How to integrate Algolia MCP with Pydantic AI

BOOK A CALLGET STARTED FOR FREE
Framework Integration Gradient
Algolia Logo
Pydantic AI Logo
divider

Introduction

This guide walks you through connecting Algolia to Pydantic AI using the Composio tool router. By the end, you'll have a working Algolia agent that can export all records from products index, clear all objects from blog_posts index, copy index settings from staging to production, create an ab test comparing two search configs through natural language commands.

This guide will help you understand how to give your Pydantic AI agent real control over a Algolia account through Composio's Algolia 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 Algolia
  • 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 Algolia 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 Algolia MCP server, and what's possible with it?

The Algolia MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Algolia account. It provides structured and secure access to your search indices, so your agent can perform actions like browsing records, managing index settings, running A/B tests, copying configurations, and tracking search events on your behalf.

  • Comprehensive index browsing and export: Easily direct your agent to retrieve and iterate through all records in any Algolia index for analysis, backup, or migration tasks.
  • Automated A/B test management: Set up, launch, and monitor A/B tests to compare search performance between different index variants or configurations—all without manual coding.
  • Index and rule duplication: Quickly copy entire indices, settings, or query rules from one index to another, streamlining your search deployment and versioning workflows.
  • Bulk index cleanup and resets: Instruct your agent to clear all objects or rules in an index while keeping configurations intact, letting you efficiently manage large data updates or reindexing processes.
  • Real-time event tracking: Capture user interactions like clicks and conversions, enabling your agent to report search analytics and optimize relevance based on actual user behavior.

Supported Tools & Triggers

Tools
Add AB TestTool to create an ab test comparing search performance between two variants.
Browse Algolia IndexTool to retrieve all records from an index.
Clear ObjectsTool to clear records of an index without affecting settings.
Clear RulesTool to delete all rules in an index.
Clicked Object IDsTool to send a click event to algolia to capture clicked items.
Clicked Object IDs After SearchTool to send a click event after a search response.
Converted Object IDsTool to send a conversion event for items outside of search context.
Copy IndexTool to copy the specified index to a new index.
Copy RulesTool to copy rules from one index to another.
Copy Index SettingsTool to copy the settings from one index to another.
Delete IndexTool to delete the specified index and all its records.
Delete Multiple RecordsTool to delete multiple records from an algolia index.
Delete RuleTool to delete the specified rule from an index.
Delete SynonymTool to delete a synonym from a specified index.
Export RulesTool to export all rules defined on an index.
Find ObjectTool to find the first object matching a query or filter in an index.
Get Object PositionTool to retrieve an object’s position in a result set.
Get multiple objectsTool to retrieve multiple records from an index.
Get Index SettingsTool to retrieve the settings of a specified index.
Index ExistsTool to check if an algolia index exists.
Init Insights API ClientTool to initialize the algolia insights api client.
List IndicesTool to list all indices and their metadata.
Partial Update ObjectsTool to partially update multiple records in the specified index.
Replace All RulesTool to push a new set of rules, erasing previous ones.
Save SynonymTool to add or update a synonym in the specified index.
Search Algolia IndexTool to perform a search on a specified algolia index.
Search Multiple IndicesTool to perform searches across multiple indices in a single call.
Search RulesTool to search for rules in the specified index.
Search SynonymsTool to search for synonyms in the specified index.
Set Index SettingsTool to update an algolia index's settings.

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 Algolia
  • 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 Algolia
  • MCPServerStreamableHTTP connects to the Algolia 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 Algolia
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["algolia"],
    )
    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 Algolia 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
algolia_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[algolia_mcp],
    instructions=(
        "You are a Algolia assistant. Use Algolia tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Algolia endpoint
  • The agent uses GPT-5 to interpret user commands and perform Algolia 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 Algolia.\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
  • Algolia 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 Algolia and Pydantic AI:

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

OpenAI Agents SDK

OpenAI Agents SDK

Use Algolia MCP with OpenAI Agents SDK

Claude Agent SDK

Claude Agent SDK

Use Algolia MCP with Claude Agent SDK

Google ADK

Google ADK

Use Algolia MCP with Google ADK

LangChain

LangChain

Use Algolia MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use Algolia MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use Algolia MCP with Mastra AI

LlamaIndex

LlamaIndex

Use Algolia MCP with LlamaIndex

CrewAI

CrewAI

Use Algolia MCP with CrewAI

FAQ

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

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

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

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

Used by agents from

Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai
Context
Letta
glean
HubSpot
Agent.ai
Altera
DataStax
Entelligence
Rolai

Never worry about agent reliability

We handle tool reliability, observability, and security so you never have to second-guess an agent action.

Book a call↗Get started for free