How to integrate Fingertip MCP with LangChain

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Introduction

This guide walks you through connecting Fingertip to LangChain using the Composio tool router. By the end, you'll have a working Fingertip agent that can show analytics for my main fingertip site, list all upcoming event types for my business, get summaries of recent blog posts, delete a workspace invitation i just sent through natural language commands.

This guide will help you understand how to give your LangChain agent real control over a Fingertip account through Composio's Fingertip 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 Fingertip project to Composio
  • Create a Tool Router MCP session for Fingertip
  • Initialize an MCP client and retrieve Fingertip tools
  • Build a LangChain agent that can interact with Fingertip
  • 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 Fingertip MCP server, and what's possible with it?

The Fingertip MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Fingertip account. It provides structured and secure access to your business management dashboard, so your agent can perform actions like creating and deleting sites, retrieving site analytics, managing memberships, and listing blog posts or event types on your behalf.

  • Instant site creation and removal: Let your agent create new Fingertip sites or delete existing ones as your business evolves.
  • Comprehensive site analytics retrieval: Ask your agent to fetch detailed analytics and performance metrics for specific sites, including store activity over selected time periods.
  • Membership and invitation management: Have your agent add, remove, or look up site memberships and cancel outstanding workspace invitations easily.
  • Blog and content organization: Direct your agent to list published blog posts, retrieve post summaries, and sort or paginate results for content management.
  • Event and form template listing: Enable your agent to fetch available event types and form templates to streamline client bookings or data collection.

Supported Tools & Triggers

Tools
Create Fingertip SiteTool to create a new Fingertip site.
Delete Fingertip SiteTool to delete a Fingertip site.
Delete Site MembershipTool to delete a specific site membership.
Delete Workspace InvitationTool to delete a workspace invitation by its ID.
Get Comprehensive Site AnalyticsTool to retrieve comprehensive analytics for a specific site.
Get Site MembershipTool to retrieve site membership details.
Health CheckTool to verify API connectivity.
List Fingertip Blog PostsTool to list published blog posts for a specific site.
List Event TypesTool to list event types for a specific site.
List Form TemplatesTool to retrieve a paginated list of form templates.
List PagesTool to list pages.
List Page ThemesTool to retrieve a paginated list of page themes.
List Site MembershipsTool to retrieve a paginated list of site memberships.
List SitesTool to retrieve a paginated list of sites accessible by the API key.
List WorkspacesTool to retrieve a paginated list of workspaces accessible to the API key.

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 Fingertip 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 Fingertip tools
  • Validating that COMPOSIO_USER_ID is also set before proceeding

Create a Tool Router session

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

url = session.mcp.url
What's happening:
  • We're creating a Tool Router session that gives your agent access to Fingertip 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 Fingertip tools as needed

Configure the agent with the MCP URL

client = MultiServerMCPClient({
    "fingertip-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 Fingertip MCP server via HTTP
  • The client is configured with a name and the URL from our Tool Router session
  • get_tools() retrieves all available Fingertip 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 Fingertip 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 Fingertip 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=['fingertip']
    )

    url = session.mcp.url
    
    client = MultiServerMCPClient({
        "fingertip-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 Fingertip 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 Fingertip 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.

How to build Fingertip MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Fingertip MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Fingertip MCP with Claude Agent SDK

Google ADK

Google ADK

Use Fingertip MCP with Google ADK

Vercel AI SDK

Vercel AI SDK

Use Fingertip MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Fingertip MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Fingertip MCP with LlamaIndex

CrewAI

CrewAI

Use Fingertip MCP with CrewAI

FAQ

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

With a standalone Fingertip MCP server, the agents and LLMs can only access a fixed set of Fingertip tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Fingertip 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 Fingertip tools.

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

Yes, absolutely. You can configure which Fingertip 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 Fingertip data and credentials are handled as safely as possible.

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