os

os.environ["OPENAI_API_KEY"] = "your-openai-api-key"
os.environ["FI_API_KEY"] = "your-futureagi-api-key"
os.environ["FI_SECRET_KEY"] = "your-futureagi-secret-key"

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3. Initialize Trace Provider

Set up the trace provider to create a new project in FutureAGI, establish telemetry data pipelines . 
from fi_instrumentation import register
from fi_instrumentation.fi_types import ProjectType

trace_provider = register(
    project_type=ProjectType.EXPERIMENT,
    project_name="openai_project",
)

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4. Instrument your Project

Instrument your Project with OpenAI Agents Instrumentor. This step ensures that all interactions with the OpenAI are tracked and monitored. 
from traceai_openai_agents import OpenAIAgentsInstrumentor
from traceai_mcp import MCPInstrumentor


OpenAIAgentsInstrumentor().instrument(tracer_provider=trace_provider)
MCPInstrumentor().instrument(tracer_provider=trace_provider)

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5. Interact with MCP Server

Interact with the MCP Server as you normally would. Our Instrumentor will automatically trace and send the telemetry data to our platform. 

import asyncio
import os
import shutil

from agents import Agent, Runner
from agents.mcp import MCPServer, MCPServerStdio

from traceai_openai_agents import OpenAIAgentsInstrumentor
from traceai_mcp import MCPInstrumentor

from fi_instrumentation import register
from fi_instrumentation.fi_types import ProjectType

trace_provider = register(
    project_type=ProjectType.EXPERIMENT,
    project_name="mcp_project",
)



OpenAIAgentsInstrumentor().instrument(tracer_provider=trace_provider)
MCPInstrumentor().instrument(tracer_provider=trace_provider)

async def run(mcp_server: MCPServer):
    agent = Agent(
        name="Assistant",
        instructions="Use the tools to read the filesystem and answer questions based on those files.",
        mcp_servers=[mcp_server],
    )

    message = "Read the files and list them."
    print(f"Running: {message}")
    result = await Runner.run(starting_agent=agent, input=message)
    print(result.final_output)


async def main():
    current_dir = os.path.dirname(os.path.abspath(__file__))
    samples_dir = os.path.join(current_dir, "sample_files")

    async with MCPServerStdio(
        name="Filesystem Server, via npx",
        params={
            "command": "npx",
            "args": ["-y", "@modelcontextprotocol/server-filesystem", samples_dir],
        },
    ) as server:
        await run(server)


if __name__ == "__main__":
    if not shutil.which("npx"):
        raise RuntimeError("npx is not installed. Please install it with `npm install -g npx`.")

    asyncio.run(main())
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