Circleci with Pydantic AI

How to integrate Circleci MCP with Pydantic AI

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Introduction Also integrate Circleci with TL;DR What is Pydantic AI What is the Circleci MCP server Supported Tools & Triggers Creating MCP Server - Stand-alone vs Composio SDK Step-by-step Guide Complete Code Conclusion How to build Circleci MCP Agent with another framework Explore Other Toolkits FAQ

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Introduction

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

OpenAI Agents SDK Claude Agent SDK Claude Code Claude Cowork Codex OpenClaw Hermes CLI Google ADK LangChain Vercel AI SDK Mastra AI LlamaIndex CrewAI

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 Circleci
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 Circleci 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 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.

Supported Tools & Triggers

Tools

Create ContextTool to create a new context in CircleCI.

Create Context (GraphQL)Tool to create a new CircleCI context using the GraphQL API.

Create Context RestrictionTool to create a context restriction in CircleCI.

Create Organization Orb AllowlistTool to create a new URL Orb allow-list entry for an organization.

Create Organization ProjectTool to create a new project within a CircleCI organization.

Create Organization GroupTool to create a group in an organization.

Create Project Environment VariableTool to create a new environment variable for a CircleCI project.

Create Usage Export JobTool 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 RestrictionTool to delete a context restriction by its ID.

Delete Namespace and Related OrbsTool to delete a CircleCI registry namespace and all its associated orbs.

Delete Namespace AliasTool to remove a namespace alias by name in CircleCI.

Delete Organization Orb Allowlist EntryTool to remove an entry from the organization's URL orb allow-list.

Delete Organization GroupTool to delete a group from a CircleCI organization.

Delete ProjectTool to delete a CircleCI project and its settings.

Delete Project Environment VariableTool to delete an environment variable from a CircleCI project.

Get ContextTool to retrieve a context by its unique ID.

Get Current UserTool to retrieve information about the currently authenticated user.

Get Flaky TestsTool to get flaky tests for a project.

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

Get Job DetailsTool to fetch details of a specific job within a project.

Get Orb DetailsTool to query detailed information about a CircleCI orb using the GraphQL API.

Get Orb VersionTool to retrieve detailed information about a specific CircleCI orb version via GraphQL.

Get OrganizationTool to retrieve organization details from CircleCI using GraphQL query.

Get Organization GroupTool to retrieve a group in an organization.

Get Pipeline ConfigTool to fetch pipeline configuration by ID.

Get Pipeline DefinitionTool to retrieve a pipeline definition by project and definition ID.

Get ProjectTool to retrieve a CircleCI project by its slug.

Get Project WorkflowsTool to get summary metrics for all workflows of a project.

Get Test MetadataTool to fetch test metadata for a specific job.

Get Usage Export JobTool to retrieve a usage export job by organization ID and job ID.

Get User InformationTool to retrieve information about a CircleCI user by their unique ID.

Get Workflow SummaryTool to get metrics and trends for a workflow.

List Context Environment VariablesTool to list all environment variables for a specific context.

List Insights BranchesTool to get all branches for a project from CircleCI Insights.

List Insights SummaryTool to get summary metrics with trends for the entire organization and for each project.

List Namespace OrbsTool to list orbs in a CircleCI registry namespace with pagination support.

List Orb CategoriesTool to retrieve all CircleCI orb categories with pagination support.

List OrbsTool to list CircleCI orbs with pagination support via GraphQL API.

List Organization GroupsTool to list all groups in a CircleCI organization.

List Pages SummaryTool to get summary metrics and trends for a project across its workflows and branches.

List Pipeline DefinitionsTool to list all pipeline definitions for a specific project.

List PipelinesTool to get a list of pipelines for an organization.

List Pipelines for ProjectTool to list all pipelines for a specific project.

List Project Environment VariablesTool to list all environment variables for a CircleCI project.

List Project SchedulesTool to list all schedules for a specific project.

List Self-Hosted RunnersList self-hosted runners in CircleCI.

List User CollaborationsTool to retrieve organizations where the authenticated user has access.

List Workflows by Pipeline IDTool to list all workflows associated with a specific pipeline.

List Workflows Jobs WorkflowsTool to get summary metrics for a project workflow's jobs.

List Workflows Test MetricsTool to get test metrics for a project's workflows.

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

Query Namespace ExistsTool to determine if a namespace exists in the CircleCI registry.

Query Orb Category IDTool to fetch the unique category ID for a CircleCI orb category by its name.

Query Orb ExistsTool to check if an orb exists in CircleCI registry and retrieve its privacy status.

Query Orb IDTool to fetch an orb's ID and optionally its namespace ID by orb name.

Query Orb Latest VersionTool to fetch the latest published version of a CircleCI orb.

Query Orb SourceTool to retrieve source code of a specific CircleCI orb version via GraphQL.

Query Plan MetricsTool 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 NamespaceTool to rename a CircleCI namespace by its UUID identifier.

Store Environment VariableTool to store an environment variable in a CircleCI context using GraphQL mutation.

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

Upsert Context Environment VariableTool to add or update an environment variable in a CircleCI context.

Validate Orb ConfigTool to validate CircleCI orb YAML configuration using the orbConfig GraphQL query.

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:

Discovery: Searches for tools matching your task and returns relevant toolkits with their details.
Authentication: Checks for active connections. If missing, creates an auth config and returns a connection URL via Auth Link.
Execution: Executes the action using the authenticated connection.

Step-by-step Guide

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

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.

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 Circleci
pydantic-ai lets you create structured AI agents with tool support
python-dotenv loads your environment variables securely from a .env file

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

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 Circleci
MCPServerStreamableHTTP connects to the Circleci MCP server endpoint
Agent from Pydantic AI lets you define and run the AI assistant

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 Circleci
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["circleci"],
    )
    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 Circleci 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

Initialize the Pydantic AI Agent

python

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

What's happening:

The MCP client connects to the Circleci endpoint
The agent uses GPT-5 to interpret user commands and perform Circleci operations
The instructions field defines the agent's role and behavior

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 Circleci.\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
Circleci API calls happen automatically under the hood
The model keeps conversation history to maintain context across turns

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 Circleci 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 Circleci
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["circleci"],
    )
    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
    circleci_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[circleci_mcp],
        instructions=(
            "You are a Circleci assistant. Use Circleci 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 Circleci.\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 Circleci through Composio's Tool Router. With this setup, your agent can perform real Circleci 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 + Circleci for workflow automation)

This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.

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TOOLKIT MARKETPLACE

FAQ

What are the differences in Tool Router MCP and Circleci MCP?

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.

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 Circleci tools.

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

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.

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 Circleci data and credentials are handled as safely as possible.

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Harsha GaddipatiCo-founder, Slashy

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

Abhi AryaCo-founder, Opennote

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 has immensely helped in keeping new users on the platform.

Nirman DaveCEO, Zams

We chose Composio over Pipedream because it delivered depth where it mattered. It supported niche tools and tricky edge cases that other platforms simply ignored. Giving us confidence to scale without compromising.

Ryan YuFounder, Extra Thursday

As a solo builder, shipping fast is life or death. The only way I can outcompete incumbents is by outmanoeuvring them. Getting bogged down in the complexities of managing agent auth would have been a death sentence for Extra Thursday.

Tomisin JenrolaFounder & CEO, SwarmZero

Before partnering with Composio, adding tool integrations was a slow, resource-intensive process. Each integration could take weeks or months of engineering time, and maintaining them meant constantly keeping up with API changes.

Jerome LeclancheCo-Founder, Ingram Technologies

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.

Harsha GaddipatiCo-founder, Slashy

Abhi AryaCo-founder, Opennote

Nirman DaveCEO, Zams

Ryan YuFounder, Extra Thursday

Tomisin JenrolaFounder & CEO, SwarmZero

Jerome LeclancheCo-Founder, Ingram Technologies

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.

Harsha GaddipatiCo-founder, Slashy

Abhi AryaCo-founder, Opennote

Nirman DaveCEO, Zams

Ryan YuFounder, Extra Thursday

Tomisin JenrolaFounder & CEO, SwarmZero

Jerome LeclancheCo-Founder, Ingram Technologies

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.

How to integrate Circleci MCP with Pydantic AI

Table of Contents

Connect Circleci without Auth hassles

Introduction

Also integrate Circleci with

TL;DR

What is Pydantic AI?

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

Supported Tools & Triggers

What is the Composio tool router, and how does it fit here?

What is Composio SDK?

How the Composio SDK works

Step-by-step Guide

Prerequisites

Getting API Keys for OpenAI and Composio

Install dependencies

Set up environment variables

Import dependencies

Create a Tool Router Session

Initialize the Pydantic AI Agent

Build the chat interface

Run the application

Complete Code

Conclusion

How to build Circleci MCP Agent with another framework

OpenAI Agents SDK

Claude Agent SDK

Claude Code

Claude Cowork

Codex

OpenClaw

Hermes

CLI

Google ADK

LangChain

Vercel AI SDK

Mastra AI

LlamaIndex

CrewAI

Explore Other Toolkits

Supabase

Codeinterpreter

GitHub

FAQ

What are the differences in Tool Router MCP and Circleci MCP?

Can I use Tool Router MCP with Pydantic AI?

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

How safe is my data with Composio Tool Router?

Used by agents from

Never worry about agent reliability