How to integrate RAWG Video Games Database MCP with Autogen

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Introduction

This guide walks you through connecting RAWG Video Games Database to AutoGen using the Composio tool router. By the end, you'll have a working RAWG Video Games Database agent that can find top-rated rpg games released in 2023, list upcoming indie games for switch, get detailed info for elden ring through natural language commands.

This guide will help you understand how to give your AutoGen agent real control over a RAWG Video Games Database account through Composio's RAWG Video Games Database MCP server.

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

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 RAWG Video Games Database
  • Wire that MCP URL into Autogen using McpWorkbench and StreamableHttpServerParams
  • Configure an Autogen AssistantAgent that can call RAWG Video Games Database tools
  • Run a live chat loop where you ask the agent to perform RAWG Video Games Database 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 RAWG Video Games Database MCP server, and what's possible with it?

The RAWG Video Games Database MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your RAWG Video Games Database account. It provides structured and secure access so your agent can perform RAWG Video Games Database operations on your behalf.

Supported Tools & Triggers

Tools
Get Creator Roles ListTool to get a list of creator positions (jobs) in the gaming industry.
List Game CreatorsTool to get a list of game creators from the RAWG database.
Get Creator DetailsTool to get details of a specific creator.
List Game DevelopersTool to get a list of game developers from the RAWG database.
Get Developer DetailsTool to get details of a specific developer from the RAWG database.
Get Game AchievementsTool to get a list of achievements for a specific game.
Get Game Additions ListTool to get a list of DLCs, GOTY editions, companion apps, and other additions for a game.
Get Game Development Team ListTool to get a list of individual creators from the development team of a specific game.
Get Game Series ListTool to get a list of games that are part of the same series.
List GamesTool to get a list of games from RAWG database.
Get Game TrailersTool to get a list of game trailers and gameplay clips from the RAWG database.
Get Parent Games ListTool to get a list of parent games for DLCs and editions.
Get Game DetailsTool to get comprehensive details of a specific game.
Get Game Reddit PostsTool to get a list of most recent posts from a game's subreddit.
Get Game ScreenshotsTool to get screenshots for a specific game from the RAWG database.
Get Game Store LinksTool to get links to stores that sell a specific game.
List Video Game GenresTool to get a list of video game genres from RAWG database.
Get Genre DetailsTool to get details of a specific video game genre.
List Video Game PlatformsTool to get a list of video game platforms from RAWG database.
List Parent PlatformsTool to get a list of parent platforms from RAWG database.
Get Platform DetailsTool to get details of a specific gaming platform from the RAWG database.
List Video Game PublishersTool to get a list of video game publishers from the RAWG database.
Get Publisher DetailsTool to get details of a specific publisher from the RAWG database.
List Video Game StoresTool to get a list of video game storefronts.
Get Store DetailsTool to get details of a specific video game store.
List TagsTool to get a list of tags from the RAWG database.
Get Tag DetailsTool to get details of a specific tag from the RAWG database.

What is the Composio tool router, and how does it fit here?

What is Tool Router?

Composio's Tool Router 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 Tool Router

The tool router generates a secure MCP URL that your agents can access to perform actions.

How the Tool Router works

The Tool Router 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

Prerequisites

You will need:

  • A Composio API key
  • An OpenAI API key (used by Autogen's OpenAIChatCompletionClient)
  • A RAWG Video Games Database account you can connect to Composio
  • Some basic familiarity with Autogen and Python async

Getting API Keys for OpenAI and Composio

OpenAI API Key
  • Go to the OpenAI dashboard and create an API key. You'll need credits to use the models, or you can connect to another model provider.
  • Keep the API key safe.
Composio API Key
  • Log in to the Composio dashboard.
  • Navigate to your API settings and generate a new API key.
  • Store this key securely as you'll need it for authentication.

Install dependencies

bash
pip install composio python-dotenv
pip install autogen-agentchat autogen-ext-openai autogen-ext-tools

Install Composio, Autogen extensions, and dotenv.

What's happening:

  • composio connects your agent to RAWG Video Games Database via MCP
  • autogen-agentchat provides the AssistantAgent class
  • autogen-ext-openai provides the OpenAI model client
  • autogen-ext-tools provides MCP workbench support

Set up environment variables

bash
COMPOSIO_API_KEY=your-composio-api-key
OPENAI_API_KEY=your-openai-api-key
USER_ID=your-user-identifier@example.com

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 RAWG Video Games Database connections to use

Import dependencies and create Tool Router session

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 RAWG Video Games Database session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["rawg_video_games_database"]
    )
    url = session.mcp.url
What's happening:
  • load_dotenv() reads your .env file
  • Composio(api_key=...) initializes the SDK
  • create(...) creates a Tool Router session that exposes RAWG Video Games Database tools
  • session.mcp.url is the MCP endpoint that Autogen will connect to

Configure MCP parameters for Autogen

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")}
)

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

Create the model client and agent

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 RAWG Video Games Database assistant agent with MCP tools
    agent = AssistantAgent(
        name="rawg_video_games_database_assistant",
        description="An AI assistant that helps with RAWG Video Games Database operations.",
        model_client=model_client,
        workbench=workbench,
        model_client_stream=True,
        max_tool_iterations=10
    )

What's happening:

  • OpenAIChatCompletionClient wraps the OpenAI model for Autogen
  • McpWorkbench connects the agent to the MCP tools
  • AssistantAgent is configured with the RAWG Video Games Database tools from the workbench

Run the interactive chat loop

python
print("Chat started! Type 'exit' or 'quit' to end the conversation.\n")
print("Ask any RAWG Video Games Database 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")
What's happening:
  • The script prompts you in a loop with You:
  • Autogen passes your input to the model, which decides which RAWG Video Games Database 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

Complete Code

Here's the complete code to get you started with RAWG Video Games Database and AutoGen:

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 RAWG Video Games Database session
    composio = Composio(api_key=os.getenv("COMPOSIO_API_KEY"))
    session = composio.create(
        user_id=os.getenv("USER_ID"),
        toolkits=["rawg_video_games_database"]
    )
    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 RAWG Video Games Database assistant agent with MCP tools
        agent = AssistantAgent(
            name="rawg_video_games_database_assistant",
            description="An AI assistant that helps with RAWG Video Games Database 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 RAWG Video Games Database 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 RAWG Video Games Database 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 RAWG Video Games Database, you can reuse the same structure for other MCP-enabled apps with minimal code changes.

How to build RAWG Video Games Database MCP Agent with another framework

OpenAI Agents SDK

OpenAI Agents SDK

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Claude Agent SDK

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Google ADK

Google ADK

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LangChain

LangChain

Use RAWG Video Games Database MCP with LangChain

Vercel AI SDK

Vercel AI SDK

Use RAWG Video Games Database MCP with Vercel AI SDK

Mastra AI

Mastra AI

Use RAWG Video Games Database MCP with Mastra AI

LlamaIndex

LlamaIndex

Use RAWG Video Games Database MCP with LlamaIndex

CrewAI

CrewAI

Use RAWG Video Games Database MCP with CrewAI

Claude Code

Claude Code

Use RAWG Video Games Database MCP with Claude Code

Codex

Codex

Use RAWG Video Games Database MCP with Codex

FAQ

What are the differences in Tool Router MCP and RAWG Video Games Database MCP?

With a standalone RAWG Video Games Database MCP server, the agents and LLMs can only access a fixed set of RAWG Video Games Database tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from RAWG Video Games Database 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 RAWG Video Games Database tools.

Can I manage the permissions and scopes for RAWG Video Games Database while using Tool Router?

Yes, absolutely. You can configure which RAWG Video Games Database 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 RAWG Video Games Database data and credentials are handled as safely as possible.

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