How to integrate Affinity MCP with OpenAI Agents SDK

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Introduction

This guide walks you through connecting Affinity to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Affinity agent that can list all companies added this week, show all opportunities in active pipeline, get recent contacts linked to acme corp, summarize all lists where john doe appears through natural language commands.

This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Affinity account through Composio's Affinity 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
  • Install the necessary dependencies
  • Initialize Composio and create a Tool Router session for Affinity
  • Configure an AI agent that can use Affinity as a tool
  • Run a live chat session where you can ask the agent to perform Affinity operations

What is open-ai-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 Affinity MCP server, and what's possible with it?

The Affinity MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Affinity account. It provides structured and secure access to your deal, company, and contact data, so your agent can analyze lists, fetch opportunity details, extract company insights, and organize people or organizations on your behalf.

  • Company data extraction and analysis: Let your agent retrieve detailed company profiles, summarize list entries, and pull custom field data for deeper insights and reporting.
  • Opportunity pipeline management: Automatically fetch and review all ongoing opportunities, track changes, and surface high-priority deals for follow-up.
  • List and view organization: Ask your agent to access entries across lists or saved views, aggregating metadata and field values for efficient CRM workflows.
  • Contact and relationship intelligence: Effortlessly browse, analyze, and summarize person records, including their list memberships, activity, and custom fields.
  • Automated CRM reporting: Generate summaries, export data, and monitor changes across companies, people, and opportunities to keep your pipeline up-to-date and actionable.

Supported Tools & Triggers

Tools
Get a company s list entriesSummarize company data across all lists, including list-specific fields and metadata like creation date and author.
Get a company s listsReturns metadata for all the lists on which the given company appears.
Get all companiesAffinity api allows paginated access to company info and custom fields.
Get all list entries on a listAccess and export essential data and metadata for companies, persons, or opportunities from a list, specifying data via `fieldids` or `fieldtypes`.
Get all list entries on a saved viewUse the endpoint to access rows in a saved view with specific filters and selected fields from a web app.
Get all opportunitiesPagination through opportunities in affinity yields basic info but excludes field data.
Get all personsThe affinity api offers paginated access to person data using `fieldids` or `fieldtypes`.
Get a person s list entriesSummary: browse rows for a person in all lists, showing field data and entry metadata like creation time and author.
Get a person s listsReturns metadata for all the lists on which the given person appears.
Get a single companyRetrieve basic company info and specific field data by using `fieldids` or `fieldtypes` parameters.
Get a single opportunityGet basic details about an opportunity without field data via provided endpoints.
Get a single personUse get `/v2/persons/fields` with `fieldids` or `fieldtypes` for detailed data; basic info by default.
Get current userReturns metadata about the current user.
Get metadata on all listsReturns metadata on lists.
Get metadata on a single listReturns metadata on a single list.
Get metadata on a single list s fieldsReturns metadata on the fields available on a single list.
Get metadata on a single saved viewReturns metadata on a single saved view.
Get metadata on company fieldsReturns metadata on non-list-specific company fields.
Get metadata on person fieldsReturns metadata on non-list-specific person fields.
Get metadata on saved viewsReturns metadata on the saved views on a list.

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:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live Affinity 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 Affinity.

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 Affinity Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["affinity"]
)

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 affinity.
  • The router checks the user's Affinity connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Affinity.
  • This approach keeps things lightweight and lets the agent request Affinity 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 Affinity. "
        "Help users perform Affinity 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 Affinity 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 Affinity 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 Affinity.
  • 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 Affinity and open-ai-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=["affinity"]
)
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 Affinity. "
        "Help users perform Affinity 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 Affinity MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Affinity.

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 Affinity MCP Agent with another framework

Claude Agent SDK

Claude Agent SDK

Use Affinity MCP with Claude Agent SDK

Google ADK

Google ADK

Use Affinity MCP with Google ADK

LangChain

LangChain

Use Affinity MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Affinity MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Affinity MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Affinity MCP with LlamaIndex

CrewAI

CrewAI

Use Affinity MCP with CrewAI

FAQ

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

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

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

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

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