How to integrate Bugherd MCP with OpenAI Agents SDK

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Introduction

This guide walks you through connecting Bugherd to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Bugherd agent that can list all active bugherd projects, create a new project for website feedback, add a comment to task by id, invite a guest client to a project through natural language commands.

This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Bugherd account through Composio's Bugherd MCP server.

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

TL;DR

Here's what you'll learn:
  • Get and set up your OpenAI and Composio API keys
  • Install the necessary dependencies
  • Initialize Composio and create a Tool Router session for Bugherd
  • Configure an AI agent that can use Bugherd as a tool
  • Run a live chat session where you can ask the agent to perform Bugherd operations

What is open-ai-agents-sdk?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.

Key features include:

  • Hosted MCP Tools: Connect to external services through hosted MCP endpoints
  • SQLite Sessions: Persist conversation history across interactions
  • Simple API: Clean interface with Agent, Runner, and tool configuration
  • Streaming Support: Real-time response streaming for interactive applications

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

The Bugherd MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Bugherd account. It provides structured and secure access to your Bugherd workspace, so your agent can perform actions like creating tasks, managing projects, posting comments, and inviting team members—all on your behalf.

  • Visual bug reporting and task creation: Instantly add new tasks to any project, capturing detailed bug reports or website feedback directly from your team or clients.
  • Project management and workflow customization: Create new projects, add workflow columns, and delete projects when they’re no longer needed to keep your bug tracking organized and up-to-date.
  • Collaboration and discussion: Add comments to tasks, attach files, and keep all stakeholders in the loop with contextual feedback and documentation.
  • Team and guest access management: Seamlessly invite members or guests to projects so the right people can track, manage, and resolve issues together.
  • Webhook automation and notifications: Set up webhooks to receive real-time notifications for events like task creation or new comments, helping you automate downstream workflows.

Supported Tools & Triggers

Tools
Add Guest to ProjectTool to add a guest (client) to a project.
Add Member to ProjectTool to add a member to a project in bugherd.
Create AttachmentTool to add a new attachment to a task using an existing url.
Create ColumnTool to create a new column in a project.
Create CommentTool to add a new comment to a task.
Create ProjectTool to create a new project.
Create TaskTool to add a new task in a project.
Create WebhookTool to create a new webhook for real-time event notifications.
Delete ProjectTool to delete a project.
List Active ProjectsTool to list all active projects in your bugherd account.
List AttachmentsTool to list all attachments for a task.
List ColumnsTool to list all columns for a project.
List ProjectsTool to list all projects in your account.
List UsersTool to list all users in your account.
List WebhooksTool to list all installed webhooks.
Show AttachmentTool to retrieve details of a specific attachment.
Show ColumnTool to show details of a specific column.
Show OrganizationTool to retrieve your bugherd organization details.
Show ProjectTool to show details for a specific project.
Show User ProjectsTool to list all projects a specific user has access to.
Show User TasksTool to list tasks created or assigned to a specific user.
Update ColumnTool to update a column in a project.
Update ProjectTool to update settings for an existing project.
Update TaskTool to update a task in a project.
Upload AttachmentTool to upload a new attachment and add it to a specific task.

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

What is Tool Router?

Composio's Tool Router 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 Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router 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

Prerequisites

Before starting, make sure you have:
  • Composio API Key and OpenAI API Key
  • Primary know-how of OpenAI Agents SDK
  • A live Bugherd project
  • Some knowledge of Python or Typescript

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

Install dependencies

pip install composio_openai_agents openai-agents python-dotenv

Install the Composio SDK and the OpenAI Agents SDK.

Set up environment variables

bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com

Create a .env file and add your OpenAI and Composio API keys.

Import dependencies

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
What's happening:
  • You're importing all necessary libraries.
  • The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Bugherd.

Set up the Composio instance

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
What's happening:
  • load_dotenv() loads your .env file so OPENAI_API_KEY and COMPOSIO_API_KEY are available as environment variables.
  • Creating a Composio instance using the API Key and OpenAIAgentsProvider class.

Create a Tool Router session

# Create a Bugherd Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["bugherd"]
)

mcp_url = session.mcp.url

What is happening:

  • You give the Tool Router the user id and the toolkits you want available. Here, it is only bugherd.
  • The router checks the user's Bugherd connection and prepares the MCP endpoint.
  • The returned session.mcp.url is the MCP URL that your agent will use to access Bugherd.
  • This approach keeps things lightweight and lets the agent request Bugherd tools only when needed during the conversation.

Configure the agent

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Bugherd. "
        "Help users perform Bugherd operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
What's happening:
  • We're creating an Agent instance with a name, model (gpt-5), and clear instructions about its purpose.
  • The agent's instructions tell it that it can access Bugherd and help with queries, inserts, updates, authentication, and fetching database information.
  • The tools array includes a HostedMCPTool that connects to the MCP server URL we created earlier.
  • The headers dict includes the Composio API key for secure authentication with the MCP server.
  • require_approval: 'never' means the agent can execute Bugherd operations without asking for permission each time, making interactions smoother.

Start chat loop and handle conversation

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
What's happening:
  • The program prints a session URL that you visit to authorize Bugherd.
  • After authorization, the chat begins.
  • Each message you type is processed by the agent using Runner.run().
  • The responses are printed to the console, and conversations are saved locally using SQLite.
  • Typing exit, quit, or q cleanly ends the chat.

Complete Code

Here's the complete code to get you started with Bugherd and open-ai-agents-sdk:

import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["bugherd"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Bugherd. "
        "Help users perform Bugherd operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())

Conclusion

This was a starter code for integrating Bugherd MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Bugherd.

Key features:

  • Hosted MCP tool integration through Composio's Tool Router
  • SQLite session persistence for conversation history
  • Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

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FAQ

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

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

Can I use Tool Router MCP with OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK 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 Bugherd tools.

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

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

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