How to integrate Circleci MCP with Autogen

This guide walks you through connecting Circleci to AutoGen using the Composio tool router. By the end, you'll have a working Circleci agent that can trigger a new pipeline on main branch, list all pipelines for backend service, get test results from last successful build through natural language commands. This guide will help you understand how to give your AutoGen agent real control over a Circleci account through Composio's Circleci MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

Circleci logoCircleci
Api Key

Circleci is a leading continuous integration and delivery platform for automating code builds, tests, and deployments. It helps teams ship quality software faster by streamlining DevOps workflows.

65 Tools

Introduction

This guide walks you through connecting Circleci to AutoGen using the Composio tool router. By the end, you'll have a working Circleci agent that can trigger a new pipeline on main branch, list all pipelines for backend service, get test results from last successful build through natural language commands.

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

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

Also integrate Circleci with

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

The Circleci MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Circleci account. It provides structured and secure access to your Circleci projects and pipelines, so your agent can trigger builds, fetch job artifacts, monitor workflows, and analyze test results on your behalf.

  • Automated pipeline triggering and management: Let your agent start new builds for specific branches or tags, enabling continuous integration workflows without manual intervention.
  • Workflow and job status monitoring: Ask your agent to fetch detailed information about jobs and workflows, including status, timing, and execution environment, to stay on top of your CI/CD processes.
  • Artifact and test result retrieval: Have the agent collect job artifacts or extract comprehensive test metadata and failure messages for easier debugging and reporting.
  • Pipeline and runner insights: Get your agent to list all pipelines for a project or enumerate available self-hosted runners, making it simple to manage and audit your Circleci resources.
  • User and configuration access: Retrieve user profile details or fetch pipeline YAML configurations as needed for documentation, troubleshooting, or workflow optimization.

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

Supported Tools

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

Create Context

Tool to create a new context in CircleCI.

Create Context (GraphQL)

Tool to create a new CircleCI context using the GraphQL API.

Create Context Restriction

Tool to create a context restriction in CircleCI.

Create Organization Orb Allowlist

Tool to create a new URL Orb allow-list entry for an organization.

Create Organization Project

Tool to create a new project within a CircleCI organization.

Create Organization Group

Tool to create a group in an organization.

Create Project Environment Variable

Tool to create a new environment variable for a CircleCI project.

Create Usage Export Job

Tool to create a usage export job for a CircleCI organization.

Delete Context (GraphQL)

Tool to delete a CircleCI context by its UUID using GraphQL API.

Delete Context Restriction

Tool to delete a context restriction by its ID.

Delete Namespace and Related Orbs

Tool to delete a CircleCI registry namespace and all its associated orbs.

Delete Namespace Alias

Tool to remove a namespace alias by name in CircleCI.

Delete Organization Orb Allowlist Entry

Tool to remove an entry from the organization's URL orb allow-list.

Delete Organization Group

Tool to delete a group from a CircleCI organization.

Delete Project

Tool to delete a CircleCI project and its settings.

Delete Project Environment Variable

Tool to delete an environment variable from a CircleCI project.

Get Context

Tool to retrieve a context by its unique ID.

Get Current User

Tool to retrieve information about the currently authenticated user.

Get Flaky Tests

Tool to get flaky tests for a project.

Get Job Artifacts

Retrieves artifacts (output files like test results, logs, build binaries, reports) produced by a CircleCI job.

Get Job Details

Tool to fetch details of a specific job within a project.

Get Orb Details

Tool to query detailed information about a CircleCI orb using the GraphQL API.

Get Orb Version

Tool to retrieve detailed information about a specific CircleCI orb version via GraphQL.

Get Organization

Tool to retrieve organization details from CircleCI using GraphQL query.

Get Organization Group

Tool to retrieve a group in an organization.

Get Pipeline Config

Tool to fetch pipeline configuration by ID.

Get Pipeline Definition

Tool to retrieve a pipeline definition by project and definition ID.

Get Project

Tool to retrieve a CircleCI project by its slug.

Get Project Workflows

Tool to get summary metrics for all workflows of a project.

Get Test Metadata

Tool to fetch test metadata for a specific job.

Get Usage Export Job

Tool to retrieve a usage export job by organization ID and job ID.

Get User Information

Tool to retrieve information about a CircleCI user by their unique ID.

Get Workflow Summary

Tool to get metrics and trends for a workflow.

List Context Environment Variables

Tool to list all environment variables for a specific context.

List Insights Branches

Tool to get all branches for a project from CircleCI Insights.

List Insights Summary

Tool to get summary metrics with trends for the entire organization and for each project.

List Namespace Orbs

Tool to list orbs in a CircleCI registry namespace with pagination support.

List Orb Categories

Tool to retrieve all CircleCI orb categories with pagination support.

List Orbs

Tool to list CircleCI orbs with pagination support via GraphQL API.

List Organization Groups

Tool to list all groups in a CircleCI organization.

List Pages Summary

Tool to get summary metrics and trends for a project across its workflows and branches.

List Pipeline Definitions

Tool to list all pipeline definitions for a specific project.

List Pipelines

Tool to get a list of pipelines for an organization.

List Pipelines for Project

Tool to list all pipelines for a specific project.

List Project Environment Variables

Tool to list all environment variables for a CircleCI project.

List Project Schedules

Tool to list all schedules for a specific project.

List Self-Hosted Runners

List self-hosted runners in CircleCI.

List User Collaborations

Tool to retrieve organizations where the authenticated user has access.

List Workflows by Pipeline ID

Tool to list all workflows associated with a specific pipeline.

List Workflows Jobs Workflows

Tool to get summary metrics for a project workflow's jobs.

List Workflows Test Metrics

Tool to get test metrics for a project's workflows.

Query Context

Tool to retrieve a CircleCI context by its UUID using GraphQL API.

Query Namespace Exists

Tool to determine if a namespace exists in the CircleCI registry.

Query Orb Category ID

Tool to fetch the unique category ID for a CircleCI orb category by its name.

Query Orb Exists

Tool to check if an orb exists in CircleCI registry and retrieve its privacy status.

Query Orb ID

Tool to fetch an orb's ID and optionally its namespace ID by orb name.

Query Orb Latest Version

Tool to fetch the latest published version of a CircleCI orb.

Query Orb Source

Tool to retrieve source code of a specific CircleCI orb version via GraphQL.

Query Plan Metrics

Tool to query plan metrics including credit usage by project and organization for a date range.

Remove Context Environment Variable (GraphQL)

Tool to remove an environment variable from a CircleCI context using GraphQL API.

Rename Namespace

Tool to rename a CircleCI namespace by its UUID identifier.

Store Environment Variable

Tool to store an environment variable in a CircleCI context using GraphQL mutation.

Trigger Pipeline

Triggers a new CI/CD pipeline run for a specified CircleCI project.

Upsert Context Environment Variable

Tool to add or update an environment variable in a CircleCI context.

Validate Orb Config

Tool to validate CircleCI orb YAML configuration using the orbConfig GraphQL query.

FAQ

Frequently asked questions

With a standalone Circleci MCP server, the agents and LLMs can only access a fixed set of Circleci tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Circleci 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 Circleci tools.

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

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