How to integrate Archive.org MCP with Pydantic AI

This guide walks you through connecting Archive.org to Pydantic AI using the Composio tool router. By the end, you'll have a working Archive.org agent that can search collections, download item files, inspect wayback captures, fetch iiif manifests, and manage item metadata through natural language commands. This guide will help you understand how to give your Pydantic AI agent real control over a Archive.org account through Composio's Archive.org MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved.

Archive.org logoArchive.org
Api Key

Archive.org is the Internet Archive's digital library of websites, books, audio, video, and images. Use it to preserve, explore, and access historical web captures and public-domain media.

26 Tools

Introduction

This guide walks you through connecting Archive.org to Pydantic AI using the Composio tool router. By the end, you'll have a working Archive.org agent that can search collections, download item files, inspect wayback captures, fetch iiif manifests, and manage item metadata through natural language commands.

This guide will help you understand how to give your Pydantic AI agent real control over a Archive.org account through Composio's Archive.org MCP server.

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

Also integrate Archive.org with

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 Archive.org
  • 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 Archive.org 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 Archive.org MCP server, and what's possible with it?

The Archive.org MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Archive.org account. It provides structured and secure access to archived content, Wayback captures, item records, usage analytics, and account tasks, so your agent can search collections, retrieve files, manage items, inspect activity, and handle reviews on your behalf.

  • Content search and retrieval: Have your agent search Archive.org by keywords and metadata, inspect complete item records, and download public files.
  • Wayback history research: Instruct your agent to find the closest archived version of a web page or list available captures for a website.
  • Item and file management: Direct your agent to check identifier availability, upload, copy, or delete files, update item metadata, and request new derivatives.
  • Images, manifests, and analytics: Let the agent inspect IIIF image details and manifests, render selected image regions, and review item views, history, geography, and referrers.
  • Account tasks and reviews: Have your agent check your account details, monitor catalog tasks and limits, read task logs, and create, update, retrieve, or delete your reviews.

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 step09 STEPS
1

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
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 pydantic-ai python-dotenv

Install the required libraries.

What's happening:

  • composio connects your agent to external SaaS tools like Archive.org
  • pydantic-ai lets you create structured AI agents with tool support
  • python-dotenv loads your environment variables securely from a .env file
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

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
5

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 Archive.org
  • MCPServerStreamableHTTP connects to the Archive.org MCP server endpoint
  • Agent from Pydantic AI lets you define and run the AI assistant
6

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 Archive.org
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["archive_org"],
    )
    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 Archive.org 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
7

Initialize the Pydantic AI Agent

python
# Attach the MCP server to a Pydantic AI Agent
archive_org_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
agent = Agent(
    "openai:gpt-5",
    toolsets=[archive_org_mcp],
    instructions=(
        "You are a Archive.org assistant. Use Archive.org tools to help users "
        "with their requests. Ask clarifying questions when needed."
    ),
)
What's happening:
  • The MCP client connects to the Archive.org endpoint
  • The agent uses GPT-5 to interpret user commands and perform Archive.org operations
  • The instructions field defines the agent's role and behavior
8

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 Archive.org.\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
  • Archive.org API calls happen automatically under the hood
  • The model keeps conversation history to maintain context across turns
9

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 Archive.org 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 Archive.org
    composio = Composio(api_key=api_key)
    session = composio.create(
        user_id=user_id,
        toolkits=["archive_org"],
    )
    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
    archive_org_mcp = MCPServerStreamableHTTP(url, headers={"x-api-key": COMPOSIO_API_KEY})
    agent = Agent(
        "openai:gpt-5",
        toolsets=[archive_org_mcp],
        instructions=(
            "You are a Archive.org assistant. Use Archive.org 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 Archive.org.\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 Archive.org through Composio's Tool Router. With this setup, your agent can perform real Archive.org 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 + Archive.org for workflow automation)
This architecture makes your AI agent "agent-native", able to securely use APIs in a unified, composable way without custom integrations.
TOOLS

Supported Tools

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

Advanced Search Archive.org Items

Search Archive.

Check Identifier Availability

Check whether an Archive.

Check Archive.org Upload Limit

Check whether Archive.

Copy Item File

Copy one Archive.

Delete Item File

Submit asynchronous deletion of one named file from an Archive.

Delete My Archive.org Review

Permanently delete the connected Archive.

Derive Archive.org Item

Queue Archive.

Download Item File

Download one public file from an Archive.

Find Wayback Snapshots

Find the closest archived Wayback Machine snapshot for each requested URL, using one before, after, or either direction for the batch.

Get Connected Archive.org User

Return the authenticated Archive.

Get Detailed Archive.org Views

Get bounded geographic view analytics and, for items, top referrers over a recent window or date range.

Get IIIF Image Info

Get normalized IIIF Image API capabilities through Archive.

Get IIIF Manifest

Get a compact IIIF Presentation manifest for an Archive.

Get Item Metadata

Get an Archive.

Get Item View Counts

Get all-time, last-30-day, and last-7-day view counts for one or more Archive.

Get Item View History

Get a bounded daily view history for one Archive.

Get My Review

Get the connected Archive.

Get Archive.org Task Log

Download a plain-text log for a task visible to the connected account.

Get Task Rate Limits

Report the connected account's current task capacity and in-flight counts for one Archive.

List Archive.org Tasks

Return any documented combination of the connected account's task summary, active catalog, and resource-authorized history, one page at a time.

List Wayback Captures

Return one bounded structured CDX page of Wayback captures for a URL or host.

Render IIIF Image

Render a bounded crop, resize, rotation, quality, and format from a fixed Archive.

Search Archive.org Items

Search Archive.

Update Item Metadata

Apply JSON Patch changes to one Archive.

Upload Item File

Create or replace one file through Archive.

Upsert My Archive.org Review

Create or overwrite the connected Archive.

FAQ

Frequently asked questions

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

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 Archive.org tools.

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

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