How to integrate Ashby MCP with CrewAI

This guide walks you through connecting Ashby to CrewAI 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 through natural language commands. This guide will help you understand how to give your CrewAI 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.

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Ashby is an applicant tracking system that handles job postings, candidate management, and hiring analytics.

125 Tools

Introduction

This guide walks you through connecting Ashby to CrewAI 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 through natural language commands.

This guide will help you understand how to give your CrewAI 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.

Also integrate Ashby with

OpenAI Agents SDKClaude Agent SDKClaude CodeClaude CoworkCodexOpenClawHermesCLIGoogle ADKLangChainVercel AI SDKMastra AILlamaIndex

TL;DR

Here's what you'll learn:
  • Get a Composio API key and configure your Ashby connection
  • Set up CrewAI with an MCP enabled agent
  • Create a Tool Router session or standalone MCP server for Ashby
  • Build a conversational loop where your agent can execute Ashby operations

What is CrewAI?

CrewAI is a powerful framework for building multi-agent AI systems. It provides primitives for defining agents with specific roles, creating tasks, and orchestrating workflows through crews.

Key features include:

  • Agent Roles: Define specialized agents with specific goals and backstories
  • Task Management: Create tasks with clear descriptions and expected outputs
  • Crew Orchestration: Combine agents and tasks into collaborative workflows
  • MCP Integration: Connect to external tools through Model Context Protocol

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.

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

Before starting, make sure you have:
  • Python 3.9 or higher
  • A Composio account and API key
  • A Ashby connection authorized in Composio
  • An OpenAI API key for the CrewAI LLM
  • Basic familiarity with Python
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 crewai crewai-tools[mcp] python-dotenv
What's happening:
  • composio connects your agent to Ashby via MCP
  • crewai provides Agent, Task, Crew, and LLM primitives
  • crewai-tools[mcp] includes MCP helpers
  • python-dotenv loads environment variables from .env
4

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_here

Create a .env file in your project root.

What's happening:

  • COMPOSIO_API_KEY authenticates with Composio
  • USER_ID scopes the session to your account
  • OPENAI_API_KEY lets CrewAI use your chosen OpenAI model
5

Import dependencies

python
import os
from composio import Composio
from crewai import Agent, Task, Crew
from crewai_tools import MCPServerAdapter
import dotenv

dotenv.load_dotenv()

COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set")
What's happening:
  • CrewAI classes define agents and tasks, and run the workflow
  • MCPServerHTTP connects the agent to an MCP endpoint
  • Composio will give you a short lived Ashby MCP URL
6

Create a Composio Tool Router session for Ashby

python
composio_client = Composio(api_key=COMPOSIO_API_KEY)
session = composio_client.create(user_id=COMPOSIO_USER_ID, toolkits=["ashby"])

url = session.mcp.url
What's happening:
  • You create a Ashby only session through Composio
  • Composio returns an MCP HTTP URL that exposes Ashby tools
7

Initialize the MCP Server

python
server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users search the internet effectively",
        backstory="You are a helpful assistant with access to search tools.",
        tools=tools,
        verbose=False,
        max_iter=10,
    )
What's Happening:
  • Server Configuration: The code sets up connection parameters including the MCP server URL, streamable HTTP transport, and Composio API key authentication.
  • MCP Adapter Bridge: MCPServerAdapter acts as a context manager that converts Composio MCP tools into a CrewAI-compatible format.
  • Agent Setup: Creates a CrewAI Agent with a defined role (Search Assistant), goal (help with internet searches), and access to the MCP tools.
  • Configuration Options: The agent includes settings like verbose=False for clean output and max_iter=10 to prevent infinite loops.
  • Dynamic Tool Usage: Once created, the agent automatically accesses all Composio Search tools and decides when to use them based on user queries.
8

Create a CLI Chatloop and define the Crew

python
print("Chat started! Type 'exit' or 'quit' to end.\n")

conversation_context = ""

while True:
    user_input = input("You: ").strip()

    if user_input.lower() in ["exit", "quit", "bye"]:
        print("\nGoodbye!")
        break

    if not user_input:
        continue

    conversation_context += f"\nUser: {user_input}\n"
    print("\nAgent is thinking...\n")

    task = Task(
        description=(
            f"Conversation history:\n{conversation_context}\n\n"
            f"Current request: {user_input}"
        ),
        expected_output="A helpful response addressing the user's request",
        agent=agent,
    )

    crew = Crew(agents=[agent], tasks=[task], verbose=False)
    result = crew.kickoff()
    response = str(result)

    conversation_context += f"Agent: {response}\n"
    print(f"Agent: {response}\n")
What's Happening:
  • Interactive CLI Setup: The code creates an infinite loop that continuously prompts for user input and maintains the entire conversation history in a string variable.
  • Input Validation: Empty inputs are ignored to prevent processing blank messages and keep the conversation clean.
  • Context Building: Each user message is appended to the conversation context, which preserves the full dialogue history for better agent responses.
  • Dynamic Task Creation: For every user input, a new Task is created that includes both the full conversation history and the current request as context.
  • Crew Execution: A Crew is instantiated with the agent and task, then kicked off to process the request and generate a response.
  • Response Management: The agent's response is converted to a string, added to the conversation context, and displayed to the user, maintaining conversational continuity.

Complete Code

Here's the complete code to get you started with Ashby and CrewAI:

python
from crewai import Agent, Task, Crew, LLM
from crewai_tools import MCPServerAdapter
from composio import Composio
from dotenv import load_dotenv
import os

load_dotenv()

GOOGLE_API_KEY = os.getenv("GOOGLE_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not GOOGLE_API_KEY:
    raise ValueError("GOOGLE_API_KEY is not set in the environment.")
if not COMPOSIO_API_KEY:
    raise ValueError("COMPOSIO_API_KEY is not set in the environment.")
if not COMPOSIO_USER_ID:
    raise ValueError("COMPOSIO_USER_ID is not set in the environment.")

# Initialize Composio and create a session
composio = Composio(api_key=COMPOSIO_API_KEY)
session = composio.create(
    user_id=COMPOSIO_USER_ID,
    toolkits=["ashby"],
)
url = session.mcp.url

# Configure LLM
llm = LLM(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY"),
)

server_params = {
    "url": url,
    "transport": "streamable-http",
    "headers": {"x-api-key": COMPOSIO_API_KEY},
}

with MCPServerAdapter(server_params) as tools:
    agent = Agent(
        role="Search Assistant",
        goal="Help users with internet searches",
        backstory="You are an expert assistant with access to Composio Search tools.",
        tools=tools,
        llm=llm,
        verbose=False,
        max_iter=10,
    )

    print("Chat started! Type 'exit' or 'quit' to end.\n")

    conversation_context = ""

    while True:
        user_input = input("You: ").strip()

        if user_input.lower() in ["exit", "quit", "bye"]:
            print("\nGoodbye!")
            break

        if not user_input:
            continue

        conversation_context += f"\nUser: {user_input}\n"
        print("\nAgent is thinking...\n")

        task = Task(
            description=(
                f"Conversation history:\n{conversation_context}\n\n"
                f"Current request: {user_input}"
            ),
            expected_output="A helpful response addressing the user's request",
            agent=agent,
        )

        crew = Crew(agents=[agent], tasks=[task], verbose=False)
        result = crew.kickoff()
        response = str(result)

        conversation_context += f"Agent: {response}\n"
        print(f"Agent: {response}\n")

Conclusion

You now have a CrewAI agent connected to Ashby through Composio's Tool Router. The agent can perform Ashby operations through natural language commands.

Next steps:

  • Add role-specific instructions to customize agent behavior
  • Plug in more toolkits for multi-app workflows
  • Chain tasks for complex multi-step operations
TOOLS

Supported Tools

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

Add Candidate to Project

Add a candidate to a project in Ashby.

Add Candidate Tag

Add a tag to a candidate in Ashby.

Add Hiring Team Member

Add an Ashby user to a hiring team at the application, job, or opening level.

Add User to Interviewer Pool

Add a user to an interviewer pool.

Add Opening Job

Adds a job to an opening (job requisition) in Ashby ATS.

Add Opening Location

Tool to add a location to an opening (job requisition).

Anonymize Candidate

Anonymize a candidate by removing personally identifiable information.

Approve Offer

Approve an offer or a specific approval step within an offer's approval process.

Archive Department

Archive a department by its unique identifier.

Archive Interviewer Pool

Archive an interviewer pool in Ashby.

Archive Location

Archives a location or location hierarchy in Ashby.

Change Application Source

Change the source attribution of an application.

Change Application Stage

Move an application to a different interview stage in the hiring pipeline.

Create Application

Create a new job application by associating a candidate with a job opening in Ashby ATS.

Create Candidate

Create a new candidate in the system.

Create Candidate Note

Create a note on a candidate profile.

Create Candidate Tag

Create a new candidate tag in Ashby for categorizing and organizing candidates.

Create Custom Field

Create a new custom field in Ashby.

Create Department

Create a new department.

Create Interviewer Pool

Create a new interviewer pool.

Create Job

Create a new job opening in Ashby ATS.

Create Location

Create a new location or location hierarchy.

Create Offer

Create a new offer for a candidate in Ashby ATS.

Create Opening

Create a new opening (job requisition) in Ashby ATS.

Create Referral

Create a referral in Ashby ATS by submitting a referral form with candidate information.

Create Survey Request

Generate a survey request and receive a survey URL to send to a candidate.

Create Survey Submission

Create a new survey submission for a candidate's application.

Get API Key Info

Retrieve information about the current API key, including associated organization, user details, and permissions.

Get Application Info

Retrieve detailed information about a specific application by its ID.

Get Candidate Info

Retrieve detailed information about a specific candidate by their ID.

Get Custom Field Info

Retrieve detailed information about a specific custom field by its ID.

Get Department Info

Retrieve detailed information about a specific department by its ID.

Get Feedback Form Definition

Retrieve detailed information about a specific feedback form definition by its ID.

Get File Info

Retrieve the URL of a file associated with a candidate.

Get Interviewer Pool Info

Retrieve detailed information about a specific interviewer pool by its ID.

Get Interviewer User Settings

Get interviewer settings for a specific user by their ID.

Get Interview Info

Retrieve detailed information about a specific interview type by its ID.

Get Interview Stage Info

Tool to fetch interview stage details by ID.

Get Job Info

Retrieve detailed information about a specific job by its ID.

Get Job Interview Plan Info

Retrieve the interview plan information for a specific job.

Get Job Posting Info

Retrieve detailed information about a specific job posting by its ID.

Get Location Info

Retrieve detailed information about a specific location by its ID.

Get Offer Info

Retrieve detailed information about a specific offer by its ID.

Get Opening Info

Retrieve detailed information about a specific opening (job requisition) by its ID.

Get Referral Form

Fetches the default referral form or creates a default referral form if none exists.

Get Survey Form Definition

Retrieve detailed information about a specific survey form definition by its ID.

Get User Info

Retrieve detailed information about a specific user by their ID.

List Application Criteria Evaluations

Retrieve AI-generated criteria evaluations for an application.

List Application Feedback

Retrieve all feedback submissions for an application.

List Application Hiring Team Roles

Retrieve all available hiring team roles for applications in the organization.

List Application History

Retrieve the complete history of stage transitions for an application.

List Applications

Retrieve a list of applications with optional pagination and sync-token filtering for incremental updates.

List Approvals

Retrieve a list of approvals (offer approvals, job approvals, etc.

List Archive Reasons

Retrieve a list of all archive reasons.

List Brands

Retrieve a list of all brands for the organization.

List Candidate Client Info

Retrieve all client info records for a specific candidate with pagination support.

List Candidate Notes

Retrieve all notes for a specific candidate in Ashby.

List Candidate Projects

Retrieve all projects associated with a candidate.

List Candidates

Retrieve a list of candidates.

List Candidate Tags

Retrieve a list of all candidate tags in your Ashby account.

List Close Reasons

Lists all close reasons for jobs or openings.

List Communication Templates

Retrieve a list of all communication templates.

List Custom Fields

Retrieve a list of all custom field definitions configured in Ashby.

List Departments

Retrieve a list of all departments in the organization.

List Feedback Form Definitions

Retrieve all feedback form definitions from your Ashby organization.

List Hiring Team Roles

Retrieve a list of possible hiring team roles in the organization.

List Interviewer Pools

Retrieve a list of all interviewer pools.

List Interview Events

Retrieves all interview events for a specific interview schedule.

List Interview Plans

Retrieve a list of interview plans.

List Interview Types

List all interview types defined in Ashby.

List Interview Schedules

Retrieve a list of interview schedules.

List Interview Stage Groups

Retrieve a list of interview stage groups.

List Interview Stages

Retrieve all interview stages for an interview plan in order.

List Job Boards

Retrieve a list of job boards.

List Job Postings

Retrieve a list of job postings.

List Jobs

Retrieve a list of all jobs from Ashby ATS (Applicant Tracking System).

List Job Templates

Retrieve a list of all job templates from Ashby ATS.

List Locations

Retrieve a list of all locations.

List Offers

Retrieve a list of job offers with their latest versions.

List Openings

Retrieve a list of openings (job requisitions).

List Projects

Retrieve a list of all projects.

List Sources

Retrieve a list of all candidate sources.

List Source Tracking Links

Retrieve all source tracking links configured in Ashby.

List Survey Form Definitions

Retrieve a list of all survey form definitions from Ashby.

List Survey Submissions

Lists all survey submissions of a given survey type from Ashby.

List Users

Retrieve a list of all users in the organization.

Move Department

Tool to move a department to another parent in the organizational hierarchy.

Move Location

Tool to move a location to a different parent in the location hierarchy.

Remove Hiring Team Member

Remove an Ashby user from a hiring team at the application, job, or opening level.

Remove User from Interviewer Pool

Remove a user from an interviewer pool.

Remove Opening Job

Remove a job from an opening (job requisition) in Ashby ATS.

Remove Opening Location

Tool to remove a location from an opening (job requisition).

Restore Department

Restore an archived department by its unique identifier.

Restore Interviewer Pool

Restore an archived interviewer pool in Ashby.

Restore Location

Restores an archived location or location hierarchy in Ashby.

Search Candidates

Search for candidates by email or name.

Search Jobs

Search for jobs by title in Ashby ATS (Applicant Tracking System).

Search Opening

Search for openings by identifier.

Search Projects

Search for projects by title in Ashby.

Search Users

Search for an Ashby user by email address.

Set Custom Field Value

Set the value of a custom field for a given object (candidate, application, job, etc.

Set Custom Field Values

Set the values of multiple custom fields for a given object in a single call.

Set Job Status

Set the status of a job in Ashby ATS (Applicant Tracking System).

Set Opening Archived

Sets the archived state of an opening.

Set Opening State

Set the workflow state of an opening (job requisition).

Start Offer

Create a new offer version instance for an in-progress offer process.

Start Offer Process

Start an offer process for a candidate's application in Ashby ATS.

Submit Application Feedback

Submit structured feedback for an application using a feedback form.

Transfer Application

Transfer an application to a different job position in Ashby ATS.

Update Application

Update an application's properties in Ashby.

Update Application History

Update the complete history of an application's stage transitions.

Update Candidate

Update an existing candidate's profile information in Ashby ATS.

Update Job Compensation

Update a job's compensation tiers in Ashby ATS.

Update Department

Update an existing department's information such as its name.

Update Interviewer Pool

Update an existing interviewer pool's title or training requirements.

Update Job

Update an existing job's properties in Ashby ATS.

Update Job Posting

Update an existing job posting's details including title, description, and visibility status.

Update Location Address

Update the address of a location or location hierarchy.

Update Location External Name

Update a location's external (candidate-facing) name.

Update Location Name

Update a location's name.

Update Location Remote Status

Tool to update a location's remote status.

Update Location Workplace Type

Tool to update a location's workplace type (OnSite, Remote, or Hybrid).

Update Opening

Update properties of an existing opening (job requisition).

Update Selectable Values Custom Field

Update the selectable values for a ValueSelect or MultiValueSelect custom field.

Update User Interviewer Settings

Update interviewer settings for a user, including daily and weekly interview limits.

FRAMEWORKS

How to build Ashby MCP Agent with another framework

OpenAI Agents SDK logo

OpenAI Agents SDK

Use Ashby MCP with OpenAI Agents SDK

Claude Agent SDK logo

Claude Agent SDK

Use Ashby MCP with Claude Agent SDK

Claude Code logo

Claude Code

Use Ashby MCP with Claude Code

Claude Cowork logo

Claude Cowork

Use Ashby MCP with Claude Cowork

Codex logo

Codex

Use Ashby MCP with Codex

OpenClaw logo

OpenClaw

Use Ashby MCP with OpenClaw

Hermes logo

Hermes

Use Ashby MCP with Hermes

CLI logo

CLI

Use Ashby MCP with CLI

Google ADK logo

Google ADK

Use Ashby MCP with Google ADK

LangChain logo

LangChain

Use Ashby MCP with LangChain

Vercel AI SDK logo

Vercel AI SDK

Use Ashby MCP with Vercel AI SDK

Mastra AI logo

Mastra AI

Use Ashby MCP with Mastra AI

LlamaIndex logo

LlamaIndex

Use Ashby MCP with LlamaIndex

FAQ

Frequently asked questions

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.

Yes, you can. CrewAI 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.

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.

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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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's immensely helped keep new users on the platform.

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