How to integrate Fingertip MCP with CrewAI

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Introduction

This guide walks you through connecting Fingertip to CrewAI 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 CrewAI 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 a Composio API key and configure your Fingertip connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Fingertip
  • Build a conversational loop where your agent can execute Fingertip operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

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, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Fingertip connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python

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

bash
pip install composio crewai crewai-tools python-dotenv
What's happening:
  • composio connects your agent to Fingertip via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools includes MCP helpers
  • python-dotenv loads environment variables from .env

Set up environment variables

bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_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 with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model

Import dependencies

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional import if you plan to adapt tools
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived Fingertip MCP URL

Create a Composio Tool Router session for Fingertip

python
composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
session = composio.create(
    user_id=os.getenv("USER_ID"),
    toolkits=["fingertip"],
)
url = session.mcp.url
What's happening:
  • You create a Fingertip only session through Composio
  • Composio returns an MCP HTTP URL that exposes Fingertip tools

Configure the LLM

python
llm = LLM(
    model="gpt-5-mini",
    api_key=os.getenv("OPENAI_API_KEY"),
)
What's happening:
  • CrewAI will call this LLM for planning and responses
  • You can swap in a different model if needed

Attach the MCP server and create the agent

python
toolkit_agent = Agent(
    role="Fingertip Assistant",
    goal="Help users interact with Fingertip through natural language commands",
    backstory=(
        "You are an expert assistant with access to Fingertip tools. "
        "You can perform various Fingertip operations on behalf of the user."
    ),
    mcps=[
        MCPServerHTTP(
            url=url,
            streamable=True,
            cache_tools_list=True,
            headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
        ),
    ],
    llm=llm,
    verbose=True,
    max_iter=10,
)
What's happening:
  • MCPServerHTTP connects the agent to the Fingertip MCP endpoint
  • cache_tools_list saves a tools catalog for faster subsequent runs
  • verbose helps you see what the agent is doing

Add a REPL loop with Task and Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to perform Fingertip operations.\n")

conversation_context = ""

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

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

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Based on the conversation history:\n{conversation_context}\n\n"
            f"Current user request: {user_input}\n\n"
            f"Please help the user with their Fingertip related request."
        ),
        expected_output="A helpful response addressing the user's request",
        agent=toolkit_agent,
    )

    crew = Crew(
        agents=[toolkit_agent],
        tasks=[task],
        verbose=False,
    )

    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's happening:
  • You build a simple chat loop and keep a running context
  • Each user turn becomes a Task handled by the same agent
  • Crew executes the task and returns a response

Run the application

python
if __name__ == "__main__":
    main()
What's happening:
  • Standard Python entry point so you can run python crewai_fingertip_agent.py

Complete Code

Here's the complete code to get you started with Fingertip and CrewAI:

python
# file: crewai_fingertip_agent.py
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter  # optional
from composio import Composio
from dotenv import load_dotenv
import os
from crewai.mcp import MCPServerHTTP

load_dotenv()

def main():
    # Initialize Composio and create a Fingertip session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["fingertip"],
    )
    url = session.mcp.url

    # Configure LLM
    llm = LLM(
        model="gpt-5-mini",
        api_key=os.getenv("OPENAI_API_KEY"),
    )

    # Create Fingertip assistant agent
    toolkit_agent = Agent(
        role="Fingertip Assistant",
        goal="Help users interact with Fingertip through natural language commands",
        backstory=(
            "You are an expert assistant with access to Fingertip tools. "
            "You can perform various Fingertip operations on behalf of the user."
        ),
        mcps=[
            MCPServerHTTP(
                url=url,
                streamable=True,
                cache_tools_list=True,
                headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")},
            ),
        ],
        llm=llm,
        verbose=True,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
    print("Try asking the agent to perform Fingertip operations.\n")

    conversation_context = ""

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

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

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Based on the conversation history:\n{conversation_context}\n\n"
                f"Current user request: {user_input}\n\n"
                f"Please help the user with their Fingertip related request."
            ),
            expected_output="A helpful response addressing the user's request",
            agent=toolkit_agent,
        )

        crew = Crew(
            agents=[toolkit_agent],
            tasks=[task],
            verbose=False,
        )

        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

if __name__ == "__main__":
    main()

Conclusion

You now have a CrewAI agent connected to Fingertip through Composio's Tool Router. The agent can perform Fingertip operations through natural language commands. Next steps:
  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations

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

LangChain

LangChain

Use Fingertip MCP with LangChain

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

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 CrewAI?

Yes, you can. CrewAI 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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