# How to integrate RAWG Video Games Database MCP with LlamaIndex

```json
{
  "title": "How to integrate RAWG Video Games Database MCP with LlamaIndex",
  "toolkit": "RAWG Video Games Database",
  "toolkit_slug": "rawg_video_games_database",
  "framework": "LlamaIndex",
  "framework_slug": "llama-index",
  "url": "https://composio.dev/toolkits/rawg_video_games_database/framework/llama-index",
  "markdown_url": "https://composio.dev/toolkits/rawg_video_games_database/framework/llama-index.md",
  "updated_at": "2026-03-29T06:47:17.350Z"
}
```

## Introduction

This guide walks you through connecting RAWG Video Games Database to LlamaIndex 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 LlamaIndex 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.

## Also integrate RAWG Video Games Database with

- [OpenAI Agents SDK](https://composio.dev/toolkits/rawg_video_games_database/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/rawg_video_games_database/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/rawg_video_games_database/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/rawg_video_games_database/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/rawg_video_games_database/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/rawg_video_games_database/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/rawg_video_games_database/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/rawg_video_games_database/framework/cli)
- [Google ADK](https://composio.dev/toolkits/rawg_video_games_database/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/rawg_video_games_database/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/rawg_video_games_database/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/rawg_video_games_database/framework/mastra-ai)
- [CrewAI](https://composio.dev/toolkits/rawg_video_games_database/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 RAWG Video Games Database
- Connect LlamaIndex to the RAWG Video Games Database MCP server
- Build a RAWG Video Games Database-powered agent using LlamaIndex
- Interact with RAWG Video Games Database 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 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

| Tool slug | Name | Description |
|---|---|---|
| `RAWG_VIDEO_GAMES_DATABASE_CREATOR_ROLES_LIST` | Get Creator Roles List | Tool to get a list of creator positions (jobs) in the gaming industry. Use when you need to browse available creator roles or positions. |
| `RAWG_VIDEO_GAMES_DATABASE_CREATORS_LIST` | List Game Creators | Tool to get a list of game creators from the RAWG database. Use when you need to browse available creators or find specific game developers, designers, or other gaming industry professionals. Supports pagination via page and page_size parameters. |
| `RAWG_VIDEO_GAMES_DATABASE_CREATORS_READ` | Get Creator Details | Tool to get details of a specific creator. Use when you need detailed information about a game creator or person from the RAWG database. |
| `RAWG_VIDEO_GAMES_DATABASE_DEVELOPERS_LIST` | List Game Developers | Tool to get a list of game developers from the RAWG database. Use when you need to browse game developers or filter games by developer. Supports pagination via page and page_size parameters. |
| `RAWG_VIDEO_GAMES_DATABASE_GET_DEVELOPER_DETAILS` | Get Developer Details | Tool to get details of a specific developer from the RAWG database. Use when you need to retrieve information about a game developer by their unique ID. |
| `RAWG_VIDEO_GAMES_DATABASE_GET_GAME_ACHIEVEMENTS` | Get Game Achievements | Tool to get a list of achievements for a specific game. Use when you need to retrieve game achievements with names, descriptions, images, and completion percentages. |
| `RAWG_VIDEO_GAMES_DATABASE_GET_GAME_ADDITIONS_LIST` | Get Game Additions List | Tool to get a list of DLCs, GOTY editions, companion apps, and other additions for a game. Use when you need to find downloadable content or special editions for a specific game. |
| `RAWG_VIDEO_GAMES_DATABASE_GET_GAME_DEVELOPMENT_TEAM_LIST` | Get Game Development Team List | Tool to get a list of individual creators from the development team of a specific game. Use when you need to find out who worked on developing a particular game. |
| `RAWG_VIDEO_GAMES_DATABASE_GET_GAME_SERIES_LIST` | Get Game Series List | Tool to get a list of games that are part of the same series. Use when you need to find all games in a franchise or series related to a specific game. |
| `RAWG_VIDEO_GAMES_DATABASE_LIST_GAMES` | List Games | Tool to get a list of games from RAWG database. Use when you need to browse, search, or filter games with extensive options including platforms, genres, release dates, ratings, and more. Supports pagination and custom ordering. |
| `RAWG_VIDEO_GAMES_DATABASE_GET_GAME_TRAILERS` | Get Game Trailers | Tool to get a list of game trailers and gameplay clips from the RAWG database. Use when you need to retrieve video content for a specific game including preview thumbnails and video URLs at different quality levels. Note that not all games have associated trailer data. |
| `RAWG_VIDEO_GAMES_DATABASE_GET_PARENT_GAMES_LIST` | Get Parent Games List | Tool to get a list of parent games for DLCs and editions. Use when you need to identify the main or base game for a DLC, expansion, or special edition. |
| `RAWG_VIDEO_GAMES_DATABASE_GET_GAME_DETAILS` | Get Game Details | Tool to get comprehensive details of a specific game. Use when you need detailed information about a game including ratings, platforms, descriptions, and metadata. |
| `RAWG_VIDEO_GAMES_DATABASE_GET_GAME_REDDIT_POSTS` | Get Game Reddit Posts | Tool to get a list of most recent posts from a game's subreddit. Use when you need to retrieve Reddit discussions, community posts, and social media content related to a specific game. |
| `RAWG_VIDEO_GAMES_DATABASE_GET_GAME_SCREENSHOTS` | Get Game Screenshots | Tool to get screenshots for a specific game from the RAWG database. Use when you need to retrieve game screenshots with image URLs, dimensions, and visibility status. Supports pagination and custom ordering. |
| `RAWG_VIDEO_GAMES_DATABASE_GET_GAME_STORE_LINKS` | Get Game Store Links | Tool to get links to stores that sell a specific game. Use when you need to find where to purchase a game from digital storefronts. |
| `RAWG_VIDEO_GAMES_DATABASE_LIST_VIDEO_GAME_GENRES` | List Video Game Genres | Tool to get a list of video game genres from RAWG database. Use when you need to browse available genres or filter games by genre. Supports pagination and custom ordering. |
| `RAWG_VIDEO_GAMES_DATABASE_GET_GENRE_DETAILS` | Get Genre Details | Tool to get details of a specific video game genre. Use when you need information about a particular genre including its name, description, and game count. |
| `RAWG_VIDEO_GAMES_DATABASE_LIST_VIDEO_GAME_PLATFORMS` | List Video Game Platforms | Tool to get a list of video game platforms from RAWG database. Use when you need to browse available gaming platforms from PC to mobile. Supports pagination and custom ordering. |
| `RAWG_VIDEO_GAMES_DATABASE_LIST_PARENT_PLATFORMS` | List Parent Platforms | Tool to get a list of parent platforms from RAWG database. Use when you need to browse platform families like PlayStation, Xbox, or PC that group related gaming platforms together. For instance, PlayStation groups PS1, PS2, PS3, PS4, and PS5. |
| `RAWG_VIDEO_GAMES_DATABASE_GET_PLATFORM_DETAILS` | Get Platform Details | Tool to get details of a specific gaming platform from the RAWG database. Use when you need information about a particular platform including its name, launch year, and game count. |
| `RAWG_VIDEO_GAMES_DATABASE_LIST_VIDEO_GAME_PUBLISHERS` | List Video Game Publishers | Tool to get a list of video game publishers from the RAWG database. Use when you need to browse game publishers or filter games by publisher. Supports pagination via page and page_size parameters. |
| `RAWG_VIDEO_GAMES_DATABASE_GET_PUBLISHER_DETAILS` | Get Publisher Details | Tool to get details of a specific publisher from the RAWG database. Use when you need to retrieve information about a game publisher by their unique ID. |
| `RAWG_VIDEO_GAMES_DATABASE_LIST_VIDEO_GAME_STORES` | List Video Game Stores | Tool to get a list of video game storefronts. Use when you need to browse digital distribution services where games can be purchased. Supports pagination and ordering options. |
| `RAWG_VIDEO_GAMES_DATABASE_GET_STORE_DETAILS` | Get Store Details | Tool to get details of a specific video game store. Use when you need information about a particular storefront including its name, domain, and game count. |
| `RAWG_VIDEO_GAMES_DATABASE_LIST_TAGS` | List Tags | Tool to get a list of tags from the RAWG database. Use when you need to browse tags that categorize games by specific characteristics. Supports pagination via page and page_size parameters. |
| `RAWG_VIDEO_GAMES_DATABASE_GET_TAG_DETAILS` | Get Tag Details | Tool to get details of a specific tag from the RAWG database. Use when you need detailed information about a particular tag including its name, games count, and description. |

## Supported Triggers

None listed.

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

The RAWG Video Games Database MCP server is an implementation of the Model Context Protocol that connects your AI agent to RAWG Video Games Database. It provides structured and secure access so your agent can perform RAWG Video Games Database 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 RAWG Video Games Database account and project
- Basic familiarity with async Python/Typescript

### 1. Getting API Keys for OpenAI, Composio, and RAWG Video Games Database

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 RAWG Video Games Database 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, rawg video games database)
- 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 RAWG Video Games Database 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=["rawg_video_games_database"],
    )

    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 RAWG Video Games Database actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform RAWG Video Games Database 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: ["rawg_video_games_database"],
    },
  );

  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 RAWG Video Games Database 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 RAWG Video Games Database
```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 RAWG Video Games Database, 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=["rawg_video_games_database"],
    )

    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 RAWG Video Games Database actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform RAWG Video Games Database 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: ["rawg_video_games_database"],
    },
  );

  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 RAWG Video Games Database 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 RAWG Video Games Database to LlamaIndex through Composio's Tool Router MCP layer.
Key takeaways:
- Tool Router dynamically exposes RAWG Video Games Database 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 RAWG Video Games Database MCP Agent with another framework

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

## Related Toolkits

- [Youtube](https://composio.dev/toolkits/youtube) - YouTube is a leading video-sharing platform for uploading, streaming, and discovering content. It empowers creators and businesses to reach global audiences and monetize their work.
- [Amara](https://composio.dev/toolkits/amara) - Amara is a collaborative platform for creating and managing subtitles and captions for videos. It helps make content accessible and multilingual for global audiences.
- [Cats](https://composio.dev/toolkits/cats) - Cats is an API with a huge library of cat images, breed data, and cat facts. It makes finding adorable cat photos and trivia effortless for your apps and users.
- [Chatfai](https://composio.dev/toolkits/chatfai) - Chatfai is an AI platform that lets users talk to AI versions of fictional characters from books, movies, and games. It offers an engaging, interactive experience for fans to chat, roleplay, and explore creative dialogues.
- [Cincopa](https://composio.dev/toolkits/cincopa) - Cincopa is a multimedia platform for uploading, managing, and customizing videos, images, and audio. It helps you deliver engaging media experiences with robust APIs and flexible integrations.
- [Dungeon fighter online](https://composio.dev/toolkits/dungeon_fighter_online) - Dungeon Fighter Online (DFO) is an arcade-style, side-scrolling action RPG packed with dynamic combat and progression. Play solo or with friends to battle monsters, complete quests, and upgrade your characters.
- [Elevenlabs](https://composio.dev/toolkits/elevenlabs) - Elevenlabs is an advanced AI voice generation platform for lifelike, multilingual speech synthesis. Perfect for creating natural voices for videos, apps, and business content in seconds.
- [Elevenreader](https://composio.dev/toolkits/elevenreader) - Elevenreader is an AI-powered text-to-speech service by ElevenLabs that converts written content into lifelike audio. It enables fast, natural audio generation from any text.
- [Epic games](https://composio.dev/toolkits/epic_games) - Epic Games is a leading video game publisher and digital storefront, known for Fortnite and Unreal Engine. It lets gamers access, manage, and purchase games all in one place.
- [Fal.ai](https://composio.dev/toolkits/fal_ai) - Fal.ai is a generative media platform offering 600+ AI models for images, video, voice, and audio. Developers use Fal.ai for fast, scalable access to cutting-edge generative AI tools.
- [Giphy](https://composio.dev/toolkits/giphy) - Giphy is the largest online library for searching and sharing GIFs and stickers. Instantly add vibrant animated content to your apps, chats, and workflows.
- [Headout](https://composio.dev/toolkits/headout) - Headout is a global platform for booking travel experiences, tours, and entertainment. It helps users discover and secure activities at top destinations, all in one place.
- [Imagekit io](https://composio.dev/toolkits/imagekit_io) - ImageKit.io is a cloud-based media management platform for image and video delivery. Instantly optimize, transform, and deliver visuals globally via a lightning-fast CDN.
- [Listennotes](https://composio.dev/toolkits/listennotes) - Listennotes is a powerful podcast search engine with a massive global database. Discover, search, and curate podcasts from around the world in seconds.
- [News api](https://composio.dev/toolkits/news_api) - News api is a REST API for searching and retrieving live news articles from across the web. Instantly access headlines, coverage, and breaking stories from thousands of sources.
- [Seat geek](https://composio.dev/toolkits/seat_geek) - SeatGeek is a live event platform offering APIs for concerts, sports, and theater data. Instantly access events, venues, and performers info for smarter ticketing and discovery.
- [Shotstack](https://composio.dev/toolkits/shotstack) - Shotstack is a cloud platform for programmatically generating videos, images, and audio. Automate creative content production at scale with flexible RESTful APIs.
- [Spotify](https://composio.dev/toolkits/spotify) - Spotify is a streaming service for music and podcasts with millions of tracks from artists worldwide. Enjoy personalized playlists, recommendations, and seamless listening across all your devices.
- [Ticketmaster](https://composio.dev/toolkits/ticketmaster) - Ticketmaster is a global platform for event discovery, ticket sales, and live entertainment management. Get real-time access to events and streamline ticketing for fans and organizers.
- [Gmail](https://composio.dev/toolkits/gmail) - Gmail is Google's email service with powerful spam protection, search, and G Suite integration. It keeps your inbox organized and makes communication fast and reliable.

## Frequently Asked Questions

### 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 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 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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