# How to integrate Epic games MCP with LlamaIndex

```json
{
  "title": "How to integrate Epic games MCP with LlamaIndex",
  "toolkit": "Epic games",
  "toolkit_slug": "epic_games",
  "framework": "LlamaIndex",
  "framework_slug": "llama-index",
  "url": "https://composio.dev/toolkits/epic_games/framework/llama-index",
  "markdown_url": "https://composio.dev/toolkits/epic_games/framework/llama-index.md",
  "updated_at": "2026-05-12T10:10:32.809Z"
}
```

## Introduction

This guide walks you through connecting Epic games to LlamaIndex using the Composio tool router. By the end, you'll have a working Epic games agent that can list your recently purchased epic games titles, show current fortnite store offers, check your unreal engine license details through natural language commands.
This guide will help you understand how to give your LlamaIndex agent real control over a Epic games account through Composio's Epic games MCP server.
Before we dive in, let's take a quick look at the key ideas and tools involved.

## Also integrate Epic games with

- [OpenAI Agents SDK](https://composio.dev/toolkits/epic_games/framework/open-ai-agents-sdk)
- [Claude Agent SDK](https://composio.dev/toolkits/epic_games/framework/claude-agents-sdk)
- [Claude Code](https://composio.dev/toolkits/epic_games/framework/claude-code)
- [Claude Cowork](https://composio.dev/toolkits/epic_games/framework/claude-cowork)
- [Codex](https://composio.dev/toolkits/epic_games/framework/codex)
- [OpenClaw](https://composio.dev/toolkits/epic_games/framework/openclaw)
- [Hermes](https://composio.dev/toolkits/epic_games/framework/hermes-agent)
- [CLI](https://composio.dev/toolkits/epic_games/framework/cli)
- [Google ADK](https://composio.dev/toolkits/epic_games/framework/google-adk)
- [LangChain](https://composio.dev/toolkits/epic_games/framework/langchain)
- [Vercel AI SDK](https://composio.dev/toolkits/epic_games/framework/ai-sdk)
- [Mastra AI](https://composio.dev/toolkits/epic_games/framework/mastra-ai)
- [CrewAI](https://composio.dev/toolkits/epic_games/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 Epic games
- Connect LlamaIndex to the Epic games MCP server
- Build a Epic games-powered agent using LlamaIndex
- Interact with Epic games 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 Epic games MCP server, and what's possible with it?

The Epic games MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Epic games account. It provides structured and secure access to your Epic Games platform, so your agent can perform actions like accessing your game library, tracking new releases, viewing purchase history, and managing your account details on your behalf.
- Game library insights: Let your agent retrieve and summarize information about your owned and recently played games.
- Store browsing and recommendations: Have the agent help you discover new games, sales, and curated recommendations from the Epic Games Store.
- Purchase history overview: Get quick reports on your past purchases, including receipts and downloadable content.
- Account management assistance: Allow your agent to help update profile details, privacy settings, or linked accounts for a streamlined experience.
- Stay up-to-date on releases: Ask the agent to notify you about upcoming game launches, updates, or major events within the Epic Games ecosystem.

## Supported Tools

| Tool slug | Name | Description |
|---|---|---|
| `EPIC_GAMES_DELETE_PRESET_METADATA_KEY` | Delete Preset Metadata Key | Tool to delete a metadata key-value pair associated with a Remote Control Preset. Use after confirming you have the correct preset name and metadata key. |
| `EPIC_GAMES_GET_ISLAND` | Get Island Metadata | Tool to fetch metadata for a specific Fortnite island by its code. Use when you have an island code and need detailed island information. |
| `EPIC_GAMES_GET_ISLAND_AVG_MINUTES_PER_PLAYER` | Get Island Average Minutes per Player | Tool to retrieve average minutes per unique player for a given island code and interval. Use when you need daily or more granular (hour/minute) player engagement metrics. Hourly/minute intervals may not be available. |
| `EPIC_GAMES_GET_ISLAND_FAVORITES` | Get Island Favorites Metrics | Tool to fetch how many times an island was added to favorites over a time interval. Use when analyzing island popularity trends. |
| `EPIC_GAMES_GET_ISLAND_METRICS_BY_INTERVAL` | Get Island Metrics by Interval | Tool to retrieve usage metrics for a Fortnite island aggregated by interval. Use when analyzing island usage over time buckets. |
| `EPIC_GAMES_GET_ISLAND_MINUTES_PLAYED` | Get Island Minutes Played | Tool to retrieve total minutes played on an island during a given interval. Use after obtaining the island code to analyze player engagement metrics. |
| `EPIC_GAMES_GET_ISLAND_PEAK_CCU` | Get Island Peak CCU | Tool to retrieve peak concurrent users for an island. Use when you need to monitor the highest concurrent users over a specific interval. |
| `EPIC_GAMES_GET_ISLAND_PLAYS` | Get Island Plays | Tool to retrieve the number of plays (session starts) for a Fortnite island. Use when you need play metrics for a specific island and time interval. |
| `EPIC_GAMES_GET_ISLAND_RECOMMENDATIONS` | Get Island Recommendations | Tool to retrieve the count of player recommendations for an island. Use when you need recommendation metrics over a given interval. |
| `EPIC_GAMES_GET_ISLAND_RETENTION` | Get Island Retention | Tool to retrieve day-over-day retention metrics for a Fortnite island. Use when analyzing retention performance by day (only supported for day interval). |
| `EPIC_GAMES_GET_ISLAND_UNIQUE_PLAYERS` | Get Island Unique Players | Tool to retrieve the number of unique players who played an island over a specific interval. Use after obtaining the island code and desired interval. |
| `EPIC_GAMES_GET_PRESET` | Get Remote Control Preset | Tool to get details for a specific Remote Control Preset by name. Use after listing or identifying available presets to fetch their configuration including groups, properties, and functions. |
| `EPIC_GAMES_GET_PRESET_METADATA` | Get Preset Metadata | Tool to retrieve all metadata entries associated with a preset. Use when you need to inspect metadata of a Remote Control Preset after confirming it exists. |
| `EPIC_GAMES_GET_PRESET_METADATA_KEY` | Get Preset Metadata Key | Tool to read a single metadata key's value for a Remote Control Preset. Use when you need to fetch a specific metadata entry after listing presets. |
| `EPIC_GAMES_GET_PRESET_PROPERTY` | Get Preset Property | Tool to read the value(s) of a property exposed through a Remote Control Preset. Use when you need to fetch the current state of a specific property from a preset. |
| `EPIC_GAMES_LIST_BLUEPRINT_CALLABLE_FUNCTIONS` | List Blueprint-Callable Functions | Tool to list blueprint-callable functions on a UObject. Use when you need to inspect available functions for automation or debugging. |
| `EPIC_GAMES_LIST_ISLANDS` | List Fortnite Islands | Tool to list public discoverable Fortnite islands sorted by newest releases first. Use when browsing community-created islands. |
| `EPIC_GAMES_OPTIONS_REMOTE` | Remote API CORS Preflight | Tool to perform a CORS preflight OPTIONS request to the Remote Control API. Use when verifying cross-origin HTTP request permissions before making other calls. |
| `EPIC_GAMES_PUT_OBJECT_CALL` | Call UObject Blueprint Function | Tool to invoke a Blueprint-callable function on an in-memory UObject. Use after confirming the target object path and function name (e.g., call SetActorLocation to move an actor). |
| `EPIC_GAMES_PUT_OBJECT_DESCRIBE` | Describe a UObject | Tool to describe a UObject. Use when you need metadata of an object identified by its path. Example: Describe UObject with path '/Game/MyMap:PersistentLevel.MyActor'. |
| `EPIC_GAMES_PUT_OBJECT_EVENT_EXPERIMENTAL` | Wait for UObject Event (Experimental) | Tool to block until the next specified UObject event occurs. Use when you need to wait for a specific property-change event on a UObject before proceeding. Experimental: this route only returns after the event fires (requires WebControl.EnableExperimentalRoutes=1). |
| `EPIC_GAMES_PUT_OBJECT_PROPERTY` | Put UObject Property | Tool to read or set a UObject's property values. Use when you need to inspect or modify one or more properties of a specified Unreal Engine UObject via Remote Control HTTP API. |
| `EPIC_GAMES_PUT_OBJECT_THUMBNAIL` | Get Object Thumbnail | Tool to fetch the Content Browser thumbnail image for a specified asset. Use when you need a preview of the asset's thumbnail. |
| `EPIC_GAMES_PUT_PRESET_FUNCTION` | Invoke Preset Function | Tool to invoke a function in a Remote Control Preset. Use after locating the preset and function name. |
| `EPIC_GAMES_PUT_PRESET_METADATA_KEY` | Put Preset Metadata Key | Tool to create or update a metadata key on a Remote Control Preset. Use when you need to set or modify metadata value for a preset. |
| `EPIC_GAMES_PUT_PRESET_PROPERTY` | Update Preset Property | Tool to update a property exposed through a Remote Control Preset. Use when you need to change the value of a preset’s property after inspecting its metadata. |
| `EPIC_GAMES_PUT_REMOTE_BATCH` | Batch Remote Control Requests | Tool to batch multiple Remote Control API calls into a single request. Use when needing to reduce round-trip latency by grouping several API calls into one batch. |
| `EPIC_GAMES_PUT_REMOTE_CONTROL_SESSION` | Initiate Remote Control Session | Tool to initiate a Remote Control session. Use when asset operations require an active session before other /remote calls. |

## Supported Triggers

None listed.

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

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

### 1. Getting API Keys for OpenAI, Composio, and Epic games

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 Epic games 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, epic games)
- 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 Epic games 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=["epic_games"],
    )

    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 Epic games actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Epic games 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: ["epic_games"],
    },
  );

  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 Epic games 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 Epic games
```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 Epic games, 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=["epic_games"],
    )

    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 Epic games actions."
    system_prompt = """
    You are a helpful assistant connected to Composio Tool Router.
    Use the available tools to answer user queries and perform Epic games 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: ["epic_games"],
    },
  );

  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 Epic games 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 Epic games to LlamaIndex through Composio's Tool Router MCP layer.
Key takeaways:
- Tool Router dynamically exposes Epic games 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 Epic games MCP Agent with another framework

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

## Related Toolkits

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- [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.
- [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.
- [RAWG Video Games Database](https://composio.dev/toolkits/rawg_video_games_database) - RAWG Video Games Database is the largest video game discovery and info service. Instantly access comprehensive details, ratings, and release dates for thousands of games.
- [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 Epic games MCP?

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

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

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

---
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