How to integrate Archive.org MCP with LlamaIndex

This guide walks you through connecting Archive.org to LlamaIndex 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 LlamaIndex 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 LlamaIndex 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 LlamaIndex 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:
  • Set your OpenAI and Composio API keys
  • Install LlamaIndex and Composio packages
  • Create a Composio Tool Router session for Archive.org
  • Connect LlamaIndex to the Archive.org MCP server
  • Build a Archive.org-powered agent using LlamaIndex
  • Interact with Archive.org through natural language

What is LlamaIndex?

LlamaIndex is a data framework for building LLM applications. It provides tools for connecting LLMs to external data sources and services through agents and tools.

Key features include:

  • ReAct Agent: Reasoning and acting pattern for tool-using agents
  • MCP Tools: Native support for Model Context Protocol
  • Context Management: Maintain conversation context across interactions
  • Async Support: Built 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 step10 STEPS
1

Prerequisites

Before you begin, make sure you have:
  • Python 3.8/Node 16 or higher installed
  • A Composio account with the API key
  • An OpenAI API key
  • A Archive.org account and project
  • Basic familiarity with async Python/Typescript
2

Getting API Keys for OpenAI, Composio, and Archive.org

OpenAI API key (OPENAI_API_KEY)
  • Go to the OpenAI dashboard
  • Create an API key if you don't have one
  • Assign it to OPENAI_API_KEY in .env
Composio API key and user ID
  • Log into the Composio dashboard
  • Copy your API key from Settings
    • Use this as COMPOSIO_API_KEY
  • Pick a stable user identifier (email or ID)
    • Use this as COMPOSIO_USER_ID
3

Installing dependencies

npm install @composio/llamaindex @llamaindex/openai @llamaindex/tools @llamaindex/workflow dotenv

Create a new Typescript project and install the necessary dependencies:

  • @composio/llamaindex: Composio's LlamaIndex integration
  • @llamaindex/openai: OpenAI LLM integration
  • @llamaindex/tools: MCP client for LlamaIndex
  • @llamaindex/workflow: Workflow framework for LlamaIndex
  • dotenv: Environment variable management
4

Set environment variables

bash
OPENAI_API_KEY=your-openai-api-key
COMPOSIO_API_KEY=your-composio-api-key
COMPOSIO_USER_ID=your-user-id

Create a .env file in your project root:

These credentials will be used to:

  • Authenticate with OpenAI's GPT-5 model
  • Connect to Composio's Tool Router
  • Identify your Composio user session for Archive.org access
5

Import modules

import "dotenv/config";
import readline from "node:readline/promises";
import { stdin as input, stdout as output } from "node:process";

import { Composio } from "@composio/core";

import { mcp } from "@llamaindex/tools";
import { agent as createAgent } from "@llamaindex/workflow";
import { openai } from "@llamaindex/openai";

dotenv.config();

Create a new file called archive.org_llamaindex_agent.ts and import the required modules:

Key imports:

  • dotenv.config loads .env at runtime
  • readline gives us a simple CLI chat loop
  • Composio is the main Composio SDK client
  • mcp connects to an MCP endpoint
  • createAgent builds a LlamaIndex agent
  • openai configures the LLM backend
6

Load environment variables and initialize Composio

const OPENAI_API_KEY = process.env.OPENAI_API_KEY;
const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY;
const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID;

if (!OPENAI_API_KEY) throw new Error("OPENAI_API_KEY is not set");
if (!COMPOSIO_API_KEY) throw new Error("COMPOSIO_API_KEY is not set");
if (!COMPOSIO_USER_ID) throw new Error("COMPOSIO_USER_ID is not set");

What's happening:

This ensures missing credentials cause early, clear errors before the agent attempts to initialise.

7

Create a Tool Router session and build the agent function

async function buildAgent() {

  console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`);
  console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`);

  const composio = new Composio({
    apiKey: COMPOSIO_API_KEY,
    provider: new LlamaindexProvider(),
  });

  const session = await composio.create(
    COMPOSIO_USER_ID!,
    {
      toolkits: ["archive_org"],
    },
  );

  const mcpUrl = session.mcp.url;
  console.log(`Composio Tool Router MCP URL: ${mcpUrl}`);

  const server = mcp({
    url: mcpUrl,
    clientName: "composio_tool_router_with_llamaindex",
    requestInit: {
      headers: {
        "x-api-key": COMPOSIO_API_KEY!,
      },
    },
    // verbose: true,
  });

  const tools = await server.tools();

  const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" });

  const agent = createAgent({
    name: "composio_tool_router_with_llamaindex",
        description : "An agent that uses Composio Tool Router MCP tools to perform actions.",
    systemPrompt:
      "You are a helpful assistant connected to Composio Tool Router."+
"Use the available tools to answer user queries and perform Archive.org actions." ,
    llm,
    tools,
  });

  return agent;
}

What's happening here:

  • We create a Composio client using your API key and configure it with the LlamaIndex provider
  • We then create a tool router MCP session for your user, specifying the toolkits we want to use (in this case, archive.org)
  • The session returns an MCP HTTP endpoint URL that acts as a gateway to all your configured tools
  • LlamaIndex will connect to this endpoint to dynamically discover and use the available Archive.org tools.
  • The MCP tools are mapped to LlamaIndex-compatible tools and plug them into the Agent.
8

Create an interactive chat loop

async function chatLoop(agent: ReturnType<typeof createAgent>) {
  const rl = readline.createInterface({ input, output });

  console.log("Type 'quit' or 'exit' to stop.");

  while (true) {
    let userInput: string;

    try {
      userInput = (await rl.question("\nYou: ")).trim();
    } catch {
      console.log("\nAgent: Bye!");
      break;
    }

    if (!userInput) {
      continue;
    }

    const lower = userInput.toLowerCase();
    if (lower === "quit" || lower === "exit") {
      console.log("Agent: Bye!");
      break;
    }

    try {
      process.stdout.write("Agent: ");

      const stream = agent.runStream(userInput);
      let finalResult: any = null;

      for await (const event of stream) {
        // The event.data contains the streamed content
        const data: any = event.data;

        // Check for streaming delta content
        if (data?.delta) {
          process.stdout.write(data.delta);
        }

        // Store final result for fallback
        if (data?.result || data?.message) {
          finalResult = data;
        }
      }

      // If no streaming happened, show the final result
      if (finalResult) {
        const answer =
          finalResult.result ??
          finalResult.message?.content ??
          finalResult.message ??
          "";
        if (answer && typeof answer === "string" && !answer.includes("[object")) {
          process.stdout.write(answer);
        }
      }

      console.log(); // New line after streaming completes
    } catch (err: any) {
      console.error("\nAgent error:", err?.message ?? err);
    }
  }

  rl.close();
}

What's happening:

  • We're creating a direct terminal interface to chat with Archive.org
  • The LLM's responses are streamed to the CLI for faster interaction.
  • The agent uses context to maintain conversation history
  • The agent processes the request, selects appropriate Archive.org tools, and returns a result
  • We extract the answer from the result data structure and display it to the user
  • You can type 'quit' or 'exit' to stop the chat loop gracefully
  • Agent responses and any errors are streamed in a clear, readable format
9

Define the main entry point

async function main() {
  try {
    const agent = await buildAgent();
    await chatLoop(agent);
  } catch (err) {
    console.error("Failed to start agent:", err);
    process.exit(1);
  }
}

main();

What's happening here:

  • We're orchestrating the entire application flow
  • The agent gets built with proper error handling
  • Then we kick off the interactive chat loop so you can start talking to Archive.org
10

Run the agent

npx ts-node llamaindex-agent.ts

When prompted, authenticate and authorise your agent with Archive.org, then start asking questions.

Complete Code

Here's the complete code to get you started with Archive.org and LlamaIndex:

import "dotenv/config";
import readline from "node:readline/promises";
import { stdin as input, stdout as output } from "node:process";

import { Composio } from "@composio/core";
import { LlamaindexProvider } from "@composio/llamaindex";

import { mcp } from "@llamaindex/tools";
import { agent as createAgent } from "@llamaindex/workflow";
import { openai } from "@llamaindex/openai";

dotenv.config();

const OPENAI_API_KEY = process.env.OPENAI_API_KEY;
const COMPOSIO_API_KEY = process.env.COMPOSIO_API_KEY;
const COMPOSIO_USER_ID = process.env.COMPOSIO_USER_ID;

if (!OPENAI_API_KEY) {
    throw new Error("OPENAI_API_KEY is not set in the environment");
  }
if (!COMPOSIO_API_KEY) {
    throw new Error("COMPOSIO_API_KEY is not set in the environment");
  }
if (!COMPOSIO_USER_ID) {
    throw new Error("COMPOSIO_USER_ID is not set in the environment");
  }

async function buildAgent() {

  console.log(`Initializing Composio client...${COMPOSIO_USER_ID!}...`);
  console.log(`COMPOSIO_USER_ID: ${COMPOSIO_USER_ID!}...`);

  const composio = new Composio({
    apiKey: COMPOSIO_API_KEY,
    provider: new LlamaindexProvider(),
  });

  const session = await composio.create(
    COMPOSIO_USER_ID!,
    {
      toolkits: ["archive_org"],
    },
  );

  const mcpUrl = session.mcp.url;
  console.log(`Composio Tool Router MCP URL: ${mcpUrl}`);

  const server = mcp({
    url: mcpUrl,
    clientName: "composio_tool_router_with_llamaindex",
    requestInit: {
      headers: {
        "x-api-key": COMPOSIO_API_KEY!,
      },
    },
    // verbose: true,
  });

  const tools = await server.tools();

  const llm = openai({ apiKey: OPENAI_API_KEY, model: "gpt-5" });

  const agent = createAgent({
    name: "composio_tool_router_with_llamaindex",
    description:
      "An agent that uses Composio Tool Router MCP tools to perform actions.",
    systemPrompt:
      "You are a helpful assistant connected to Composio Tool Router."+
"Use the available tools to answer user queries and perform Archive.org actions." ,
    llm,
    tools,
  });

  return agent;
}

async function chatLoop(agent: ReturnType<typeof createAgent>) {
  const rl = readline.createInterface({ input, output });

  console.log("Type 'quit' or 'exit' to stop.");

  while (true) {
    let userInput: string;

    try {
      userInput = (await rl.question("\nYou: ")).trim();
    } catch {
      console.log("\nAgent: Bye!");
      break;
    }

    if (!userInput) {
      continue;
    }

    const lower = userInput.toLowerCase();
    if (lower === "quit" || lower === "exit") {
      console.log("Agent: Bye!");
      break;
    }

    try {
      process.stdout.write("Agent: ");

      const stream = agent.runStream(userInput);
      let finalResult: any = null;

      for await (const event of stream) {
        // The event.data contains the streamed content
        const data: any = event.data;

        // Check for streaming delta content
        if (data?.delta) {
          process.stdout.write(data.delta);
        }

        // Store final result for fallback
        if (data?.result || data?.message) {
          finalResult = data;
        }
      }

      // If no streaming happened, show the final result
      if (finalResult) {
        const answer =
          finalResult.result ??
          finalResult.message?.content ??
          finalResult.message ??
          "";
        if (answer && typeof answer === "string" && !answer.includes("[object")) {
          process.stdout.write(answer);
        }
      }

      console.log(); // New line after streaming completes
    } catch (err: any) {
      console.error("\nAgent error:", err?.message ?? err);
    }
  }

  rl.close();
}

async function main() {
  try {
    const agent = await buildAgent();
    await chatLoop(agent);
  } catch (err: any) {
    console.error("Failed to start agent:", err?.message ?? err);
    process.exit(1);
  }
}

main();

Conclusion

You've successfully connected Archive.org to LlamaIndex through Composio's Tool Router MCP layer. Key takeaways:
  • Tool Router dynamically exposes Archive.org tools through an MCP endpoint
  • LlamaIndex's ReActAgent handles reasoning and orchestration; Composio handles integrations
  • The agent becomes more capable without increasing prompt size
  • Async Python provides clean, efficient execution of agent workflows
You can easily extend this to other toolkits like Gmail, Notion, Stripe, GitHub, and more by adding them to the toolkits parameter.
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. LlamaIndex 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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