# How to integrate Productlane MCP with Pydantic AI

```json
{
  "title": "How to integrate Productlane MCP with Pydantic AI",
  "toolkit": "Productlane",
  "toolkit_slug": "productlane",
  "framework": "Pydantic AI",
  "framework_slug": "pydantic-ai",
  "url": "https://composio.dev/toolkits/productlane/framework/pydantic-ai",
  "markdown_url": "https://composio.dev/toolkits/productlane/framework/pydantic-ai.md",
  "updated_at": "2026-05-12T10:22:53.644Z"
}
```

## Introduction

This guide walks you through connecting Productlane to Pydantic AI using the Composio tool router. By the end, you'll have a working Productlane agent that can open productlane widget for user feedback, display specific docs article in widget, register listener for widget submit events through natural language commands.
This guide will help you understand how to give your Pydantic AI agent real control over a Productlane account through Composio's Productlane MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Productlane with

- [OpenAI Agents SDK](https://composio.dev/toolkits/productlane/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/productlane/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/productlane/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/productlane/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/productlane/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/productlane/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/productlane/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/productlane/framework/cli)
- [Google ADK](https://composio.dev/toolkits/productlane/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/productlane/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/productlane/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/productlane/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/productlane/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/productlane/framework/crew-ai)

## 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 Productlane
- 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 Productlane 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 Productlane MCP server, and what's possible with it?

The Productlane MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Productlane account. It provides structured and secure access to your customer feedback and support workflows, so your agent can programmatically control the Productlane widget, surface documentation, listen for widget events, and manage user interaction—all on your behalf.
- Dynamic widget control: Let your agent open, close, enable, disable, or toggle the Productlane widget in response to customer or team actions.
- Contextual docs surfacing: Automatically display specific Productlane documentation articles within the widget to assist users at the right moment.
- Event-driven automation: Register or remove event listeners so your agent can react to widget events like open, close, submit, or widget load—enabling smart, real-time workflows.
- Seamless widget experience: Programmatically manage the widget's state across your app to ensure users always get the right support touchpoint.
- Custom interaction flows: Use the widget's event system to trigger your own logic or follow-ups based on how users interact with Productlane support.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `PRODUCTLANE_CREATE_CHANGELOG` | Create Changelog Entry | Tool to create a new changelog entry in Productlane. Use when you need to document product updates, new features, or bug fixes. The content supports markdown format including headings, bulleted lists, and other markdown features. |
| `PRODUCTLANE_CREATE_COMPANY` | Create Company | Tool to create a new company in Productlane. Use when you need to add a company record with optional domain-based contact auto-linking. Authentication required via Bearer token. |
| `PRODUCTLANE_CREATE_CONTACT` | Create Contact | Tool to create a new contact in your Productlane workspace with optional company linking. Use when adding new contacts to track customer interactions and feedback. |
| `PRODUCTLANE_CREATE_FEEDBACK` | Create Feedback | Tool to create new feedback in Productlane. Use when submitting user feedback, feature requests, or bug reports through the API. This is equivalent to adding feedback through the Productlane widget or portal. Requires email, feedback text, and pain level. |
| `PRODUCTLANE_CREATE_INSIGHT` | Create Insight | Tool to create a new insight/thread in Productlane workspace. Use when you need to capture customer feedback, feature requests, or bug reports. |
| `PRODUCTLANE_CREATE_THREAD` | Create Thread | Tool to create a new thread in Productlane. Use when you need to create feedback, feature requests, or bug reports from users. |
| `PRODUCTLANE_CREATE_UPVOTE` | Create Upvote | Tool to create an upvote for a project or issue. Use when you need to record user support for a project or issue. Either projectId or issueId must be provided. |
| `PRODUCTLANE_DELETE_COMPANY` | Delete Company | Tool to delete a company by its unique ID. Use when you need to permanently remove a company and all associated data from Productlane. |
| `PRODUCTLANE_DELETE_CONTACT` | Delete Contact | Tool to delete a contact by ID. Use when you need to permanently remove a contact from Productlane. Authentication is required and you can only delete your own contacts. |
| `PRODUCTLANE_DELETE_UPVOTE` | Delete Upvote | Tool to delete an upvote by its unique ID. Use when removing a previously cast upvote on an issue or project. |
| `PRODUCTLANE_ENABLE_WIDGET` | Enable Productlane Widget | Tool to enable the Productlane widget. Use after confirming the widget is currently disabled. |
| `PRODUCTLANE_GET_CHANGELOG` | Get Changelog | Tool to retrieve a published changelog by ID from Productlane. Use when you need to fetch details about a specific changelog entry. No authorization is required for published changelogs. |
| `PRODUCTLANE_GET_COMPANY` | Get Company by ID | Tool to retrieve a company by its unique ID. Use when you need detailed information about a specific company including its metadata, integrations, and associated data. |
| `PRODUCTLANE_GET_CONTACT` | Get Contact | Tool to retrieve a contact by ID or email from Productlane. Use when you need to fetch details about a specific contact in your workspace. Authentication is required and you can only access contacts that belong to your workspace. |
| `PRODUCTLANE_GET_HELP_CENTER_ARTICLE` | Get Help Center Article | Tool to retrieve a help center article by its ID. Use when you need to fetch details, content, and metadata for a specific help center article. |
| `PRODUCTLANE_GET_INSIGHT` | Get Insight | Tool to retrieve an insight/thread by its ID. Use when you need to fetch details about a specific piece of feedback or customer insight. |
| `PRODUCTLANE_GET_ISSUE` | Get Issue by ID | Tool to retrieve a specific issue by its ID from a workspace. Use when you need to fetch detailed information about an issue including its title, description, status, priority, and metadata. |
| `PRODUCTLANE_GET_LINEAR_OPTIONS` | Get Linear Customer Options | Tool to retrieve available Linear customer statuses and tiers for your workspace. Use when you need to know the valid Linear options before creating or updating companies. Returns null for both statuses and tiers if Linear is not connected. |
| `PRODUCTLANE_GET_PROJECT` | Get Project | Tool to retrieve a project by its ID from a workspace. Use when you need to fetch details about a specific project including its name, description, progress, and associated metadata. |
| `PRODUCTLANE_GET_WORKSPACE` | Get Workspace | Tool to fetch workspace details by ID. Use when you need to retrieve workspace configuration, branding, or latest changelog information. |
| `PRODUCTLANE_INVITE_USER` | Invite User to Workspace | Tool to invite a new user to your Productlane workspace. An invitation email with a join link will be sent to the user. Only admins can invite users. |
| `PRODUCTLANE_LIST_CHANGELOGS` | List Changelogs | Tool to list all published changelogs for a workspace by ID. Use when you need to retrieve changelog entries for a specific Productlane workspace. |
| `PRODUCTLANE_LIST_COMPANIES` | List Companies | Tool to list all companies in Productlane. Use 'take' and 'skip' parameters to paginate through results. Supports filtering by domain or name. |
| `PRODUCTLANE_LIST_CONTACTS` | List contacts | Tool to retrieve all contacts for your workspace. Use when you need to list contacts with optional pagination support. |
| `PRODUCTLANE_LIST_HELP_CENTER_ARTICLES` | List Help Center Articles | Tool to list all help center articles for a specific workspace. Use when you need to retrieve documentation or support articles from a workspace's help center. |
| `PRODUCTLANE_LIST_INSIGHTS` | List Insights | Tool to list all threads/insights for your workspace with optional filtering. Use when you need to retrieve insights filtered by state, issue, or project, with support for pagination via 'take' and 'skip' parameters. |
| `PRODUCTLANE_LIST_ISSUES` | List Productlane Issues | Tool to retrieve all issues from a Productlane workspace. Use when you need to fetch issues from a workspace that has their portal/roadmap published. |
| `PRODUCTLANE_LIST_MEMBERS` | List Workspace Members | Tool to retrieve all members of your workspace with their roles and user information. Returns memberships sorted by role (admins first). |
| `PRODUCTLANE_LIST_PROJECTS` | List Projects | Tool to retrieve all projects within a workspace. Use when you need to list available projects from a published Productlane workspace portal or roadmap. |
| `PRODUCTLANE_UPDATE_COMPANY` | Update Company | Tool to update an existing company record in Productlane by its unique identifier. Use when you need to modify company details such as name, domains, revenue, size, status, tier, or external IDs. All fields except the company ID are optional. |
| `PRODUCTLANE_UPDATE_CONTACT` | Update Contact | Tool to update an existing contact in Productlane. Use when you need to modify contact details such as name, email, or company associations. Users can only update their own contacts. |
| `PRODUCTLANE_UPDATE_INSIGHT` | Update Insight | Tool to update an existing insight (thread) by ID. Use when you need to modify insight properties such as title, state, pain level, or associations with projects, companies, or contacts. |
| `PRODUCTLANE_WIDGET_CLOSE` | Close Productlane Widget | Tool to close the Productlane widget. Use when you need to hide the widget after completing an interaction. |
| `PRODUCTLANE_WIDGET_DISABLE` | Disable Productlane Widget | Tool to disable the Productlane widget across the entire page. Use when needing to turn off the widget programmatically. |
| `PRODUCTLANE_WIDGET_OFF_EVENT` | Widget off event | Tool to remove a previously registered widget event listener. Use after widget setup to deregister callbacks. |
| `PRODUCTLANE_WIDGET_ON_EVENT` | Register Widget Event Listener | Tool to register a listener for Productlane widget events. Use after widget initialization to run custom logic on 'open', 'close', 'submit', or 'widgetLoaded' events. |
| `PRODUCTLANE_WIDGET_OPEN` | Open Productlane Widget | Tool to generate a JavaScript snippet that opens the Productlane widget. Use when you need to programmatically display the widget on your front-end after page load. |
| `PRODUCTLANE_WIDGET_OPEN_DOCS` | Open Productlane Docs Article in Widget | Tool to open a specific docs article in the Productlane widget. Use after widget initialization and load. |
| `PRODUCTLANE_WIDGET_TOGGLE` | Toggle Productlane Widget | Tool to toggle the Productlane widget between open and closed states. Use after widget initialization. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Productlane MCP server is an implementation of the Model Context Protocol that connects your AI agent to Productlane. It provides structured and secure access so your agent can perform Productlane operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 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

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) 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](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Navigate to your API settings and generate a new API key.
- Store this key securely as you'll need it for authentication.

### 2. Install dependencies

Install the required libraries.
What's happening:
- composio connects your agent to external SaaS tools like Productlane
- pydantic-ai lets you create structured AI agents with tool support
- python-dotenv loads your environment variables securely from a .env file
```bash
pip install composio pydantic-ai python-dotenv
```

### 3. Set up environment variables

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
```bash
COMPOSIO_API_KEY=your_composio_api_key_here
USER_ID=your_user_id_here
OPENAI_API_KEY=your_openai_api_key
```

### 4. Import dependencies

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

### 5. Create a Tool Router Session

What's happening:
- We're creating a Tool Router session that gives your agent access to Productlane 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
```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 Productlane
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["productlane"],
    )
    url = session.mcp.url
    if not url:
        raise ValueError("Composio session did not return an MCP URL")
```

### 6. Initialize the Pydantic AI Agent

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

### 7. Build the chat interface

What's happening:
- The agent reads input from the terminal and streams its response
- Productlane API calls happen automatically under the hood
- The model keeps conversation history to maintain context across turns
```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 Productlane.\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()
```

### 8. Run the application

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

## Complete Code

```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 Productlane
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["productlane"],
    )
    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
    productlane_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[productlane_mcp],
        instructions=(
            "You are a Productlane assistant. Use Productlane 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 Productlane.\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 Productlane through Composio's Tool Router. With this setup, your agent can perform real Productlane 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 + Productlane for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.

## How to build Productlane MCP Agent with another framework

- [OpenAI Agents SDK](https://composio.dev/toolkits/productlane/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/productlane/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/productlane/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/productlane/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/productlane/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/productlane/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/productlane/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/productlane/framework/cli)
- [Google ADK](https://composio.dev/toolkits/productlane/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/productlane/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/productlane/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/productlane/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/productlane/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/productlane/framework/crew-ai)

## Related Toolkits

- [Aeroleads](https://composio.dev/toolkits/aeroleads) - Aeroleads is a B2B lead generation platform for finding business emails and phone numbers. Grow your sales pipeline faster with powerful prospecting tools.
- [Autobound](https://composio.dev/toolkits/autobound) - Autobound is an AI-powered sales engagement platform that crafts hyper-personalized outreach and insights. It helps sales teams boost response rates and close more deals through tailored content and recommendations.
- [Better proposals](https://composio.dev/toolkits/better_proposals) - Better Proposals is a web-based tool for crafting and sending professional proposals. It helps teams impress clients and close deals faster with slick, easy-to-use templates.
- [Bidsketch](https://composio.dev/toolkits/bidsketch) - Bidsketch is a proposal software that helps businesses create professional proposals quickly and efficiently. It streamlines the proposal process, saving time while boosting client win rates.
- [Bolna](https://composio.dev/toolkits/bolna) - Bolna is an AI platform for building conversational voice agents. It helps businesses automate support and streamline interactions through natural, voice-powered conversations.
- [Botsonic](https://composio.dev/toolkits/botsonic) - Botsonic is a no-code AI chatbot builder for easily creating and deploying chatbots to your website. It empowers businesses to offer conversational experiences without writing code.
- [Botstar](https://composio.dev/toolkits/botstar) - BotStar is a comprehensive chatbot platform for designing, developing, and training chatbots visually on Messenger and websites. It helps businesses automate conversations and customer interactions without coding.
- [Callerapi](https://composio.dev/toolkits/callerapi) - CallerAPI is a white-label caller identification platform for branded caller ID and fraud prevention. It helps businesses boost customer trust while stopping spam, fraud, and robocalls.
- [Callingly](https://composio.dev/toolkits/callingly) - Callingly is a lead response management platform that automates immediate call and text follow-ups with new leads. It helps sales teams boost response speed and close more deals by connecting seamlessly with CRMs and lead sources.
- [Callpage](https://composio.dev/toolkits/callpage) - Callpage is a lead capture platform that lets businesses instantly connect with website visitors via callback. It boosts lead generation and increases your sales conversion rates.
- [Clearout](https://composio.dev/toolkits/clearout) - Clearout is an AI-powered service for verifying, finding, and enriching email addresses. It boosts deliverability and helps you discover high-quality leads effortlessly.
- [Clientary](https://composio.dev/toolkits/clientary) - Clientary is a platform for managing clients, invoices, projects, proposals, and more. It streamlines client work and saves you serious admin time.
- [Convolo ai](https://composio.dev/toolkits/convolo_ai) - Convolo ai is an AI-powered communications platform for sales teams. It accelerates lead response and improves conversion rates by automating calls and integrating workflows.
- [Delighted](https://composio.dev/toolkits/delighted) - Delighted is a customer feedback platform based on the Net Promoter System®. It helps you quickly gather, track, and act on customer sentiment.
- [Emelia](https://composio.dev/toolkits/emelia) - Emelia is an all-in-one B2B prospecting platform for cold-email, LinkedIn outreach, and prospect research. It streamlines outbound campaigns so you can find, engage, and warm up leads faster.
- [Findymail](https://composio.dev/toolkits/findymail) - Findymail is a B2B data provider offering verified email and phone contacts for sales prospecting. Enhance outreach with automated exports, email verification, and CRM enrichment.
- [Freshdesk](https://composio.dev/toolkits/freshdesk) - Freshdesk is customer support software with ticketing and automation tools. It helps teams streamline helpdesk operations for faster, better customer support.
- [Fullenrich](https://composio.dev/toolkits/fullenrich) - FullEnrich is a B2B contact enrichment platform that aggregates emails and phone numbers from 15+ data vendors. Instantly find and verify lead contact data to boost your outreach.
- [Gatherup](https://composio.dev/toolkits/gatherup) - GatherUp is a customer feedback and online review management platform. It helps businesses boost their reputation by streamlining how they collect and manage customer feedback.
- [Getprospect](https://composio.dev/toolkits/getprospect) - Getprospect is a business email discovery tool with LinkedIn integration. Use it to quickly find and verify professional email addresses.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Productlane MCP?

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

### Can I use Tool Router MCP with Pydantic AI?

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 Productlane tools.

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

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

---
[See all toolkits](https://composio.dev/toolkits) · [Composio docs](https://docs.composio.dev/llms.txt)
