How to integrate Ashby MCP with Pydantic AI

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Introduction

This guide walks you through connecting Ashby to Pydantic AI using the Composio tool router. By the end, you'll have a working Ashby agent that can list all candidates for open roles, post a new job opening for engineering, summarize candidates in interview stage, export recent hiring activity to csv through natural language commands.

This guide will help you understand how to give your Pydantic AI agent real control over a Ashby account through Composio's Ashby 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:
  • How to set up your Composio API key and User ID
  • How to create a Composio Tool Router session for Ashby
  • 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 Ashby 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 Ashby MCP server, and what's possible with it?

The Ashby MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Ashby account. It provides structured and secure access to your recruiting data, so your agent can perform actions like managing job postings, tracking candidate progress, scheduling interviews, and generating hiring reports on your behalf.

  • Automated job posting management: Easily create, update, or close job listings across your organization with direct agent assistance.
  • Candidate pipeline tracking: Have your agent fetch, organize, and update candidate progress through every stage of the hiring process.
  • Interview scheduling and coordination: Let your agent schedule interviews, send calendar invites, and manage interviewer assignments to streamline the process.
  • Data-driven hiring analytics: Generate reports and insights about your hiring funnel, candidate sources, and time-to-hire with a simple agent request.
  • Centralized communication with applicants: Enable your agent to send status updates, feedback, or reminders to candidates, keeping everyone in the loop automatically.

Supported Tools & Triggers

Tools
Add Candidate TagAdd a tag to a candidate.
Change Application SourceChange the source attribution of an application.
Change Application StageMove an application to a different interview stage.
Create ApplicationCreate a new application for a candidate to a specific job.
Create CandidateCreate a new candidate in the system.
Create Candidate TagCreate a new candidate tag.
Create DepartmentCreate a new department.
Create JobCreate a new job opening.
Get API Key InfoRetrieve information about the current API key, including associated organization, user details, and permissions.
Get Application InfoRetrieve detailed information about a specific application by its ID.
Get Candidate InfoRetrieve detailed information about a specific candidate by their ID.
Get Department InfoRetrieve detailed information about a specific department by its ID.
Get Interview InfoRetrieve detailed information about a specific interview type by its ID.
Get Job InfoRetrieve detailed information about a specific job by its ID.
Get Job Posting InfoRetrieve detailed information about a specific job posting by its ID.
Get Location InfoRetrieve detailed information about a specific location by its ID.
Get Opening InfoRetrieve detailed information about a specific opening (job requisition) by its ID.
Get User InfoRetrieve detailed information about a specific user by their ID.
List Application FeedbackRetrieve all feedback submissions for an application.
List Application HistoryRetrieve the complete history of stage transitions for an application.
List ApplicationsRetrieve a list of applications.
List ApprovalsRetrieve a list of approvals (offer approvals, job approvals, etc.
List Archive ReasonsRetrieve a list of all archive reasons.
List Candidate NotesRetrieve all notes for a specific candidate.
List Candidate ProjectsRetrieve all projects associated with a candidate.
List CandidatesRetrieve a list of candidates.
List Candidate TagsRetrieve a list of all candidate tags.
List Close ReasonsRetrieve a list of all close reasons for jobs and openings.
List Communication TemplatesRetrieve a list of all communication templates.
List Custom FieldsRetrieve a list of all custom field definitions.
List DepartmentsRetrieve a list of all departments in the organization.
List Feedback Form DefinitionsRetrieve a list of all feedback form definitions.
List Interviewer PoolsRetrieve a list of all interviewer pools.
List Interview PlansRetrieve a list of interview plans.
List InterviewsRetrieve a list of interviews.
List Interview SchedulesRetrieve a list of interview schedules.
List Interview Stage GroupsRetrieve a list of interview stage groups.
List Job BoardsRetrieve a list of job boards.
List Job PostingsRetrieve a list of job postings.
List JobsRetrieve a list of jobs.
List Job TemplatesRetrieve a list of job templates.
List LocationsRetrieve a list of all locations.
List OffersRetrieve a list of job offers.
List OpeningsRetrieve a list of openings (job requisitions).
List ProjectsRetrieve a list of all projects.
List SourcesRetrieve a list of all candidate sources.
List Source Tracking LinksRetrieve a list of all source tracking links.
List Survey Form DefinitionsRetrieve a list of all survey form definitions.
List UsersRetrieve a list of all users in the organization.
Search CandidatesSearch for candidates by email or name.
Search JobsSearch for jobs by title.
Search ProjectsSearch for projects by title.
Search UsersSearch for users by email or name.
Set Job StatusSet the status of a job (Open, Closed, Draft).
Update ApplicationUpdate custom fields or other properties of an application.
Update CandidateUpdate candidate information such as name, position, company, or school.
Update DepartmentUpdate department information such as name.
Update JobUpdate job details such as title and other properties.
Update Job PostingUpdate job posting details such as title or listing status.

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:
  • 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 Ashby
  • 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 Ashby
  • MCPServerStreamableHTTP connects to the Ashby 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 Ashby
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["ashby"],
    )
    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 Ashby 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
ashby_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[ashby_mcp],
    instructions=(
        "You are a Ashby assistant. Use Ashby tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Ashby endpoint
  • The agent uses GPT-5 to interpret user commands and perform Ashby 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 Ashby.\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
  • Ashby 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 Ashby 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 Ashby
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["ashby"],
    )
    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
    ashby_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[ashby_mcp],
        instructions=(
            "You are a Ashby assistant. Use Ashby 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 Ashby.\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 Ashby through Composio's Tool Router. With this setup, your agent can perform real Ashby 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 + Ashby for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.

How to build Ashby MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

Use Ashby MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Ashby MCP with Claude Agent SDK

Google ADK

Google ADK

Use Ashby MCP with Google ADK

LangChain

LangChain

Use Ashby MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Ashby MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Ashby MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Ashby MCP with LlamaIndex

CrewAI

CrewAI

Use Ashby MCP with CrewAI

FAQ

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

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

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

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

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