How to integrate Productboard MCP with Pydantic AI

This guide walks you through connecting Productboard to Pydantic AI 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 Pydantic AI 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 Pydantic AI 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 Pydantic AI 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

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TL;DR

Here's what you'll learn:
  • How to set up your Composio API key and User ID
  • How to create a Composio Tool Router session for Productboard
  • How to attach an MCP Server to a Pydantic AI agent
  • How to stream responses and maintain chat history
  • How to build a simple REPL-style chat interface to test your Productboard workflows

What is Pydantic AI?

Pydantic AI is a Python framework for building AI agents with strong typing and validation. It leverages Pydantic's data validation capabilities to create robust, type-safe AI applications.

Key features include:

  • Type Safety: Built on Pydantic for automatic data validation
  • MCP Support: Native support for Model Context Protocol servers
  • Streaming: Built-in support for streaming responses
  • Async First: Designed for async/await patterns

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 step09 STEPS
1

Prerequisites

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account with an active API key
  • Basic familiarity with Python and async programming
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 pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like Productboard
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file
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

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates your agent to Composio's API
  • USER_ID associates your session with your account for secure tool access
  • OPENAI_API_KEY to access OpenAI LLMs
5

Import dependencies

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()
What's happening:
  • We load environment variables and import required modules
  • Composio manages connections to Productboard
  • MCPServerStreamableHTTP connects to the Productboard MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant
6

Create a Tool Router Session

python
async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Productboard
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["productboard"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")
What's happening:
  • We're creating a Tool Router session that gives your agent access to Productboard tools
  • The create method takes the user ID and specifies which toolkits should be available
  • The returned session.mcp.url is the MCP server URL that your agent will use
7

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
productboard_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[productboard_mcp],
    instructions=(
        "You are a Productboard assistant. Use Productboard tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Productboard endpoint
  • The agent uses GPT-5 to interpret user commands and perform Productboard operations
  • The instructions field defines the agent's role and behavior
8

Build the chat interface

python
# Simple REPL with message history
history = []
print("Chat started! Type 'exit' or 'quit' to end.\n")
print("Try asking the agent to help you with Productboard.\n")

while True:
    user_input = input("You: ").strip()
    if user_input.lower() in {"exit", "quit", "bye"}:
        print("\nGoodbye!")
        break
    if not user_input:
        continue

    print("\nAgent is thinking...\n", flush=True)

    async with agent.run_stream(user_input, message_history=history) as stream_result:
        collected_text = ""
        async for chunk in stream_result.stream_output():
            text_piece = None
            if isinstance(chunk, str):
                text_piece = chunk
            elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                text_piece = chunk.delta
            elif hasattr(chunk, "text"):
                text_piece = chunk.text
            if text_piece:
                collected_text += text_piece
        result = stream_result

    print(f"Agent: {collected_text}\n")
    history = result.all_messages()
What's happening:
  • The agent reads input from the terminal and streams its response
  • Productboard API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns
9

Run the application

python
if __name__ == "__main__":
    asyncio.run(main())
What's happening:
  • The asyncio loop launches the agent and keeps it running until you exit

Complete Code

Here's the complete code to get you started with Productboard and Pydantic AI:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerStreamableHTTP

load_dotenv()

async def main():
    api_key = os.getenv("COMPOSIO_API_KEY")
    user_id = os.getenv("USER_ID")
    if not api_key or not user_id:
        raise RuntimeError("Set COMPOSIO_API_KEY and USER_ID in your environment")

    # Create a Composio Tool Router session for Productboard
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["productboard"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")

    # Attach the MCP server to a Pydantic AI Agent
    productboard_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[productboard_mcp],
        instructions=(
            "You are a Productboard assistant. Use Productboard tools to help users "
            "with their requests. Ask clarifying questions when needed."
        ),
    )

    # Simple REPL with message history
    history = []
    print("Chat started! Type 'exit' or 'quit' to end.\n")
    print("Try asking the agent to help you with Productboard.\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "bye"}:
            print("\nGoodbye!")
            break
        if not user_input:
            continue

        print("\nAgent is thinking...\n", flush=True)

        async with agent.run_stream(user_input, message_history=history) as stream_result:
            collected_text = ""
            async for chunk in stream_result.stream_output():
                text_piece = None
                if isinstance(chunk, str):
                    text_piece = chunk
                elif hasattr(chunk, "delta") and isinstance(chunk.delta, str):
                    text_piece = chunk.delta
                elif hasattr(chunk, "text"):
                    text_piece = chunk.text
                if text_piece:
                    collected_text += text_piece
            result = stream_result

        print(f"Agent: {collected_text}\n")
        history = result.all_messages()

if __name__ == "__main__":
    asyncio.run(main())

Conclusion

You've built a Pydantic AI agent that can interact with Productboard through Composio's Tool Router. With this setup, your agent can perform real Productboard actions through natural language. You can extend this further by:
  • Adding other toolkits like Gmail, HubSpot, or Salesforce
  • Building a web-based chat interface around this agent
  • Using multiple MCP endpoints to enable cross-app workflows (for example, Gmail + Productboard for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.
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

CrewAI logo

CrewAI

Use Productboard MCP with CrewAI

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. Pydantic AI 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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Karan skipped his own birthday party to fix our critical issue. It was 10pm and he diverted his Waymo to help us instead. This really sets the bar — it shows the commitment you need when users rely on your software.

Harsha Gaddipati
Harsha Gaddipati
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.

Abhi Arya
Abhi Arya
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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CEO, Zams

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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Founder, Extra Thursday

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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Founder & CEO, SwarmZero

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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