# How to integrate Shorten rest MCP with Autogen

```json
{
  "title": "How to integrate Shorten rest MCP with Autogen",
  "toolkit": "Shorten rest",
  "toolkit_slug": "shorten_rest",
  "framework": "AutoGen",
  "framework_slug": "autogen",
  "url": "https://composio.dev/toolkits/shorten_rest/framework/autogen",
  "markdown_url": "https://composio.dev/toolkits/shorten_rest/framework/autogen.md",
  "updated_at": "2026-05-12T10:26:02.046Z"
}
```

## Introduction

This guide walks you through connecting Shorten rest to AutoGen using the Composio tool router. By the end, you'll have a working Shorten rest agent that can shorten this long marketing campaign url, create branded short link for event signup, track click stats for your recent short link through natural language commands.
This guide will help you understand how to give your AutoGen agent real control over a Shorten rest account through Composio's Shorten rest MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Shorten rest with

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

## TL;DR

Here's what you'll learn:
- Get and set up your OpenAI and Composio API keys
- Install the required dependencies for Autogen and Composio
- Initialize Composio and create a Tool Router session for Shorten rest
- Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
- Configure an Autogen AssistantAgent that can call Shorten rest tools
- Run a live chat loop where you ask the agent to perform Shorten rest operations

## What is AutoGen?

Autogen is a framework for building multi-agent conversational AI systems from Microsoft. It enables you to create agents that can collaborate, use tools, and maintain complex workflows.
Key features include:
- Multi-Agent Systems: Build collaborative agent workflows
- MCP Workbench: Native support for Model Context Protocol tools
- Streaming HTTP: Connect to external services through streamable HTTP
- AssistantAgent: Pre-built agent class for tool-using assistants

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

The Shorten rest MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Shorten.REST account. It provides structured and secure access to your link management tools, so your agent can perform actions like creating short URLs, managing branded links, tracking analytics, and organizing your shortened links on your behalf.
- Instant URL shortening: Ask your agent to quickly generate shortened links for any URL with just a command.
- Branded link creation: Let your agent create custom, branded short URLs to match your organization's identity.
- Analytics and click tracking: Retrieve detailed analytics on link clicks, usage trends, and engagement metrics directly through your agent.
- Link organization and management: Have your agent list, update, or delete your shortened links to keep your link library organized and up-to-date.
- Bulk link processing: Enable your agent to handle multiple URL shortening or management tasks in a single workflow, saving you valuable time.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `SHORTEN_REST_CREATE_ALIAS` | Create Alias | Tool to create a new alias (short URL) under a specified domain. Use when you need to shorten a URL. If no domain is specified, the alias will be attached to the default domain Short.fyi. You can override domain-level Meta Tags and Tracking Snippets by specifying them for each URL. |
| `SHORTEN_REST_DELETE_ALIAS` | Delete Alias | Tool to delete a single alias by providing alias and domain. Use when you need to remove an existing shortened URL. If no domain is provided, the API searches for the matching alias within the Short.fyi domain. |
| `SHORTEN_REST_GET_ALIASES` | Get Aliases | Tool to retrieve all URL aliases of the authenticated user. Use when you need to list existing aliases (supports pagination). |
| `SHORTEN_REST_GET_CLICKS` | Get click data for aliases | Tool to retrieve click data for shortened URLs. Use to check click analytics for your aliases. Returns a list of click records which may be empty if no clicks have occurred yet. Returned records may represent a limited window or subset of historical clicks rather than complete per-click logs. |
| `SHORTEN_REST_LIST_ALIASES_BY_DOMAIN` | List aliases by domain | Tool to retrieve all alias names associated with your account and a given domain. Results are in descending order by creation date. Use when you need to list alias names (not full details) for a specific domain with pagination support. |
| `SHORTEN_REST_UPDATE_ALIAS` | Update Alias | Tool to update an existing short URL alias by providing its alias name and domain. Use when you need to modify destinations, metatags, or snippets for an existing alias. IMPORTANT: When updating array properties (like destinations), the entire array is replaced, so you must include all existing records you want to keep. |

## Supported Triggers

None listed.

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

The Shorten rest MCP server is an implementation of the Model Context Protocol that connects your AI agents and assistants directly to Shorten rest. Instead of manually wiring Shorten rest APIs, OAuth, and scopes yourself, you get a structured, tool-based interface that an LLM can call safely.
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

You will need:
- A Composio API key
- An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
- A Shorten rest account you can connect to Composio
- Some basic familiarity with Autogen and Python async

### 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).
- Navigate to your API settings and generate a new API key.
- Store this key securely as you'll need it for authentication.

### 2. Install dependencies

Install Composio, Autogen extensions, and dotenv.
What's happening:
- composio connects your agent to Shorten rest via MCP
- autogen-agentchat provides the AssistantAgent class
- autogen-ext-openai provides the OpenAI model client
- autogen-ext-tools provides MCP workbench support
```bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools
```

### 3. Set up environment variables

Create a .env file in your project folder.
What's happening:
- COMPOSIO_API_KEY is required to talk to Composio
- OPENAI_API_KEY is used by Autogen's OpenAI client
- USER_ID is how Composio identifies which user's Shorten rest connections to use
```bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com
```

### 4. Import dependencies and create Tool Router session

What's happening:
- load_dotenv() reads your .env file
- Composio(api_key=...) initializes the SDK
- create(...) creates a Tool Router session that exposes Shorten rest tools
- session.mcp.url is the MCP endpoint that Autogen will connect to
```python
import asyncio
import os
from dotenv import load_dotenv
from composio import Composio

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Shorten rest session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["shorten_rest"]
    )
    url = session.mcp.url
```

### 5. Configure MCP parameters for Autogen

Autogen expects parameters describing how to talk to the MCP server. That is what StreamableHttpServerParams is for.
What's happening:
- url points to the Tool Router MCP endpoint from Composio
- timeout is the HTTP timeout for requests
- sse_read_timeout controls how long to wait when streaming responses
- terminate_on_close=True cleans up the MCP server process when the workbench is closed
```python
# Configure MCP server parameters for Streamable HTTP
server_params = StreamableHttpServerParams(
    url=url,
    timeout=30.0,
    sse_read_timeout=300.0,
    terminate_on_close=True,
    headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
)
```

### 6. Create the model client and agent

What's happening:
- OpenAIChatCompletionClient wraps the OpenAI model for Autogen
- McpWorkbench connects the agent to the MCP tools
- AssistantAgent is configured with the Shorten rest tools from the workbench
```python
# Create model client
model_client = OpenAIChatCompletionClient(
    model="gpt-5",
    api_key=os.getenv("OPENAI_API_KEY")
)

# Use McpWorkbench as context manager
async with McpWorkbench(server_params) as workbench:
    # Create Shorten rest assistant agent with MCP tools
    agent = AssistantAgent(
        name="shorten_rest_assistant",
        description="An AI assistant that helps with Shorten rest operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )
```

### 7. Run the interactive chat loop

What's happening:
- The script prompts you in a loop with You:
- Autogen passes your input to the model, which decides which Shorten rest tools to call via MCP
- agent.run_stream(...) yields streaming messages as the agent thinks and calls tools
- Typing exit, quit, or bye ends the loop
```python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any Shorten rest related question or task to the agent.\n")

# Conversation loop
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")

    # Run the agent with streaming
    try:
        response_text = ""
        async for message in agent.run_stream(task=user_input):
            if hasattr(message, "content") and message.content:
                response_text = message.content

        # Print the final response
        if response_text:
            print(f"Agent: {response_text}\n")
        else:
            print("Agent: I encountered an issue processing your request.\n")

    except Exception as e:
        print(f"Agent: Sorry, I encountered an error: {str(e)}\n")
```

## Complete Code

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

from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient
from autogen_ext.tools.mcp import McpWorkbench, StreamableHttpServerParams

load_dotenv()

async def main():
    # Initialize Composio and create a Shorten rest session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["shorten_rest"]
    )
    url = session.mcp.url

    # Configure MCP server parameters for Streamable HTTP
    server_params = StreamableHttpServerParams(
        url=url,
        timeout=30.0,
        sse_read_timeout=300.0,
        terminate_on_close=True,
        headers={"x-api-key": os.getenv("COMPOSIO_API_KEY")}
    )

    # Create model client
    model_client = OpenAIChatCompletionClient(
        model="gpt-5",
        api_key=os.getenv("OPENAI_API_KEY")
    )

    # Use McpWorkbench as context manager
    async with McpWorkbench(server_params) as workbench:
        # Create Shorten rest assistant agent with MCP tools
        agent = AssistantAgent(
            name="shorten_rest_assistant",
            description="An AI assistant that helps with Shorten rest operations.",
            model_client=model_client,
            workbench=workbench,
            model_client_stream=True,
            max_tool_iterations=10
        )

        print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
        print("Ask any Shorten rest related question or task to the agent.\n")

        # Conversation loop
        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")

            # Run the agent with streaming
            try:
                response_text = ""
                async for message in agent.run_stream(task=user_input):
                    if hasattr(message, 'content') and message.content:
                        response_text = message.content

                # Print the final response
                if response_text:
                    print(f"Agent: {response_text}\n")
                else:
                    print("Agent: I encountered an issue processing your request.\n")

            except Exception as e:
                print(f"Agent: Sorry, I encountered an error: {str(e)}\n")

if __name__ == "__main__":
    asyncio.run(main())
```

## Conclusion

You now have an Autogen assistant wired into Shorten rest through Composio's Tool Router and MCP. From here you can:
- Add more toolkits to the toolkits list, for example notion or hubspot
- Refine the agent description to point it at specific workflows
- Wrap this script behind a UI, Slack bot, or internal tool
Once the pattern is clear for Shorten rest, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

## How to build Shorten rest MCP Agent with another framework

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

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## Frequently Asked Questions

### What are the differences in Tool Router MCP and Shorten rest MCP?

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

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

Yes, you can. Autogen 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 Shorten rest tools.

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

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

---
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