How to integrate Felt MCP with OpenAI Agents SDK

Trusted by
AWS
Glean
Zoom
Airtable
GET STARTED FOR FREEGET A DEMO

30 min · no commitment · see it on your stack

Felt logo
OpenAI Agents SDK logo
divider

Introduction

This guide walks you through connecting Felt to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Felt agent that can add geojson features to an existing map, duplicate a project map for a new client, delete a layer from your city zoning map through natural language commands.

This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Felt account through Composio's Felt MCP server.

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

Also integrate Felt with

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the necessary dependencies
  • Initialize Composio and create a Tool Router session for Felt
  • Configure an AI agent that can use Felt as a tool
  • Run a live chat session where you can ask the agent to perform Felt operations

What is OpenAI Agents SDK?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.

Key features include:

  • Hosted MCP Tools: Connect to external services through hosted MCP endpoints
  • SQLite Sessions: Persist conversation history across interactions
  • Simple API: Clean interface with Agent, Runner, and tool configuration
  • Streaming Support: Real-time response streaming for interactive applications

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

The Felt MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Felt account. It provides structured and secure access to your maps, projects, and geospatial data, so your agent can perform actions like creating projects, modifying maps, updating map elements, and retrieving user or map details on your behalf.

  • Project and map creation: Instantly have your agent create new Felt projects and initialize interactive maps to kickstart geospatial workflows.
  • Element and layer management: Direct your agent to add, update, or delete map elements and layers—making it easy to modify map content or clean up unwanted data.
  • Map duplication and deletion: Clone existing maps for experimentation or backup, or remove entire maps and projects when they’re no longer needed.
  • Detailed map and user insights: Retrieve comprehensive details about any specific map or your authenticated user profile for streamlined map management and reporting.

Supported Tools & Triggers

Tools
Create or Update ElementsCreate or update map elements using GeoJSON FeatureCollection format.
Create ProjectCreate a new Felt project with the specified name and visibility settings.
Delete ElementTool to delete a specific element from a map.
Delete LayerTool to delete a specific layer from a map.
Delete MapPermanently deletes a map and all its associated data from Felt.
Delete ProjectTool to delete a project and all its contents.
Duplicate MapCreates a complete copy of a Felt map including all layers, elements, and configuration.
Get Map DetailsRetrieves comprehensive details of a specific Felt map including title, URL, layers, elements, basemap settings, access permissions, and timestamps.
Get User DetailsTool to retrieve information about the authenticated user.
List Element GroupsRetrieves all element groups from a Felt map.
List ElementsLists all elements on a specific map as a GeoJSON FeatureCollection.
List LayersTool to list all layers on a specific map.
List ProjectsTool to retrieve a list of projects accessible to the user.
List SourcesList all data sources (external data connections) accessible to the authenticated user.
Update ProjectTool to update an existing project's name or visibility.

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

What is Composio SDK?

Composio's Composio SDK 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 Composio SDK

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

How the Composio SDK works

The Composio SDK 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:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live Felt project
  • Some knowledge of Python or Typescript

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

Install dependencies

pip install composio_openai_agents openai-agents python-dotenv

Install the Composio SDK and the OpenAI Agents SDK.

Set up environment variables

bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com

Create a .env file and add your OpenAI and Composio API keys.

Import dependencies

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
What's happening:
  • You're importing all necessary libraries.
  • The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Felt.

Set up the Composio instance

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
What's happening:
  • load_dotenv() loads your .env file so OPENAI_API_KEY and COMPOSIO_API_KEY are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.

Create a Tool Router session

# Create a Felt Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["felt"]
)

mcp_url = session.mcp.url

What is happening:

  • You give the Tool Router the user id and the toolkits you want available. Here, it is only felt.
  • The router checks the user's Felt connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Felt.
  • This approach keeps things lightweight and lets the agent request Felt tools only when needed during the conversation.

Configure the agent

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Felt. "
        "Help users perform Felt operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
What's happening:
  • We're creating an Agent instance with a name, model (gpt-5), and clear instructions about its purpose.
  • The agent's instructions tell it that it can access Felt and help with queries, inserts, updates, authentication, and fetching database information.
  • The tools array includes a HostedMCPTool that connects to the MCP server URL we created earlier.
  • The headers dict includes the Composio API key for secure authentication with the MCP server.
  • require_approval: 'never' means the agent can execute Felt operations without asking for permission each time, making interactions smoother.

Start chat loop and handle conversation

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
What's happening:
  • The program prints a session URL that you visit to authorize Felt.
  • After authorization, the chat begins.
  • Each message you type is processed by the agent using Runner.run().
  • The responses are printed to the console, and conversations are saved locally using SQLite.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with Felt and OpenAI Agents SDK:

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["felt"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Felt. "
        "Help users perform Felt operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())

Conclusion

This was a starter code for integrating Felt MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Felt.

Key features:

  • Hosted MCP tool integration through Composio's Tool Router
  • SQLite session persistence for conversation history
  • Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

How to build Felt MCP Agent with another framework

Claude Agent SDK logo

Claude Agent SDK

Use Felt MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Felt MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Felt MCP with Claude Cowork

Codex logo

Codex

Use Felt MCP with Codex

OpenClaw logo

OpenClaw

Use Felt MCP with OpenClaw

Hermes logo

Hermes

Use Felt MCP with Hermes

CLI logo

CLI

Use Felt MCP with CLI

Google ADK logo

Google ADK

Use Felt MCP with Google ADK

LangChain logo

LangChain

Use Felt MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Felt MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Felt MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Felt MCP with LlamaIndex

CrewAI logo

CrewAI

Use Felt MCP with CrewAI

FAQ

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

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

Can I use Tool Router MCP with OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK 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 Felt tools.

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

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

Used by agents from

Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai

Never worry about agent reliability

We handle tool reliability, observability, and security so you never have to second-guess an agent action.

Get started for freeGet a demo↗