SIGN UPLOG IN
X (Twitter)LinkedInGitHubDiscordYouTube

How to integrate Fibery MCP with Autogen

Connect Autogen to Fibery MCP. List all open tasks for your team, fetch details for project entity by id, and more using natural language, with authentication handled for you.

Get started for freeGet a demo
Fibery logoFibery
Api Key

Fibery is a collaborative work management platform for organizing projects, documents, and knowledge. It helps teams streamline workflows and centralize information in one space.

23 Tools

Introduction

This guide walks you through connecting Fibery to AutoGen using the Composio tool router. By the end, you'll have a working Fibery agent that can create and update entities, run GraphQL queries, upload files, fetch your workspace schema, and count entities by type through natural language commands.

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

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

Also integrate Fibery with

Claude CodeClaude CoworkOpenAI Agents SDKClaude Agent SDKCodexOpenClawHermesAtomic AgentGoogle ADKLangChainVercel AI SDKMastra AILlamaIndexCrewAIPydantic AI

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 Fibery
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call Fibery tools
  • Run a live chat loop where you ask the agent to perform Fibery 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 Fibery MCP server, and what's possible with it?

The Fibery MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Fibery account. It provides structured and secure access to your workspace data, so your agent can perform actions like querying entities, managing custom apps, running GraphQL queries, and organizing files—all with zero manual integration code.

  • Entity query and retrieval: Instantly fetch detailed information or lists of entities based on type, filters, and fields, making it easy to surface project or task data as needed.
  • Custom app and endpoint management: Let your agent list, inspect, or delete custom apps and endpoints, streamlining workspace configuration and app lifecycle management.
  • Flexible data manipulation with GraphQL: Execute custom GraphQL queries and mutations against your Fibery space to fetch, update, or manipulate structured data programmatically.
  • File and resource cleanup: Remove outdated files or entities efficiently, helping keep your workspace organized and clutter-free with automated deletions.
  • Authentication and workspace insights: Validate tokens securely and retrieve workspace or app metadata, ensuring your agent always operates with up-to-date context and permissions.

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 Fibery 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 Fibery 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 Fibery 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 Fibery session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["fibery"]
    )
    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 Fibery 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 Fibery assistant agent with MCP tools
    agent = AssistantAgent(
        name="fibery_assistant",
        description="An AI assistant that helps with Fibery 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 Fibery 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 Fibery 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 Fibery 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 Fibery 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 Fibery session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["fibery"]
    )
    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 Fibery assistant agent with MCP tools
        agent = AssistantAgent(
            name="fibery_assistant",
            description="An AI assistant that helps with Fibery 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 Fibery 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 Fibery 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 Fibery, you can reuse the same structure for other MCP-enabled apps with minimal code changes.
TOOLS

Supported Tools

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

Delete Custom App Endpoint

Delete a custom app endpoint by app and endpoint IDs.

Delete Entity

Permanently delete a Fibery entity by its UUID and type.

Delete File

Delete a file from Fibery storage using its secret identifier.

Execute GraphQL Query

Execute GraphQL queries or mutations against a Fibery workspace.

Get App Information

Retrieve application information, including version, name, authentication methods and data sources when available.

Get Custom App Endpoints

List custom endpoints for a given Fibery app, for use when selecting an endpoint to invoke.

Get Custom Apps

List Fibery workspace app records and their identifiers, titles, names and versions, subject to a configurable limit that defaults to 100.

Get File

Download a file from Fibery by its secret or ID.

Get GraphQL Schema

Retrieve a Fibery GraphQL introspection response as a string to discover available types, fields and operations before composing queries.

Get User Preferences

Retrieve UI preferences from the first user returned by a Fibery user query.

Refresh access token

Check Fibery access credentials and return token information.

Validate Fibery authentication and get access token

Request an access token using an OAuth2 password grant or check the configured Fibery authorization.

Create Entity

Tool to create a new Fibery entity.

Count Entities by Type

Request a count of entities for a specified Fibery type or database, such as users or features.

Fetch Datalist Options

Fetch a page of options for a field of a Fibery entity type for uses such as filtering or dropdowns.

Fetch Schema

Fetch the complete schema metadata for a Fibery workspace.

Exchange OAuth2 authorization code

Request an OAuth2 authorization-code exchange for a Fibery custom integration, using the authorization code and redirect URI.

Delete/Revoke Access Token

Delete/revoke an existing Fibery API access token by its ID.

Validate Fibery Workspace Credentials

Test Fibery workspace credentials with a user query, supporting workspace tokens, API keys, basic auth and OAuth2.

Validate Filter

Check a filter definition for a Fibery data source before using it in a query.

Update Entity

Update fields on a Fibery entity of a specified type, including text, numbers, states and relations.

Update User Preferences

Update UI preferences for the first Fibery user returned by a workspace query.

Upload File

Upload a file to Fibery storage for later attachment to entities or use in documents.

FRAMEWORKS

How to build Fibery MCP Agent with another framework

Claude Code logo

Claude Code

Use Fibery MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Fibery MCP with Claude Cowork

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Fibery MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Fibery MCP with Claude Agent SDK

Codex logo

Codex

Use Fibery MCP with Codex

OpenClaw logo

OpenClaw

Use Fibery MCP with OpenClaw

Hermes logo

Hermes

Use Fibery MCP with Hermes

Atomic Agent logo

Atomic Agent

Use Fibery MCP with Atomic Agent

Google ADK logo

Google ADK

Use Fibery MCP with Google ADK

LangChain logo

LangChain

Use Fibery MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Fibery MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Fibery MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Fibery MCP with LlamaIndex

CrewAI logo

CrewAI

Use Fibery MCP with CrewAI

Pydantic AI logo

Pydantic AI

Use Fibery MCP with Pydantic AI

FAQ

Frequently asked questions

Start with Fibery.It takes 30 seconds.

Managed auth, hosted MCP servers, and every Fibery tool your agent needs.Free to start.

Start building