How to integrate Fly MCP with LangChain

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Introduction

This guide walks you through connecting Fly to LangChain using the Composio tool router. By the end, you'll have a working Fly agent that can deploy latest image to fly in tokyo, list all running fly apps by region, scale up my fly app to 3 instances through natural language commands.

This guide will help you understand how to give your LangChain agent real control over a Fly account through Composio's Fly MCP server.

Before we dive in, let's take a quick look at the key ideas and tools involved.

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Connect your Fly project to Composio
  • Create a Tool Router MCP session for Fly
  • Initialize an MCP client and retrieve Fly tools
  • Build a LangChain agent that can interact with Fly
  • Set up an interactive chat interface for testing

What is LangChain?

LangChain is a framework for developing applications powered by language models. It provides tools and abstractions for building agents that can reason, use tools, and maintain conversation context.

Key features include:

  • Agent Framework: Build agents that can use tools and make decisions
  • MCP Integration: Connect to external services through Model Context Protocol adapters
  • Memory Management: Maintain conversation history across interactions
  • Multi-Provider Support: Works with OpenAI, Anthropic, and other LLM providers

What is the Fly MCP server, and what's possible with it?

The Fly MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Fly account. It provides structured and secure access so your agent can perform Fly operations on your behalf.

Supported Tools & Triggers

Tools
Add WireGuard PeerTool to add a WireGuard peer connection to a Fly.
Check App Name AvailabilityTool to validate an app name for Fly.
Check JobsExecute GraphQL queries against the Fly.
Check User Only TokenCheck whether the authentication token only allows user access.
Create Health Check JobTool to create a health check job for monitoring application endpoints in Fly.
Create Check Job RunTriggers a run of an existing health check job on Fly.
Create Delegated WireGuard TokenTool to create a delegated WireGuard token for peer management in a Fly.
Create Third-Party ConfigurationTool to create a third-party service configuration for discharging macaroon caveats.
Delete Delegated WireGuard TokenTool to delete a delegated WireGuard token from a Fly.
Delete OrganizationTool to delete a Fly.
Delete Remote BuilderTool to delete a remote builder configuration for a Fly.
Delete Third Party ConfigurationTool to delete a third-party service configuration from Fly.
Detach Postgres ClusterTool to detach a Postgres cluster from a Fly.
Establish SSH KeyTool to establish an SSH key for a Fly.
Fetch Nodes by IDsFetches a list of node objects from Fly.
Get Add-OnTool to find a Fly.
Get Add-On ProviderTool to query information about a specific Fly.
Get app detailsTool to retrieve detailed information about a specific Fly.
Get CertificateTool to retrieve a certificate by its ID from Fly.
Get Current Token InfoTool to get information about the current authentication token.
Get Latest Image DetailsTool to retrieve the latest available tag details for a given image repository from Fly.
Get Latest Image TagTool to retrieve the latest available image tag for a Fly.
Get MachineTool to get a single machine by ID from Fly.
Get Nearest RegionTool to retrieve the nearest Fly.
Get Node by IDTool to fetch an object by its globally unique ID using Fly.
Get OrganizationTool to find a Fly.
Get Personal OrganizationTool to retrieve the user's personal organization details from Fly.
Get PlacementsTool to get placement recommendations for Machines in Fly.
Get Platform InformationTool to retrieve Fly.
Get Products and PricingTool to retrieve Fly.
Get RegionsTool to get the list of available Fly.
Get Viewer InfoTool to retrieve the authenticated user's account information from Fly.
Issue CertificateTool to issue an SSH certificate for accessing Fly.
List Add-On PlansTool to list available add-on service plans from Fly.
List Add-OnsTool to list add-ons associated with an organization in Fly.
List AppsTool to list all Fly Apps in an organization.
List Apps via GraphQLList all Fly.
Check LocationsRetrieve all available Fly.
List MachinesTool to list Fly.
List Organization MachinesTool to list all Machines across all apps in a Fly organization.
Remove WireGuard PeerTool to remove a WireGuard peer connection from a Fly.
Set Apps V2 DefaultTool to configure whether new apps in an organization use Apps V2 by default on Fly.
Update Third-Party ConfigurationTool to update an existing third-party service configuration for discharging macaroon caveats.
Validate ConfigTool to validate a Fly.
Validate WireGuard PeersTool to validate WireGuard peer IP addresses in a Fly.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router helps agents find the right tools for a task at runtime. You can plug in multiple toolkits (like Gmail, HubSpot, and GitHub), and the agent will identify the relevant app and action to complete multi-step workflows. This can reduce token usage and improve the reliability of tool calls. Read more here: Getting started with Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router follows a three-phase workflow:

  1. Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
  2. Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
  3. Execution: Executes the action using the authenticated connection.

Step-by-step Guide

Prerequisites

Before starting this tutorial, make sure you have:
  • Python 3.10 or higher installed on your system
  • A Composio account with an API key
  • An OpenAI API key
  • Basic familiarity with Python and async programming

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.

Install dependencies

pip install composio-langchain langchain-mcp-adapters langchain python-dotenv

Install the required packages for LangChain with MCP support.

What's happening:

  • composio-langchain provides Composio integration for LangChain
  • langchain-mcp-adapters enables MCP client connections
  • langchain is the core agent framework
  • python-dotenv loads environment variables

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
COMPOSIO_USER_ID=your_composio_user_id_here
OPENAI_API_KEY=your_openai_api_key_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your requests to Composio's API
  • COMPOSIO_USER_ID identifies the user for session management
  • OPENAI_API_KEY enables access to OpenAI's language models

Import dependencies

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()
What's happening:
  • We're importing LangChain's MCP adapter and Composio SDK
  • The dotenv import loads environment variables from your .env file
  • This setup prepares the foundation for connecting LangChain with Fly functionality through MCP

Initialize Composio client

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))

    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
What's happening:
  • We're loading the COMPOSIO_API_KEY from environment variables and validating it exists
  • Creating a Composio instance that will manage our connection to Fly tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

# Create Tool Router session for Fly
session = composio.create(
    user_id=os.getenv("COMPOSIO_USER_ID"),
    toolkits=['fly']
)

url = session.mcp.url
What's happening:
  • We're creating a Tool Router session that gives your agent access to Fly tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use
  • This approach allows the agent to dynamically load and use Fly tools as needed

Configure the agent with the MCP URL

client = MultiServerMCPClient({
    "fly-agent": {
        "transport": "streamable_http",
        "url": session.mcp.url,
        "headers": {
            "x-api-key": os.getenv("COMPOSIO_API_KEY")
        }
    }
})

tools = await client.get_tools()

agent = create_agent("gpt-5", tools)
What's happening:
  • We're creating a MultiServerMCPClient that connects to our Fly MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • get_tools() retrieves all available Fly tools that the agent can use
  • We're creating a LangChain agent using the GPT-5 model

Set up interactive chat interface

conversation_history = []

print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Fly related question or task to the agent.\n")

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ['exit', 'quit', 'bye']:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_history.append({"role": "user", "content": user_input})
    print("\nAgent is thinking...\n")

    response = await agent.ainvoke({"messages": conversation_history})
    conversation_history = response['messages']
    final_response = response['messages'][-1].content
    print(f"Agent: {final_response}\n")
What's happening:
  • We initialize an empty conversation_history list to maintain context across interactions
  • A while loop continuously accepts user input from the command line
  • When a user types a message, it's added to the conversation history and sent to the agent
  • The agent processes the request using the ainvoke() method with the full conversation history
  • Users can type 'exit', 'quit', or 'bye' to end the chat session gracefully

Run the application

if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • We call the main() function using asyncio.run() to start the application

Complete Code

Here's the complete code to get you started with Fly and LangChain:

from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain.agents import create_agent
from dotenv import load_dotenv
from composio import Composio
import asyncio
import os

load_dotenv()

async def main():
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    
    if not os.getenv("COMPOSIO_API_KEY"):
        raise ValueError("COMPOSIO_API_KEY is not set")
    if not os.getenv("COMPOSIO_USER_ID"):
        raise ValueError("COMPOSIO_USER_ID is not set")
    
    session = composio.create(
        user_id=os.getenv("COMPOSIO_USER_ID"),
        toolkits=['fly']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "fly-agent": {
            "transport": "streamable_http",
            "url": url,
            "headers": {
                "x-api-key": os.getenv("COMPOSIO_API_KEY")
            }
        }
    })
    
    tools = await client.get_tools()
  
    agent = create_agent("gpt-5", tools)
    
    conversation_history = []
    
    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Ask any Fly related question or task to the agent.\n")
    
    while True:
        user_input = input("You: ").strip()
        
        if user_input.lower() in ['exit', 'quit', 'bye']:
            print("\nGoodbye!")
            break
        
        if not user_input:
            continue
        
        conversation_history.append({"role": "user", "content": user_input})
        print("\nAgent is thinking...\n")
        
        response = await agent.ainvoke({"messages": conversation_history})
        conversation_history = response['messages']
        final_response = response['messages'][-1].content
        print(f"Agent: {final_response}\n")

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You've successfully built a LangChain agent that can interact with Fly through Composio's Tool Router.

Key features of this implementation:

  • Dynamic tool loading through Composio's Tool Router
  • Conversation history maintenance for context-aware responses
  • Async Python provides clean, efficient execution of agent workflows
You can extend this further by adding error handling, implementing specific business logic, or integrating additional Composio toolkits to create multi-app workflows.

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FAQ

What are the differences in Tool Router MCP and Fly MCP?

With a standalone Fly MCP server, the agents and LLMs can only access a fixed set of Fly tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Fly and many other apps based on the task at hand, all through a single MCP endpoint.

Can I use Tool Router MCP with LangChain?

Yes, you can. LangChain fully supports MCP integration. You get structured tool calling, message history handling, and model orchestration while Tool Router takes care of discovering and serving the right Fly tools.

Can I manage the permissions and scopes for Fly while using Tool Router?

Yes, absolutely. You can configure which Fly scopes and actions are allowed when connecting your account to Composio. You can also bring your own OAuth credentials or API configuration so you keep full control over what the agent can do.

How safe is my data with Composio Tool Router?

All sensitive data such as tokens, keys, and configuration is fully encrypted at rest and in transit. Composio is SOC 2 Type 2 compliant and follows strict security practices so your Fly data and credentials are handled as safely as possible.

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