How to integrate Parseur MCP with Autogen

This guide walks you through connecting Parseur to AutoGen using the Composio tool router. By the end, you'll have a working Parseur agent that can list all documents in your invoices mailbox, create a webhook to send parsed receipts, pause the outgoing webhook for orders mailbox through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Parseur account through Composio's Parseur MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

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Parseur is an AI-powered data extraction platform that parses emails, PDFs, and documents into structured data. Automate tedious data entry and get actionable information, fast.

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Introduction

This guide walks you through connecting Parseur to AutoGen using the Composio tool router. By the end, you'll have a working Parseur agent that can list all documents in your invoices mailbox, create a webhook to send parsed receipts, pause the outgoing webhook for orders mailbox through natural language commands.

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

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

Also integrate Parseur with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAI

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the required dependencies for Autogen and Composio
  • Initialize Composio and create a Tool Router session for Parseur
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Parseur tools
  • Run a live chat loop where you ask the agent to perform Parseur operations

What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.

Key features include:

  • Multi-Agent Systems: Build collaborative agent workflows
  • MCP Workbench: Native support for Model Context Protocol tools
  • Streaming HTTP: Connect to external services through streamable HTTP
  • AssistantAgent: Pre-built agent class for tool-using assistants

What is the Parseur MCP server, and what's possible with it?

The Parseur MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Parseur account. It provides structured and secure access to your Parseur data extraction workflows, so your agent can perform actions like managing mailboxes, handling documents, configuring webhooks, and automating template operations on your behalf.

  • Mailbox management and discovery: Let your agent list, browse, and filter all Parseur mailboxes to keep tabs on your parsing operations and document streams.
  • Document listing and retrieval: Effortlessly fetch documents from specific mailboxes, enabling automated sorting, searching, or pagination of your parsed files.
  • Template and parsing rule automation: Ask your agent to list templates within any mailbox, so you can quickly inspect or update parsing rules as your data extraction needs evolve.
  • Webhook configuration and control: Enable your agent to create, update, pause, enable, or delete webhooks, making it easy to automate real-time data delivery to your other systems.
  • Comprehensive webhook inspection: Retrieve detailed webhook information or list all webhooks for a mailbox, ensuring you always know how and where your parsed data is flowing.

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

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A Parseur account you can connect to Composio
  • Some basic familiarity with Autogen and Python async
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 python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools

Install Composio, Autogen extensions, and dotenv.

What's happening:

  • composio connects your agent to Parseur via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

4

Set up environment variables

bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com

Create a .env file in your project folder.

What's happening:

  • COMPOSIO_API_KEY is required to talk to Composio
  • OPENAI_API_KEY is used by Autogen's OpenAI client
  • USER_ID is how Composio identifies which user's Parseur connections to use
5

Import dependencies and create Tool Router session

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Parseur session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["parseur"]
    )
    url = session.mcp.url
What's happening:
  • load_dotenv() reads your .env file
  • Composio(api_key=...) initializes the SDK
  • create(...) creates a Tool Router session that exposes Parseur tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to
6

Configure MCP parameters for Autogen

python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.

What's happening:

  • url points to the Tool Router MCP endpoint from Composio
  • timeout is the HTTP timeout for requests
  • sse_read_timeout controls how long to wait when streaming responses
  • terminate_on_close=True cleans up the MCP server process when the workbench is closed
7

Create the model client and agent

python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Parseur assistant agent with MCP tools
    agent = AssistantAgent(
        name="parseur_assistant",
        description="An AI assistant that helps with Parseur operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )

What's happening:

  • OpenAIChatCompletionClient wraps the OpenAI model for Autogen
  • McpWorkbench connects the agent to the MCP tools
  • AssistantAgent is configured with the Parseur tools from the workbench
8

Run the interactive chat loop

python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Parseur related question or task to the agent.\n")

# Conversation loop
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")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
What's happening:
  • The script prompts you in a loop with You:
  • Autogen passes your input to the model, which decides which Parseur tools to call via MCP
  • agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
  • Typing exit, quit, or bye ends the loop

Complete Code

Here's the complete code to get you started with Parseur and AutoGen:

python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Parseur session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["parseur"]
    )
    url = session.mcp.url

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Parseur assistant agent with MCP tools
        agent = AssistantAgent(
            name="parseur_assistant",
            description="An AI assistant that helps with Parseur operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

        print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
        print("Ask any Parseur related question or task to the agent.\n")

        # Conversation loop
        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")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

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

Conclusion

You now have an Autogen assistant wired into Parseur through Composio's Tool Router and MCP. From here you can:
  • Add more toolkits to the toolkits list, for example notion or hubspot
  • Refine the agent description to point it at specific workflows
  • Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Parseur, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
TOOLS

Supported Tools

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

Copy Document

Tool to copy a document to another mailbox.

Copy Mailbox

Tool to copy a mailbox (parser) in Parseur.

Create custom download

Tool to create a custom download (export configuration) for a mailbox.

Create mailbox

Tool to create a new mailbox (parser) in Parseur.

Delete custom download

Tool to delete a custom download (export configuration) from a mailbox.

Delete document

Tool to delete a specific document by ID.

Delete mailbox

Tool to delete a mailbox (parser) by ID.

Delete webhook

Tool to delete a specific webhook.

Disable webhook

Tool to disable a webhook for a mailbox.

Enable webhook

Enables a paused webhook for a specified mailbox, allowing it to receive and forward parsed document events.

Get Bootstrap Config

Tool to retrieve bootstrap configuration data.

Get Document

Tool to retrieve full details of a specific document by ID.

Get Document Logs

Tool to get document logs for a specific document.

Get Mailbox by ID

Tool to retrieve full mailbox (parser) configuration by ID.

Get Mailbox Schema

Tool to retrieve the JSON schema for a mailbox's parsed fields.

List Custom Downloads

Tool to retrieve custom downloads (export configurations) for a mailbox.

List Documents in Mailbox

Tool to list documents within a specific mailbox.

List Mailboxes (Full Details)

Tool to list mailboxes (parsers) with full configuration details.

List Templates for Mailbox

Tool to list all templates in a given mailbox.

Reprocess a document

Tool to reprocess a document.

Retrieve a webhook

Tool to retrieve details of a specific webhook.

Skip a document

Tool to skip a document.

Update custom download

Tool to update a custom download (export configuration) for a mailbox.

Update Mailbox

Tool to update a mailbox (parser) configuration.

Update webhook

Tool to update an existing webhook’s settings.

Upload Email Document

Tool to upload an email or text document to Parseur for parsing.

FRAMEWORKS

How to build Parseur MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Parseur MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Parseur MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Parseur MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Parseur MCP with Claude Cowork

Codex logo

Codex

Use Parseur MCP with Codex

OpenClaw logo

OpenClaw

Use Parseur MCP with OpenClaw

Hermes logo

Hermes

Use Parseur MCP with Hermes

CLI logo

CLI

Use Parseur MCP with CLI

Google ADK logo

Google ADK

Use Parseur MCP with Google ADK

LangChain logo

LangChain

Use Parseur MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Parseur MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Parseur MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Parseur MCP with LlamaIndex

CrewAI logo

CrewAI

Use Parseur MCP with CrewAI

FAQ

Frequently asked questions

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

Yes, you can. Autogen 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 Parseur tools.

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

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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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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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