How to integrate Endorsal MCP with CrewAI

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Introduction

This guide walks you through connecting Endorsal to CrewAI using the Composio tool router. By the end, you'll have a working Endorsal agent that can add new customer testimonial from recent feedback, list all active autorequest campaigns, show all testimonials submitted by this contact through natural language commands.

This guide will help you understand how to give your CrewAI agent real control over a Endorsal account through Composio's Endorsal MCP server.

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

Also integrate Endorsal with

TL;DR

Here's what you'll learn:
  • Get a Composio API key and configure your Endorsal connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Endorsal
  • Build a conversational loop where your agent can execute Endorsal 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 Endorsal MCP server, and what's possible with it?

The Endorsal MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Endorsal account. It provides structured and secure access to your testimonials, contacts, and campaign data, so your agent can perform actions like collecting new testimonials, managing contacts, organizing campaigns, and displaying review widgets on your behalf.

  • Automated testimonial collection and submission: Enable your agent to create and submit new customer testimonials directly into your Endorsal account, streamlining the feedback process.
  • Campaign management and insights: Let your agent retrieve and list all AutoRequest campaigns, check campaign details, and monitor their status to keep your outreach efforts on track.
  • Contact and testimonial organization: Easily fetch, list, and manage all contacts, as well as pull up all testimonials associated with a specific contact for better relationship tracking.
  • Widget and property access: Allow your agent to fetch details of specific display widgets and properties, helping you control how testimonials are showcased on your website.
  • Tag and metadata retrieval: Retrieve tag details and full testimonial metadata, so your agent can help organize, group, or analyze your customer feedback efficiently.

Supported Tools & Triggers

Tools
Archive ContactTool to archive a contact using its unique identifier.
Create ContactTool to create a new contact in your Endorsal account.
Create TagTool to create a new tag in Endorsal.
Create TestimonialTool to submit a new testimonial.
Delete TagTool to delete a tag using its unique identifier.
Delete TestimonialTool to permanently delete a testimonial by its ID.
Get AutoRequest CampaignTool to retrieve a specific AutoRequest campaign by its unique identifier.
Get ContactTool to retrieve details of a specific contact by its unique identifier.
Get TagTool to retrieve details of a specific tag by its unique identifier.
Get TestimonialRetrieves complete details of a specific testimonial by its ID.
Get Wall of LoveRetrieves the Wall of Love for a property, returning testimonials that match its configuration options.
Get WidgetTool to retrieve details of a specific widget by its unique identifier.
List All TagsTool to retrieve a list of all Tag Objects across all properties in your Endorsal account.
List AutoRequest CampaignsTool to retrieve a list of all AutoRequest campaigns.
List ContactsRetrieves a paginated list of all contacts for a specific property in your Endorsal account.
List Contact TestimonialsRetrieves all testimonials associated with a specific contact in Endorsal.
List PropertiesTool to retrieve all properties for the authenticated account.
List TagsRetrieves all tags associated with a specific property in Endorsal.
List Tag TestimonialsTool to retrieve all testimonials for a given tag.
List TestimonialsRetrieves a paginated list of all testimonials in your Endorsal account.
List WidgetsRetrieves all testimonial display widgets associated with your Endorsal account.
Search ContactsTool to search contacts using query Match Objects.
Search TestimonialsTool to search testimonials using query Match Objects.
Tag TestimonialTool to add tag(s) to a testimonial.
Update ContactTool to update a contact's information.
Update TestimonialTool to update an existing testimonial.

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:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Endorsal 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 Endorsal 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 Endorsal MCP URL

Create a Composio Tool Router session for Endorsal

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

url = session.mcp.url
What's happening:
  • You create a Endorsal only session through Composio
  • Composio returns an MCP HTTP URL that exposes Endorsal 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 Endorsal 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=["endorsal"],
)
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 Endorsal through Composio's Tool Router. The agent can perform Endorsal 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

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FAQ

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

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

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

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

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