How to integrate Harvest MCP with CrewAI

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Introduction

This guide walks you through connecting Harvest to CrewAI using the Composio tool router. By the end, you'll have a working Harvest agent that can create a new client for acme corp, log an expense for project 'website redesign', generate an invoice for hours worked this week, send an estimate message to a client through natural language commands.

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

The Harvest MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Harvest account. It provides structured and secure access to your time-tracking, invoicing, and project management data, so your agent can create clients, log expenses, send invoices, record payments, and manage estimates automatically on your behalf.

  • Client and contact management: Seamlessly create new clients and add contacts to keep your client list up to date without manual entry.
  • Estimate creation and communication: Automatically generate new estimates, categorize line items, and send estimate messages or updates to clients.
  • Expense tracking automation: Log new expense entries against projects, ensuring accurate financial records and effortless cost tracking.
  • Streamlined invoicing and payments: Create professional invoices, categorize invoice items, send invoice notifications, and record payments as soon as they happen.
  • Project financial workflow optimization: Let your agent handle the full cycle—from creating clients to sending invoices and tracking payments—saving your team valuable time and reducing errors.

Supported Tools & Triggers

Tools
Create ClientTool to create a new client.
Create Client ContactTool to create a new client contact.
Create EstimateTool to create a new estimate.
Create Estimate Item CategoryTool to create a new estimate item category in harvest.
Create Estimate MessageTool to create a new message for an estimate.
Create ExpenseTool to create a new expense entry.
Create InvoiceTool to create a new invoice.
Create Invoice Item CategoryTool to create a new invoice item category.
Create Invoice MessageTool to create a new message for an invoice.
Create Invoice PaymentTool to create a new payment on an invoice.
Create ProjectTool to create a new project.
Create TaskTool to create a new task.
Create Time EntryTool to create a new time entry.
Create UserTool to create a new user.
Delete ClientTool to delete a client.
Delete Client ContactTool to delete a client contact.
Delete EstimateTool to delete an estimate.
Delete Estimate MessageTool to delete an estimate message.
Delete InvoiceTool to delete an invoice.
Delete Invoice Item CategoryTool to delete an invoice item category.
Delete Invoice MessageTool to delete a message from an invoice.
Delete Invoice PaymentTool to delete an invoice payment.
Delete ProjectTool to delete a project.
Delete TaskTool to delete a task.
Delete Time EntryTool to delete a time entry.
Delete UserTool to delete a user.
Get ClientTool to retrieve a specific client by id.
Get Client ContactTool to retrieve a specific client contact.
Get Company InfoTool to retrieve information about the authenticated user's company.
Get EstimateTool to retrieve a specific estimate by id.
Get InvoiceTool to retrieve a specific invoice by id.
Get ProjectTool to retrieve a specific harvest project by id.
Get TaskTool to retrieve a specific task by id.
Get Time EntryTool to retrieve a single time entry by id.
Get UserTool to retrieve a specific user by id.
List Client ContactsTool to list client contacts.
List ClientsTool to list clients.
List Estimate MessagesTool to list messages for an estimate.
List Expense CategoriesTool to list expense categories.
List Invoice Item CategoriesTool to retrieve invoice item categories.
List Invoice MessagesTool to list messages associated with a given invoice.
List Invoice PaymentsTool to retrieve payments for a specific invoice.
List InvoicesTool to list invoices.
List projectsTool to list projects.
List TasksTool to list tasks.
List Time EntriesTool to retrieve a list of time entries.
List UsersTool to list users.
Update ClientTool to update an existing client.
Update Client ContactTool to update a client contact.
Update Company InfoTool to update information about the company.
Update EstimateTool to update an existing estimate.
Update Estimate Item CategoryTool to update an estimate item category.
Update ExpenseTool to update an existing expense.
Update InvoiceTool to update an existing invoice.
Update ProjectTool to update an existing project.
Update TaskTool to update an existing task.
Update Time EntryTool to update an existing time entry.
Update UserTool to update an existing user.

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 Harvest 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 Harvest 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 Harvest MCP URL

Create a Composio Tool Router session for Harvest

python
composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
session = composio.create(
    user_id=os.getenv("USER_ID"),
    toolkits=["harvest"],
)
url = session.mcp.url
What's happening:
  • You create a Harvest only session through Composio
  • Composio returns an MCP HTTP URL that exposes Harvest 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="Harvest Assistant",
    goal="Help users interact with Harvest through natural language commands",
    backstory=(
        "You are an expert assistant with access to Harvest tools. "
        "You can perform various Harvest 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 Harvest 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 Harvest 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 Harvest 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_harvest_agent.py

Complete Code

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

python
# file: crewai_harvest_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 Harvest session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["harvest"],
    )
    url = session.mcp.url

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

    # Create Harvest assistant agent
    toolkit_agent = Agent(
        role="Harvest Assistant",
        goal="Help users interact with Harvest through natural language commands",
        backstory=(
            "You are an expert assistant with access to Harvest tools. "
            "You can perform various Harvest 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 Harvest 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 Harvest 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 Harvest through Composio's Tool Router. The agent can perform Harvest 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 Harvest MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Harvest MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Harvest MCP with Claude Agent SDK

Google ADK

Google ADK

Use Harvest MCP with Google ADK

LangChain

LangChain

Use Harvest MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Harvest MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Harvest MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Harvest MCP with LlamaIndex

FAQ

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

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

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

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

Used by agents from

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

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