How to integrate Faraday MCP with CrewAI

GET STARTED FOR FREE
Framework Integration Gradient
Faraday Logo
CrewAI Logo
divider

Introduction

This guide walks you through connecting Faraday to CrewAI using the Composio tool router. By the end, you'll have a working Faraday agent that can enrich salesforce leads with predictive insights, automate email categorization using faraday ai, trigger customer follow-up based on faraday scores through natural language commands.

This guide will help you understand how to give your CrewAI agent real control over a Faraday account through Composio's Faraday 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 Faraday connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Faraday
  • Build a conversational loop where your agent can execute Faraday 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 Faraday MCP server, and what's possible with it?

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

Supported Tools & Triggers

Tools
Archive CohortTool to archive a cohort in Faraday.
Archive ConnectionTool to archive a connection in Faraday.
Archive DatasetTool to archive a dataset in Faraday.
Archive OutcomeTool to archive an outcome in Faraday.
Archive Persona SetTool to archive a persona set in Faraday.
Archive PlaceTool to archive a place in Faraday.
Archive ScopeTool to archive a scope in Faraday.
Archive StreamTool to archive a stream in Faraday.
Archive TargetTool to archive a target in Faraday.
Archive TraitTool to archive a trait in Faraday.
Create AccountTool to create a new Faraday account with specified name and branding.
Create CohortsTool to create a new cohort in Faraday.
Create DatasetTool to create a new dataset in Faraday.
Create OutcomeTool to create a new outcome.
Create Persona SetTool to create a new persona set.
Create PlaceTool to create a new place in Faraday.
Create ScopeTool to create a new scope in Faraday.
Create StreamTool to create a new stream or find an existing stream by name.
Create Target PreviewTool to start a preview delivery for a target.
Create TargetTool to create a target in Faraday.
Create TraitTool to create a new trait in Faraday.
Create Webhook EndpointTool to create a new webhook endpoint.
Delete AccountTool to delete an account by its UUID.
Delete All Orphaned TraitsTool to delete all orphaned traits from Faraday.
Delete CohortTool to permanently delete a cohort from Faraday.
Delete ConnectionTool to delete a Faraday connection by its UUID.
Delete DatasetTool to delete a dataset from Faraday.
Delete OutcomeTool to delete an outcome by its UUID.
Delete Persona SetTool to delete a persona set.
Delete PlaceTool to delete a place by its UUID.
Delete ScopeTool to delete a scope by its UUID.
Delete StreamTool to delete a stream by its UUID or name.
Delete TargetTool to delete a target by its UUID.
Delete UploadPermanently deletes a file from a Faraday dataset directory.
Delete Webhook EndpointTool to delete a webhook endpoint by its UUID.
Force Update CohortTool to trigger a rerun for a cohort.
Force Update ConnectionTool to trigger a rerun for a Faraday connection.
Force Update DatasetTool to trigger a rerun for a dataset.
Force Update OutcomeTool to trigger a rerun for an outcome resource.
Force Update Persona SetTool to trigger a rerun for a persona set resource.
Force Update PlaceTool to trigger a rerun for a place.
Force Update ScopeTool to trigger a rerun for a scope resource.
Force Update StreamTool to trigger a rerun for a stream.
Force Update TargetTool to trigger a rerun for a target.
Force Update TraitTool to trigger a rerun for a trait.
Get AccountTool to retrieve detailed information about a Faraday account by its UUID.
List AccountsTool to list all Faraday accounts accessible by the current user.
Get Accounts BillingTool to get billing information about your account.
Get CohortTool to retrieve a specific cohort by ID.
Get Cohort Membership AnalysisTool to get cohort membership counts over time for a specific cohort.
List CohortsTool to list all cohorts in your Faraday account.
Get Connection DatasetsTool to retrieve all datasets that use a specific connection.
Get Connection TargetsTool to retrieve all targets that use a specific connection.
Get Current AccountTool to retrieve the current account information.
Get Current Account BillingTool to retrieve billing information about the current account.
Get DatasetTool to retrieve a dataset by its UUID.
Get Dataset Ingress LogsTool to retrieve dataset ingress metrics over time.
List Feature StoresTool to list all feature stores.
Get Dependency GraphTool to retrieve the complete dependency graph for all resources on an account.
Get Market Opportunity AnalysesTool to retrieve all market opportunity analyses from Faraday.
Get OutcomeTool to retrieve an outcome by its ID.
List OutcomesTool to list all outcomes for the account.
Get Persona SetTool to retrieve a persona set by its UUID.
Get Persona Set Analysis FlowTool to retrieve the flow of persona sets over time, showing how individuals move between different personas.
List Persona SetsTool to list all persona sets.
Get Persona Set Analysis DimensionsTool to get various trait breakdown information about a persona set.
Get PlaceTool to retrieve a specific place by its UUID.
List PlacesTool to list all places in Faraday.
List RecommendersTool to list all recommenders.
Get ScopeTool to retrieve detailed information about a Faraday scope by its UUID.
Get Scope AnalysisTool to get analysis for a scope including outcomes and recommenders with probability distributions.
Get Scope DatasetsTool to retrieve all datasets associated with a Faraday scope.
Get Scope EfficacyTool to retrieve efficacy metrics for a scope.
Get Scope Payload CohortsTool to get payload cohorts for a specific scope.
Get Scope Payload OutcomesTool to retrieve payload outcomes for a specific scope.
Get Scope Payload Persona SetsTool to get payload persona sets for a specific scope.
Get Scope Payload RecommendersTool to retrieve payload recommenders for a specific scope.
Get Scope Population Exclusion CohortsTool to get population exclusion cohorts for a scope.
Get Scope Population CohortsTool to get population cohorts for a specific scope.
Get Scope TargetsTool to get all targets for a specific scope.
Get StreamTool to retrieve a stream by its UUID or name.
List StreamsTool to list all streams in your Faraday account.
Get Streams AnalysisTool to get the count of stream events emitted over a time period.
Get TargetTool to retrieve a specific target by its UUID from Faraday.
Get Target AnalysisTool to retrieve a target's analysis including geographic distributions and trait breakdowns.
Get TraitTool to retrieve a specific trait by ID.
Get Trait Analysis DimensionsTool to retrieve the percentage of the US population that falls into each category of a trait.
Get Traits CSVTool to retrieve all user-defined and Faraday-provided traits in CSV format.
Get UploadTool to download a previously uploaded file from a Faraday dataset directory.
List Uploaded FilesTool to retrieve the list of previously uploaded files in Faraday.
Get UsagesTool to retrieve usage statistics for your Faraday account.
Get Webhook EndpointTool to retrieve a webhook endpoint by its UUID.
List Webhook EndpointsTool to list all webhook endpoints configured for the account.
List AttributesTool to list all attributes in the feature store.
List ConnectionsTool to list all connections configured in Faraday.
List ScopesTool to list all scopes.
List TargetsTool to list all targets in your Faraday account.
Unarchive CohortTool to unarchive a previously archived cohort.
Unarchive DatasetTool to unarchive a dataset in Faraday.
Unarchive OutcomeTool to unarchive an outcome in Faraday.
Unarchive Persona SetTool to unarchive a previously archived persona set.
Unarchive PlaceTool to unarchive a previously archived place.
Unarchive ScopeTool to unarchive a previously archived scope.
Unarchive StreamTool to unarchive a stream in Faraday.
Unarchive TraitTool to unarchive a trait.
Update AccountTool to update an account's name or branding settings.
Update CohortTool to update a cohort's configuration using JSON Merge Patch semantics.
Update ConnectionTool to update a Faraday connection's name or options.
Update DatasetTool to update a dataset configuration using JSON Merge Patch semantics.
Update OutcomeTool to update an outcome's configuration using JSON Merge Patch semantics.
Update Persona SetTool to edit a persona set's configuration using JSON Merge Patch.
Update PlaceTool to update a place's name, addresses, or geojson geometry.
Update ScopeTool to update a Faraday scope's configuration using JSON Merge Patch semantics.
Update StreamTool to update a stream's properties using JSON Merge Patch semantics.
Update TargetTool to update a target's configuration in Faraday.
Update TraitTool to update a trait's properties using JSON Merge Patch semantics.
Update Webhook EndpointTool to update a webhook endpoint's configuration.

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 Faraday 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[mcp] python-dotenv
What's happening:
  • composio connects your agent to Faraday via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools[mcp] 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
import os
from composio import Composio
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
import dotenv

dotenv.load_dotenv()

COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")
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 Faraday MCP URL

Create a Composio Tool Router session for Faraday

python
composio_client = Composio(api_key=COMPOSIO_API_KEY)
session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["faraday"])

url = session.mcp.url
What's happening:
  • You create a Faraday only session through Composio
  • Composio returns an MCP HTTP URL that exposes Faraday tools

Initialize the MCP Server

python
server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users search the internet effectively",
        backstory="You are a helpful assistant with access to search tools.",
        tools=tools,
        verbose=False,
        max_iter=10,
    )
What's Happening:
  • Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication.
  • MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format.
  • Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools.
  • Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops.
  • Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries.

Create a CLI Chatloop and define the Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\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"Conversation history:\n{conversation_context}\n\n"
            f"Current request: {user_input}"
        ),
        expected_output="A helpful response addressing the user's request",
        agent=agent,
    )

    crew = Crew(agents=[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:
  • Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable.
  • Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean.
  • Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses.
  • Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context.
  • Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response.
  • Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity.

Complete Code

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

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter
from composio import Composio
from dotenv import load_dotenv
import os

load_dotenv()

GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_API_KEY is not set in the environment.")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment.")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment.")

# Initialize Composio and create a session
composio = Composio(api_key=COMPOSIO_API_KEY)
session = composio.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["faraday"],
)
url = session.mcp.url

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

server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users with internet searches",
        backstory="You are an expert assistant with access to Composio Search tools.",
        tools=tools,
        llm=llm,
        verbose=False,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end.\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"Conversation history:\n{conversation_context}\n\n"
                f"Current request: {user_input}"
            ),
            expected_output="A helpful response addressing the user's request",
            agent=agent,
        )

        crew = Crew(agents=[agent], tasks=[task], verbose=False)
        result = crew.kickoff()
        response = str(result)

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

Conclusion

You now have a CrewAI agent connected to Faraday through Composio's Tool Router. The agent can perform Faraday 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 Faraday MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Faraday MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Faraday MCP with Claude Agent SDK

Google ADK

Google ADK

Use Faraday MCP with Google ADK

LangChain

LangChain

Use Faraday MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Faraday MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Faraday MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Faraday MCP with LlamaIndex

Claude Code

Claude Code

Use Faraday MCP with Claude Code

Codex

Codex

Use Faraday MCP with Codex

FAQ

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

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

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

Yes, absolutely. You can configure which Faraday 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 Faraday 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.

Book a call↗Get started for free