# How to integrate Docmosis MCP with OpenAI Agents SDK

```json
{
  "title": "How to integrate Docmosis MCP with OpenAI Agents SDK",
  "toolkit": "Docmosis",
  "toolkit_slug": "docmosis",
  "framework": "OpenAI Agents SDK",
  "framework_slug": "open-ai-agents-sdk",
  "url": "https://composio.dev/toolkits/docmosis/framework/open-ai-agents-sdk",
  "markdown_url": "https://composio.dev/toolkits/docmosis/framework/open-ai-agents-sdk.md",
  "updated_at": "2026-05-12T10:09:06.847Z"
}
```

## Introduction

This guide walks you through connecting Docmosis to the OpenAI Agents SDK using the Composio tool router. By the end, you'll have a working Docmosis agent that can generate monthly invoice pdf for a customer, create personalized offer letters for new hires, produce event registration forms as word docs through natural language commands.
This guide will help you understand how to give your OpenAI Agents SDK agent real control over a Docmosis account through Composio's Docmosis MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Docmosis with

- [Claude Agent SDK](https://composio.dev/toolkits/docmosis/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/docmosis/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/docmosis/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/docmosis/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/docmosis/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/docmosis/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/docmosis/framework/cli)
- [Google ADK](https://composio.dev/toolkits/docmosis/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/docmosis/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/docmosis/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/docmosis/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/docmosis/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/docmosis/framework/crew-ai)

## TL;DR

Here's what you'll learn:
- Get and set up your OpenAI and Composio API keys
- Install the necessary dependencies
- Initialize Composio and create a Tool Router session for Docmosis
- Configure an AI agent that can use Docmosis as a tool
- Run a live chat session where you can ask the agent to perform Docmosis operations

## What is OpenAI Agents SDK?

The OpenAI Agents SDK is a lightweight framework for building AI agents that can use tools and maintain conversation state. It provides a simple interface for creating agents with hosted MCP tool support.
Key features include:
- Hosted MCP Tools: Connect to external services through hosted MCP endpoints
- SQLite Sessions: Persist conversation history across interactions
- Simple API: Clean interface with Agent, Runner, and tool configuration
- Streaming Support: Real-time response streaming for interactive applications

## What is the Docmosis MCP server, and what's possible with it?

The Docmosis MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Docmosis account. It provides structured and secure access to your document templates and generation capabilities, so your agent can perform actions like generating documents, merging data fields, exporting PDFs or Word files, and automating report creation on your behalf.
- Dynamic document generation: Instantly create PDF or Word documents from pre-built templates by merging in your custom data fields.
- Automated report and invoice creation: Let your agent assemble business reports, invoices, or letters using real-time input and reusable templates.
- Template management and selection: Retrieve, list, and select from available templates for different document types or business needs.
- Batch document processing: Generate multiple documents at once by feeding bulk data sets—perfect for automating repetitive paperwork.
- Flexible file export and delivery: Export generated documents in your preferred format and deliver them to specified locations, systems, or users automatically.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `DOCMOSIS_DELETE_IMAGE` | Docmosis: Delete Image(s) | Tool to delete one or more stored images. Use when you need to remove images; ensure imageName(s) are valid before use. |
| `DOCMOSIS_DELETE_TEMPLATE` | Docmosis: Delete Template(s) | Tool to delete one or more templates from the environment. Use when you need to remove templates; multiple templates can be deleted in a single request. |
| `DOCMOSIS_ENVIRONMENT_READY` | Docmosis Environment Ready | Tool to verify environment readiness. Use when ensuring the environment is active and within quota before rendering documents. |
| `DOCMOSIS_ENVIRONMENT_SUMMARY` | Docmosis Environment Summary | Tool to retrieve environment summary. Use when you need status, plan, and quota details of your Docmosis environment after authentication. |
| `DOCMOSIS_GET_API_KEY` | Docmosis: Get API Key | Tool to extract the Docmosis API access key from connection metadata. Use before other Docmosis API calls to retrieve the Bearer token from the Authorization header. |
| `DOCMOSIS_GET_BATCH_UPLOAD_STATUS` | Get Batch Upload Status | Tool to check the status of a template batch upload job. Use when monitoring batch upload progress or checking if a batch upload has completed. |
| `DOCMOSIS_GET_IMAGE` | Download Docmosis Images | Tool to download one or more images. Use when you need to retrieve stored image files by name. If multiple names provided, images are returned in a zip archive. |
| `DOCMOSIS_GET_RENDER_QUEUE` | Get Docmosis Render Queue | Tool to get current render queue status and utilization. Use when monitoring queue capacity before scheduling rendering tasks. |
| `DOCMOSIS_GET_RENDER_TAGS` | Get Render Tags | Tool to retrieve statistics on renders tagged with user-defined phrases. Returns page counts and document counts aggregated monthly. Use when reporting activity of user groups or features. |
| `DOCMOSIS_GET_SAMPLE_DATA` | Get Template Sample Data | Tool to generate sample data for a Docmosis template based on its structure. Creates placeholder values that can be used for testing renders. Returns data in JSON or XML format. |
| `DOCMOSIS_GET_TEMPLATE` | Download Docmosis Templates | Tool to retrieve originally uploaded templates. Use when you need to download template files by name. If multiple names provided (up to 100), templates are returned in a zip archive. |
| `DOCMOSIS_GET_TEMPLATE_DETAILS` | Get Docmosis Template Details | Tool to retrieve metadata for an uploaded template. Returns name, size, MD5 hash, last modified date, and error status. Use after uploading a template to verify it was stored correctly or to check if it has errors. |
| `DOCMOSIS_GET_TEMPLATE_STRUCTURE` | Get Docmosis Template Structure | Tool to retrieve a template's parsed structure: fields, repeats, conditions, images, and refs. Use after uploading a template to inspect its JSON structure. |
| `DOCMOSIS_LIST_IMAGES` | Docmosis: List Images | Tool to list available stock images. Use when you need to retrieve image names optionally filtered by folder. |
| `DOCMOSIS_LIST_TEMPLATES` | Docmosis: List Templates | Tool to list all templates available in the environment. Use when you need to retrieve template names, optionally filtered by folder with pagination support. |
| `DOCMOSIS_PING` | Docmosis Ping | Tool to check connectivity to Docmosis Cloud services. Use when validating that the service endpoint is reachable before other operations. |
| `DOCMOSIS_PING_DOCMOSIS_SERVICE` | Ping Docmosis Service | Tool to check that Docmosis Cloud services are online and at least one server is listening. Use for diagnostics and monitoring to verify service availability. |

## Supported Triggers

None listed.

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

The Docmosis MCP server is an implementation of the Model Context Protocol that connects your AI agent to Docmosis. It provides structured and secure access so your agent can perform Docmosis 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 starting, make sure you have:
- Composio API Key and OpenAI API Key
- Primary know-how of OpenAI Agents SDK
- A live Docmosis project
- Some knowledge of Python or Typescript

### 1. Getting API Keys for OpenAI and Composio

OpenAI API Key
- Go to the [OpenAI dashboard](https://platform.openai.com/settings/organization/api-keys) 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](https://dashboard.composio.dev?utm_source=toolkits&utm_medium=framework_docs).
- Go to Settings and copy your API key.

### 2. Install dependencies

Install the Composio SDK and the OpenAI Agents SDK.
```python
pip install composio_openai_agents openai-agents python-dotenv
```

```typescript
npm install @composio/openai-agents @openai/agents dotenv
```

### 3. Set up environment variables

Create a .env file and add your OpenAI and Composio API keys.
```bash
OPENAI_API_KEY=sk-...your-api-key
COMPOSIO_API_KEY=your-api-key
USER_ID=composio_user@gmail.com
```

### 4. Import dependencies

What's happening:
- You're importing all necessary libraries.
- The Composio and OpenAIAgentsProvider classes are imported to connect your OpenAI agent to Composio tools like Docmosis.
```python
import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';
```

### 5. Set up the Composio instance

No description provided.
```python
load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())
```

```typescript
dotenv.config();

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});
```

### 6. Create a Tool Router session

What is happening:
- You give the Tool Router the user id and the toolkits you want available. Here, it is only docmosis.
- The router checks the user's Docmosis connection and prepares the MCP endpoint.
- The returned session.mcp.url is the MCP URL that your agent will use to access Docmosis.
- This approach keeps things lightweight and lets the agent request Docmosis tools only when needed during the conversation.
```python
# Create a Docmosis Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["docmosis"]
)

mcp_url = session.mcp.url
```

```typescript
// Create Tool Router session for Docmosis
const session = await composio.create(userId as string, {
  toolkits: ['docmosis'],
});
const mcpUrl = session.mcp.url;
```

### 7. Configure the agent

No description provided.
```python
# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Docmosis. "
        "Help users perform Docmosis operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)
```

```typescript
// Configure agent with MCP tool
const agent = new Agent({
  name: 'Assistant',
  model: 'gpt-5',
  instructions:
    'You are a helpful assistant that can access Docmosis. Help users perform Docmosis operations through natural language.',
  tools: [
    hostedMcpTool({
      serverLabel: 'tool_router',
      serverUrl: mcpUrl,
      headers: { 'x-api-key': composioApiKey },
      requireApproval: 'never',
    }),
  ],
});
```

### 8. Start chat loop and handle conversation

No description provided.
```python
print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
```

```typescript
// Keep conversation state across turns
const conversationSession = new OpenAIConversationsSession();

// Simple CLI
const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout,
  prompt: 'You: ',
});

console.log('\nComposio Tool Router session created.');
console.log('\nChat started. Type your requests below.');
console.log("Commands: 'exit', 'quit', or 'q' to end\n");

try {
  const first = await run(agent, 'What can you help me with?', { session: conversationSession });
  console.log(`Assistant: ${first.finalOutput}\n`);
} catch (e) {
  console.error('Error:', e instanceof Error ? e.message : e, '\n');
}

rl.prompt();

rl.on('line', async (userInput) => {
  const text = userInput.trim();

  if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
    console.log('Goodbye!');
    rl.close();
    process.exit(0);
  }

  if (!text) {
    rl.prompt();
    return;
  }

  try {
    const result = await run(agent, text, { session: conversationSession });
    console.log(`\nAssistant: ${result.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();
});

rl.on('close', () => {
  console.log('\n👋 Session ended.');
  process.exit(0);
});
```

## Complete Code

```python
import asyncio
import os
from dotenv import load_dotenv

from composio import Composio
from composio_openai_agents import OpenAIAgentsProvider
from agents import Agent, Runner, HostedMCPTool, SQLiteSession

load_dotenv()

api_key = os.getenv("COMPOSIO_API_KEY")
user_id = os.getenv("USER_ID")

if not api_key:
    raise RuntimeError("COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key")

# Initialize Composio
composio = Composio(api_key=api_key, provider=OpenAIAgentsProvider())

# Create Tool Router session
session = composio.create(
    user_id=user_id,
    toolkits=["docmosis"]
)
mcp_url = session.mcp.url

# Configure agent with MCP tool
agent = Agent(
    name="Assistant",
    model="gpt-5",
    instructions=(
        "You are a helpful assistant that can access Docmosis. "
        "Help users perform Docmosis operations through natural language."
    ),
    tools=[
        HostedMCPTool(
            tool_config={
                "type": "mcp",
                "server_label": "tool_router",
                "server_url": mcp_url,
                "headers": {"x-api-key": api_key},
                "require_approval": "never",
            }
        )
    ],
)

print("\nComposio Tool Router session created.")

chat_session = SQLiteSession("conversation_openai_toolrouter")

print("\nChat started. Type your requests below.")
print("Commands: 'exit', 'quit', or 'q' to end\n")

async def main():
    try:
        result = await Runner.run(
            agent,
            "What can you help me with?",
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")
    except Exception as e:
        print(f"Error: {e}\n")

    while True:
        user_input = input("You: ").strip()
        if user_input.lower() in {"exit", "quit", "q"}:
            print("Goodbye!")
            break

        result = await Runner.run(
            agent,
            user_input,
            session=chat_session
        )
        print(f"Assistant: {result.final_output}\n")

asyncio.run(main())
```

```typescript
import 'dotenv/config';
import { Composio } from '@composio/core';
import { OpenAIAgentsProvider } from '@composio/openai-agents';
import { Agent, hostedMcpTool, run, OpenAIConversationsSession } from '@openai/agents';
import * as readline from 'readline';

const composioApiKey = process.env.COMPOSIO_API_KEY;
const userId = process.env.USER_ID;

if (!composioApiKey) {
  throw new Error('COMPOSIO_API_KEY is not set. Create a .env file with COMPOSIO_API_KEY=your_key');
}
if (!userId) {
  throw new Error('USER_ID is not set');
}

// Initialize Composio
const composio = new Composio({
  apiKey: composioApiKey,
  provider: new OpenAIAgentsProvider(),
});

async function main() {
  // Create Tool Router session
  const session = await composio.create(userId as string, {
    toolkits: ['docmosis'],
  });
  const mcpUrl = session.mcp.url;

  // Configure agent with MCP tool
  const agent = new Agent({
    name: 'Assistant',
    model: 'gpt-5',
    instructions:
      'You are a helpful assistant that can access Docmosis. Help users perform Docmosis operations through natural language.',
    tools: [
      hostedMcpTool({
        serverLabel: 'tool_router',
        serverUrl: mcpUrl,
        headers: { 'x-api-key': composioApiKey },
        requireApproval: 'never',
      }),
    ],
  });

  // Keep conversation state across turns
  const conversationSession = new OpenAIConversationsSession();

  // Simple CLI
  const rl = readline.createInterface({
    input: process.stdin,
    output: process.stdout,
    prompt: 'You: ',
  });

  console.log('\nComposio Tool Router session created.');
  console.log('\nChat started. Type your requests below.');
  console.log("Commands: 'exit', 'quit', or 'q' to end\n");

  try {
    const first = await run(agent, 'What can you help me with?', { session: conversationSession });
    console.log(`Assistant: ${first.finalOutput}\n`);
  } catch (e) {
    console.error('Error:', e instanceof Error ? e.message : e, '\n');
  }

  rl.prompt();

  rl.on('line', async (userInput) => {
    const text = userInput.trim();

    if (['exit', 'quit', 'q'].includes(text.toLowerCase())) {
      console.log('Goodbye!');
      rl.close();
      process.exit(0);
    }

    if (!text) {
      rl.prompt();
      return;
    }

    try {
      const result = await run(agent, text, { session: conversationSession });
      console.log(`\nAssistant: ${result.finalOutput}\n`);
    } catch (e) {
      console.error('Error:', e instanceof Error ? e.message : e, '\n');
    }

    rl.prompt();
  });

  rl.on('close', () => {
    console.log('\nSession ended.');
    process.exit(0);
  });
}

main().catch((err) => {
  console.error('Fatal error:', err);
  process.exit(1);
});
```

## Conclusion

This was a starter code for integrating Docmosis MCP with OpenAI Agents SDK to build a functional AI agent that can interact with Docmosis.
Key features:
- Hosted MCP tool integration through Composio's Tool Router
- SQLite session persistence for conversation history
- Simple async chat loop for interactive testing
You can extend this by adding more toolkits, implementing custom business logic, or building a web interface around the agent.

## How to build Docmosis MCP Agent with another framework

- [Claude Agent SDK](https://composio.dev/toolkits/docmosis/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/docmosis/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/docmosis/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/docmosis/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/docmosis/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/docmosis/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/docmosis/framework/cli)
- [Google ADK](https://composio.dev/toolkits/docmosis/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/docmosis/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/docmosis/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/docmosis/framework/mastra-ai)
- [LlamaIndex](https://composio.dev/toolkits/docmosis/framework/llama-index)
- [CrewAI](https://composio.dev/toolkits/docmosis/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.
- [Conversion tools](https://composio.dev/toolkits/conversion_tools) - Conversion Tools is an online service for converting documents between formats such as PDF, Word, Excel, XML, and CSV. It lets you automate complex document workflows with just a few clicks.
- [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.

## Frequently Asked Questions

### What are the differences in Tool Router MCP and Docmosis MCP?

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

### Can I use Tool Router MCP with OpenAI Agents SDK?

Yes, you can. OpenAI Agents SDK 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 Docmosis tools.

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

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

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