How to integrate Productboard MCP with CrewAI

This guide walks you through connecting Productboard to CrewAI using the Composio tool router. By the end, you'll have a working Productboard agent that can create a new feature idea in productboard, list all features in the current release, add customer feedback to a specific feature through natural language commands. This guide will help you understand how to give your CrewAI agent real control over a Productboard account through Composio's Productboard MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Productboard is a product management platform that consolidates feedback and prioritizes features. It helps teams align roadmaps with customer insights and strategic goals.

99 Tools

Introduction

This guide walks you through connecting Productboard to CrewAI using the Composio tool router. By the end, you'll have a working Productboard agent that can create a new feature idea in productboard, list all features in the current release, add customer feedback to a specific feature through natural language commands.

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

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

Also integrate Productboard with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndex

TL;DR

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

The Productboard MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Productboard account. It provides structured and secure access to your product management workspace, so your agent can perform actions like managing feature ideas, collecting user feedback, prioritizing roadmap items, and aligning strategic goals on your behalf.

  • Centralized feedback collection: Let your agent gather, aggregate, and organize product feedback from stakeholders and customers, so nothing slips through the cracks.
  • Feature and idea management: Enable your agent to create, update, categorize, and prioritize feature ideas or product requests in your Productboard workspace.
  • Roadmap planning and alignment: Ask your agent to assist in building and updating product roadmaps, ensuring initiatives align with business objectives and customer needs.
  • Insightful prioritization workflows: Have the agent score, sort, and recommend features for development using built-in prioritization frameworks and customer impact data.
  • Collaboration and stakeholder updates: Empower your agent to share status updates, progress changes, and new plans with internal teams and stakeholders directly from Productboard.

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

Step by step08 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Productboard connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python
2

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.
3

Install dependencies

bash
pip install composio crewai crewai-tools[mcp] python-dotenv
What's happening:
  • composio connects your agent to Productboard via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools[mcp] includes MCP helpers
  • python-dotenv loads environment variables from .env
4

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
5

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 Productboard MCP URL
6

Create a Composio Tool Router session for Productboard

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

url = session.mcp.url
What's happening:
  • You create a Productboard only session through Composio
  • Composio returns an MCP HTTP URL that exposes Productboard tools
7

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.
8

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 Productboard 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=["productboard"],
)
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 Productboard through Composio's Tool Router. The agent can perform Productboard 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
TOOLS

Supported Tools

Every Productboard action and event your agent gets out of the box.

Add Note Followers

Tool to add multiple followers to a Productboard note.

Add Note Tag

Adds a tag to a Productboard note for categorization and organization.

Create Company in Productboard

Tool to create a new company in Productboard.

Create Company Custom Field

Tool to create a new custom field for companies.

Create Component

Tool to create a new (sub)component under a product or component.

Create Entity Relationship

Tool to create a relationship between two entities in Productboard.

Create Entity (v2)

Tool to create a new entity in Productboard using the v2 API.

Create Feature

Tool to create a new feature or subfeature in Productboard.

Create Feature-Objective Link

Tool to create a link between a feature and an objective (OKR).

Create Note Link

Tool to create a link between a note and an entity.

Create Note (v2)

Tool to create a new note in Productboard using the v2 API.

Create Objective

Tool to create a new objective in Productboard.

Create Objective-Feature Link

Tool to create a new link between an objective and a feature.

Create Release

Tool to create a new release in Productboard.

Create User

Tool to create a new user in Productboard.

Create Webhook Subscription

Tool to create a new webhook subscription.

Delete Company

Tool to delete a specific company.

Delete Company Field

Tool to delete a specific company custom field.

Delete Custom Field Value

Tool to delete a custom field value from a hierarchy entity in Productboard.

Delete Entity Relationship

Tool to delete a relationship between two entities.

Delete Entity V2

Tool to delete a PM entity using the v2 API.

Delete Feature

Tool to delete a specific feature.

Delete Feature Objective Link

Tool to delete a link between a feature and an objective.

Delete Initiative

Tool to delete a specific initiative.

Delete Key Result

Tool to delete a specific key result from Productboard.

Delete Note Relationship

Tool to delete a note relationship.

Delete Note V2

Tool to delete a note using the v2 API.

Delete Note Tag

Tool to remove a tag from a Productboard note.

Delete Objective

Tool to delete a specific objective from Productboard.

Delete Objective-Feature Link

Tool to delete a link between an objective and a feature.

Delete Release

Tool to delete a specific release.

Delete User

Tool to delete a specific user.

Delete Webhook Subscription

Tool to delete a webhook subscription.

Get Component

Tool to retrieve details of a specific component.

Get Custom Field Value

Tool to retrieve a custom field's value for a specific hierarchy entity.

Get Entity Configuration

Tool to retrieve entity configuration for a specific type.

Get Entity V2

Tool to retrieve a PM entity using the v2 API.

Get Feature Release Assignment

Tool to retrieve a specific feature release assignment.

Get Hierarchy Entity Custom Field

Tool to retrieve a specific custom field definition for hierarchy entities.

Get Notes Configuration V2

Tool to retrieve note configuration by type (simple, conversation, or opportunity).

Get Note V2

Tool to retrieve a note using the v2 API.

Get Objective

Tool to retrieve details of a specific objective.

Get Release

Tool to retrieve details of a specific release by ID.

Get Release Group

Tool to retrieve details of a specific release group.

Get Webhook Subscription

Tool to retrieve details of a specific webhook subscription.

List Analytics Member Activities V2

Tool to retrieve member activity analytics data from Productboard.

List Companies

Tool to list companies.

List Company Custom Fields

Lists all custom field definitions for companies in your Productboard workspace.

List Custom Fields

Lists custom field definitions for hierarchy entities (Products, Components, Features).

List Custom Field Values

Lists custom field values for hierarchy entities (products, components, features) in Productboard.

List Entities Configurations V2

Tool to retrieve configurations for all entity types in Productboard.

List Entity Relationships

Tool to retrieve relationships for an entity in Productboard.

List Entities V2

Tool to list entities from Productboard using the v2 API.

List Feature Initiatives

Tool to list initiatives linked to a given feature.

List Feature Objectives

Lists all objectives (OKRs) linked to a top-level feature.

List Feature Release Assignments

Tool to list feature–release assignments.

List Feature Statuses

Tool to list feature statuses.

List Feedback Form Configurations

Tool to list feedback form configurations.

List Initiatives

Tool to list initiatives from Productboard.

List Jira Integrations

Tool to list Jira integrations.

List Key Results

List key results from Productboard.

List Notes Configurations V2

Tool to list note configurations from Productboard v2 API.

List Note Links

Tool to list links associated with a note.

List Note Relationships V2

Tool to retrieve relationships associated with a note.

List Notes V2

Tool to retrieve a paginated list of notes from Productboard using the v2 API.

List Note Tags

Tool to retrieve all tags associated with a specific Productboard note.

List Objective Linked Features

Lists all features linked to a specific objective.

List Objective Linked Initiatives

Tool to list initiatives linked to a specific objective.

List Plugin Integrations

List all plugin integrations in the Productboard workspace.

List Release Groups

Lists all release groups in the Productboard workspace.

List Releases

Tool to list all releases in Productboard.

List Users

Retrieves a paginated list of all users in the Productboard workspace.

List Webhook Subscriptions

Tool to list all webhook subscriptions.

Remove Note Follower

Tool to remove a follower from a Productboard note.

Retrieve Company

Tool to retrieve details of a specific company.

Retrieve Company Field

Tool to retrieve details of a specific company custom field.

Retrieve Company Field Value

Tool to retrieve a specific company custom field value.

Retrieve Feature

Tool to retrieve details of a specific feature.

Retrieve Product

Tool to retrieve details of a specific product.

Retrieve User

Tool to retrieve details of a specific user.

List SCIM Users

Tool to list users via SCIM.

Search Entities V2

Tool to search for entities across Productboard using the v2 API.

Set Company Field Value

Tool to set or replace a specific company custom field's value.

Set Custom Field Value

Tool to set a custom field value on a hierarchy entity.

Set Entity Parent Relationship

Tool to set parent relationship on an entity.

Set Feature Release Assignment

Tool to update a feature release assignment.

Set Features

Tool to update a feature by ID.

Set Note Customer Relationship

Tool to set a customer relationship on a note in Productboard.

Set Product

Tool to update a product using PUT method in Productboard.

Update Company Custom Field

Tool to update a company custom field name.

Update Company

Tool to update an existing company in Productboard.

Update Component

Tool to update an existing component.

Update Entity V2

Tool to update a PM entity using the v2 API.

Update Features

Tool to update a feature in Productboard.

Update Note V2

Tool to update a note using the v2 API.

Update Objective

Tool to update an existing objective in Productboard.

Update Product

Tool to update a product in Productboard.

Update Release

Tool to update an existing release in Productboard.

Update User

Tool to update a user's information.

FRAMEWORKS

How to build Productboard MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Productboard MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Productboard MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Productboard MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Productboard MCP with Claude Cowork

Codex logo

Codex

Use Productboard MCP with Codex

OpenClaw logo

OpenClaw

Use Productboard MCP with OpenClaw

Hermes logo

Hermes

Use Productboard MCP with Hermes

CLI logo

CLI

Use Productboard MCP with CLI

Google ADK logo

Google ADK

Use Productboard MCP with Google ADK

LangChain logo

LangChain

Use Productboard MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Productboard MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Productboard MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Productboard MCP with LlamaIndex

FAQ

Frequently asked questions

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

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 Productboard tools.

Yes, absolutely. You can configure which Productboard 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.

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 Productboard data and credentials are handled as safely as possible.

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Co-founder, Slashy

A lot of students tell us that the moment their connected tools start talking to each other inside Opennote feels almost magical. The agent just knows them, and it's immensely helped keep new users on the platform.

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Co-founder, Opennote

We chose Composio over Pipedream because it delivered depth where it mattered — niche tools and tricky edge cases other platforms simply ignored. That gave us confidence to scale without compromising.

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As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down managing agent auth would have been a death sentence.

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Before Composio, adding tool integrations was slow and resource-intensive. Each one could take weeks of engineering time, and maintaining them meant constantly keeping up with API changes.

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With hands-on help from their founder, we integrated Gmail and Google Drive in just 30 minutes. This level of personal support and commitment is exactly what startups should strive for.

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