# How to integrate Conversion tools MCP with LlamaIndex

```json
{
  "title": "How to integrate Conversion tools MCP with LlamaIndex",
  "toolkit": "Conversion tools",
  "toolkit_slug": "conversion_tools",
  "framework": "LlamaIndex",
  "framework_slug": "llama-index",
  "url": "https://composio.dev/toolkits/conversion_tools/framework/llama-index",
  "markdown_url": "https://composio.dev/toolkits/conversion_tools/framework/llama-index.md",
  "updated_at": "2026-05-12T10:07:30.282Z"
}
```

## Introduction

This guide walks you through connecting Conversion tools to LlamaIndex using the Composio tool router. By the end, you'll have a working Conversion tools agent that can convert your excel file to clean csv, export a website as a pdf snapshot, extract text from this word document through natural language commands.
This guide will help you understand how to give your LlamaIndex agent real control over a Conversion tools account through Composio's Conversion tools MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Conversion tools with

- [ChatGPT](https://composio.dev/toolkits/conversion_tools/framework/chatgpt)
- [Antigravity](https://composio.dev/toolkits/conversion_tools/framework/antigravity)
- [OpenAI Agents SDK](https://composio.dev/toolkits/conversion_tools/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/conversion_tools/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/conversion_tools/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/conversion_tools/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/conversion_tools/framework/codex)
- [Cursor](https://composio.dev/toolkits/conversion_tools/framework/cursor)
- [VS Code](https://composio.dev/toolkits/conversion_tools/framework/vscode)
- [OpenCode](https://composio.dev/toolkits/conversion_tools/framework/opencode)
- [OpenClaw](https://composio.dev/toolkits/conversion_tools/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/conversion_tools/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/conversion_tools/framework/cli)
- [Google ADK](https://composio.dev/toolkits/conversion_tools/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/conversion_tools/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/conversion_tools/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/conversion_tools/framework/mastra-ai)
- [CrewAI](https://composio.dev/toolkits/conversion_tools/framework/crew-ai)

## 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 Conversion tools
- Connect LlamaIndex to the Conversion tools MCP server
- Build a Conversion tools-powered agent using LlamaIndex
- Interact with Conversion tools 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 Conversion tools MCP server, and what's possible with it?

The Conversion tools MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Conversion tools account. It provides structured and secure access to a wide range of file and document conversion utilities, so your agent can convert documents, extract data, generate snapshots, and automate file handling between multiple formats on your behalf.
- Seamless document format conversion: Effortlessly have your agent convert Excel, Word, Markdown, OXPS, or JPG files to formats like CSV, HTML, PDF, text, or JSON.
- Website snapshot creation: Ask your agent to capture entire web pages as PDF documents or PNG images, ready to download or share.
- Automated file upload and processing: Let your agent upload local files, obtain conversion-ready file IDs, and initiate multi-step conversion workflows.
- AI-powered data extraction: Use AI tools to transform images (JPG) into structured JSON, streamlining data entry and analysis tasks.
- Easy retrieval of conversion results: Direct your agent to track conversion tasks and download the final output files once processing is complete.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `CONVERSION_TOOLS_CONVERT_EXCEL_TO_HTML` | Convert Excel to HTML | Convert an Excel (.xlsx) file to HTML table format. Use when you need to transform spreadsheet data into an HTML representation. Provide either a file upload or a public URL to the Excel file. Returns a task_id that can be used to check the conversion status and download the result once complete. |
| `CONVERSION_TOOLS_CONVERT_WORD_TO_TEXT` | Convert Word to Text | Convert Word documents (.doc/.docx) to plain text (.txt). The action uploads the document, waits for conversion to complete (up to ~60 seconds), and returns the task status with a URL to download the converted text file. Use when you need to extract text content from Word documents for further processing. |
| `CONVERSION_TOOLS_CREATE_TASK` | Create Conversion Task | Tool to create a new conversion task. This is the main endpoint for performing conversions across 100+ conversion types including XML, JSON, Excel, PDF, CSV, images, audio/video, and more. Use when you need to convert any supported file format or website. Counts against quota unless sandbox mode is enabled. |
| `CONVERSION_TOOLS_DOWNLOAD_FILE` | Download Converted File | Download a converted file from the Conversion Tools API using its file ID. Use this action after a conversion task completes successfully. The file_id is obtained from the task status response when status is 'SUCCESS'. Converted files are automatically deleted after 24 hours. Workflow: 1. Run a conversion task (e.g., convert_website_to_pdf) 2. Check task status until status is 'SUCCESS' 3. Use the file_id from the task response to download the result |
| `CONVERSION_TOOLS_GET_AUTH_INFO` | Get Auth Info | Tool to get information about the authenticated user including email address. Use when you need to verify API credentials or retrieve the user's email. |
| `CONVERSION_TOOLS_GET_CONFIG` | Get Conversion Config | Tool to get available conversion types and their configuration. Returns the list of all supported conversions with their options. Use this to discover what conversions are available and what parameters they accept. |
| `CONVERSION_TOOLS_GET_FILE_INFO` | Get File Info | Tool to get metadata about a file including size, name, and preview (for text files). Use when you need to retrieve information about a previously uploaded file. This does NOT count against your quota. |
| `CONVERSION_TOOLS_GET_TASK_STATUS` | Get Task Status | Tool to get the status of a conversion task. Poll this endpoint until status is SUCCESS or ERROR. On SUCCESS, the response includes file_id which can be used to download the result file. |
| `CONVERSION_TOOLS_LIST_TASKS` | List Conversion Tasks | Get all tasks for the authenticated user (up to 50 most recent tasks). Use this action to retrieve conversion task history, check task statuses, or find completed tasks for downloading results. This does NOT count against your API quota. Filter by status to retrieve only tasks in a specific state (PENDING, RUNNING, SUCCESS, or ERROR). |
| `CONVERSION_TOOLS_UPDATE_TASK_RETENTION` | Update Task Retention | Tool to update the retention mode for a task. Use when you need to change how long task files are kept before automatic deletion. Standard mode (standard_24h) retains files for 24 hours. TTL mode (ttl_15m) is for paid users only and deletes files after 15 minutes. |
| `CONVERSION_TOOLS_UPLOAD_FILE` | Upload File | Upload a file to the ConversionTools API for subsequent conversion operations. This action uploads a file and returns a file_id that can be used with other conversion actions such as convert_word_to_text, convert_excel_to_csv, convert_oxps_to_pdf, etc. Supported formats include: documents (DOC, DOCX, PDF, TXT, RTF), spreadsheets (XLS, XLSX, CSV), images (PNG, JPG, GIF, BMP), and various other file types. |

## Supported Triggers

None listed.

## Creating MCP Server - Stand-alone vs Composio SDK

The Conversion tools MCP server is an implementation of the Model Context Protocol that connects your AI agent to Conversion tools. It provides structured and secure access so your agent can perform Conversion tools operations on your behalf through a secure, permission-based interface.
With Composio's managed implementation, you don't have to create your own developer app. For production, if you're building an end product, we recommend using your own credentials. The managed server helps you prototype fast and go from 0-1 faster.

## Step-by-step Guide

### 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 Conversion tools account and project
- Basic familiarity with async Python/Typescript

### 1. Getting API Keys for OpenAI, Composio, and Conversion tools

No description provided.

### 2. Installing dependencies

No description provided.
```python
pip install composio-llamaindex llama-index llama-index-llms-openai llama-index-tools-mcp python-dotenv
```

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

### 3. Set environment variables

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 Conversion tools access
```bash
OPENAI_API_KEY=your-openai-api-key
COMPOSIO_API_KEY=your-composio-api-key
COMPOSIO_USER_ID=your-user-id
```

### 4. Import modules

No description provided.
```python
import asyncio
import os
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()
```

```typescript
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();
```

### 5. Load environment variables and initialize Composio

No description provided.
```python
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
COMPOSIO_API_KEY = os.getenv("COMPOSIO_API_KEY")
COMPOSIO_USER_ID = os.getenv("COMPOSIO_USER_ID")

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_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")
```

```typescript
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");
```

### 6. Create a Tool Router session and build the agent function

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, conversion tools)
- 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 Conversion tools tools.
- The MCP tools are mapped to LlamaIndex-compatible tools and plug them into the Agent.
```python
async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["conversion_tools"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")

    description = "An agent that uses Composio Tool Router MCP tools to perform Conversion tools actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Conversion tools actions.
    """
    return ReActAgent(tools=tools, llm=llm, description=description, system_prompt=system_prompt, verbose=True)
```

```typescript
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: ["conversion_tools"],
    },
  );

  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 Conversion tools actions." ,
    llm,
    tools,
  });

  return agent;
}
```

### 7. Create an interactive chat loop

No description provided.
```python
async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")
```

```typescript
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();
}
```

### 8. Define the main entry point

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 Conversion tools
```python
async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")
```

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

main();
```

### 9. Run the agent

When prompted, authenticate and authorise your agent with Conversion tools, then start asking questions.
```bash
python llamaindex_agent.py
```

```typescript
npx ts-node llamaindex-agent.ts
```

## Complete Code

```python
import asyncio
import os
import signal
import dotenv

from composio import Composio
from composio_llamaindex import LlamaIndexProvider
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.workflow import Context
from llama_index.llms.openai import OpenAI
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec

dotenv.load_dotenv()

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

if not OPENAI_API_KEY:
    raise ValueError("OPENAI_API_KEY is not set")
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")

async def build_agent() -> ReActAgent:
    composio_client = Composio(
        api_key=COMPOSIO_API_KEY,
        provider=LlamaIndexProvider(),
    )

    session = composio_client.create(
        user_id=COMPOSIO_USER_ID,
        toolkits=["conversion_tools"],
    )

    mcp_url = session.mcp.url
    print(f"Composio MCP URL: {mcp_url}")

    mcp_client = BasicMCPClient(mcp_url, headers={"x-api-key": COMPOSIO_API_KEY})
    mcp_tool_spec = McpToolSpec(client=mcp_client)
    tools = await mcp_tool_spec.to_tool_list_async()

    llm = OpenAI(model="gpt-5")
    description = "An agent that uses Composio Tool Router MCP tools to perform Conversion tools actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Conversion tools actions.
    """
    return ReActAgent(
        tools=tools,
        llm=llm,
        description=description,
        system_prompt=system_prompt,
        verbose=True,
    );

async def chat_loop(agent: ReActAgent) -> None:
    ctx = Context(agent)
    print("Type 'quit', 'exit', or Ctrl+C to stop.")

    while True:
        try:
            user_input = input("\nYou: ").strip()
        except (KeyboardInterrupt, EOFError):
            print("\nBye!")
            break

        if not user_input or user_input.lower() in {"quit", "exit"}:
            print("Bye!")
            break

        try:
            print("Agent: ", end="", flush=True)
            handler = agent.run(user_input, ctx=ctx)

            async for event in handler.stream_events():
                # Stream token-by-token from LLM responses
                if hasattr(event, "delta") and event.delta:
                    print(event.delta, end="", flush=True)
                # Show tool calls as they happen
                elif hasattr(event, "tool_name"):
                    print(f"\n[Using tool: {event.tool_name}]", flush=True)

            # Get final response
            response = await handler
            print()  # Newline after streaming
        except KeyboardInterrupt:
            print("\n[Interrupted]")
            continue
        except Exception as e:
            print(f"\nError: {e}")

async def main() -> None:
    agent = await build_agent()
    await chat_loop(agent)

if __name__ == "__main__":
    # Handle Ctrl+C gracefully
    signal.signal(signal.SIGINT, lambda s, f: (print("\nBye!"), exit(0)))
    try:
        asyncio.run(main())
    except KeyboardInterrupt:
        print("\nBye!")
```

```typescript
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: ["conversion_tools"],
    },
  );

  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 Conversion tools 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 Conversion tools to LlamaIndex through Composio's Tool Router MCP layer.
Key takeaways:
- Tool Router dynamically exposes Conversion tools 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.

## How to build Conversion tools MCP Agent with another framework

- [ChatGPT](https://composio.dev/toolkits/conversion_tools/framework/chatgpt)
- [Antigravity](https://composio.dev/toolkits/conversion_tools/framework/antigravity)
- [OpenAI Agents SDK](https://composio.dev/toolkits/conversion_tools/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/conversion_tools/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/conversion_tools/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/conversion_tools/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/conversion_tools/framework/codex)
- [Cursor](https://composio.dev/toolkits/conversion_tools/framework/cursor)
- [VS Code](https://composio.dev/toolkits/conversion_tools/framework/vscode)
- [OpenCode](https://composio.dev/toolkits/conversion_tools/framework/opencode)
- [OpenClaw](https://composio.dev/toolkits/conversion_tools/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/conversion_tools/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/conversion_tools/framework/cli)
- [Google ADK](https://composio.dev/toolkits/conversion_tools/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/conversion_tools/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/conversion_tools/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/conversion_tools/framework/mastra-ai)
- [CrewAI](https://composio.dev/toolkits/conversion_tools/framework/crew-ai)

## Related Toolkits

- [Google Drive](https://composio.dev/toolkits/googledrive) - Google Drive is a cloud storage platform for uploading, sharing, and collaborating on files. It's perfect for keeping your documents accessible and organized across devices.
- [Google Docs](https://composio.dev/toolkits/googledocs) - Google Docs is a cloud-based word processor that enables document creation and real-time collaboration. Its seamless sharing and version history make team editing and content management a breeze.
- [Google Super](https://composio.dev/toolkits/googlesuper) - Google Super is an all-in-one suite combining Gmail, Drive, Calendar, Sheets, Analytics, and more. It gives you a unified platform to manage your digital life, boosting productivity and organization.
- [Affinda](https://composio.dev/toolkits/affinda) - Affinda is an AI-powered document processing platform that automates data extraction from resumes, invoices, and more. It streamlines document-heavy workflows by turning files into structured, actionable data.
- [Agility cms](https://composio.dev/toolkits/agility_cms) - Agility CMS is a headless content management system for building and managing digital experiences across platforms. It lets teams update content quickly and deliver omnichannel experiences with ease.
- [Algodocs](https://composio.dev/toolkits/algodocs) - Algodocs is an AI-powered platform that automates data extraction from business documents. It delivers fast, secure, and accurate processing without templates or manual training.
- [Api2pdf](https://composio.dev/toolkits/api2pdf) - Api2Pdf is a REST API for generating PDFs from HTML, URLs, and documents using powerful engines like wkhtmltopdf and Headless Chrome. It streamlines document conversion and automation for developers and businesses.
- [Aryn](https://composio.dev/toolkits/aryn) - Aryn is an AI-powered platform for parsing, extracting, and analyzing data from unstructured documents. Use it to automate document processing and unlock actionable insights from your files.
- [Boldsign](https://composio.dev/toolkits/boldsign) - Boldsign is a digital eSignature platform for sending, signing, and tracking documents online. Organizations use it to automate agreements and manage legally binding workflows efficiently.
- [Boloforms](https://composio.dev/toolkits/boloforms) - BoloForms is an eSignature platform built for small businesses, offering unlimited signatures, templates, and forms. It simplifies digital document signing and team collaboration at a predictable, fixed price.
- [Box](https://composio.dev/toolkits/box) - Box is a cloud content management and file sharing platform for businesses. It helps teams securely store, organize, and collaborate on files from anywhere.
- [Carbone](https://composio.dev/toolkits/carbone) - Carbone is a blazing-fast report generator that turns JSON data into PDFs, Word docs, spreadsheets, and more using flexible templates. It lets you automate document creation at scale with minimal code.
- [Castingwords](https://composio.dev/toolkits/castingwords) - CastingWords is a transcription service specializing in human-powered, accurate transcripts via a simple API. Get seamless audio-to-text conversion for interviews, meetings, podcasts, and more.
- [Cloudconvert](https://composio.dev/toolkits/cloudconvert) - CloudConvert is a powerful file conversion service supporting over 200 file formats. It streamlines converting, compressing, and managing documents, media, and more, all in one place.
- [Cloudlayer](https://composio.dev/toolkits/cloudlayer) - Cloudlayer is a document and asset generation service for creating PDFs and images via API or SDKs. It lets you automate high-quality doc creation, saving dev time and reducing manual work.
- [Cloudpress](https://composio.dev/toolkits/cloudpress) - Cloudpress is a content export tool for Google Docs and Notion. It automates publishing to your favorite Content Management Systems.
- [Contentful graphql](https://composio.dev/toolkits/contentful_graphql) - Contentful graphql is a content delivery API that lets you access Contentful data using GraphQL queries. It gives you efficient, flexible ways to fetch and manage structured content for any digital project.
- [Convertapi](https://composio.dev/toolkits/convertapi) - ConvertAPI is a robust file conversion service for documents, images, and spreadsheets. It streamlines programmatic format changes and lets developers automate complex workflows with a single API.
- [Craftmypdf](https://composio.dev/toolkits/craftmypdf) - CraftMyPDF is a web-based service for designing and generating PDFs with templates and live data. It streamlines document creation by automating personalized PDFs at scale.
- [Docmosis](https://composio.dev/toolkits/docmosis) - Docmosis generates PDF and Word documents from user-defined templates. It's perfect for merging data fields to quickly produce reports, invoices, and business letters.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Conversion tools MCP?

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

### Can I use Tool Router MCP with LlamaIndex?

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 Conversion tools tools.

### Can I manage the permissions and scopes for Conversion tools while using Tool Router?

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

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