# How to integrate Ticketmaster MCP with LlamaIndex ```json { "title": "How to integrate Ticketmaster MCP with LlamaIndex", "toolkit": "Ticketmaster", "toolkit_slug": "ticketmaster", "framework": "LlamaIndex", "framework_slug": "llama-index", "url": "https://composio.dev/toolkits/ticketmaster/framework/llama-index", "markdown_url": "https://composio.dev/toolkits/ticketmaster/framework/llama-index.md", "updated_at": "2026-05-12T10:28:25.248Z" } ``` ## Introduction This guide walks you through connecting Ticketmaster to LlamaIndex using the Composio tool router. By the end, you'll have a working Ticketmaster agent that can find concerts happening in new york this weekend, get details about taylor swift's upcoming shows, list comedy events in los angeles next month through natural language commands. This guide will help you understand how to give your LlamaIndex agent real control over a Ticketmaster account through Composio's Ticketmaster MCP server. Before we dive in, let's take a quick look at the key ideas and tools involved. ## Also integrate Ticketmaster with - [OpenAI Agents SDK](https://composio.dev/toolkits/ticketmaster/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/ticketmaster/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/ticketmaster/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/ticketmaster/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/ticketmaster/framework/codex) - [OpenClaw](https://composio.dev/toolkits/ticketmaster/framework/openclaw) - [Hermes](https://composio.dev/toolkits/ticketmaster/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/ticketmaster/framework/cli) - [Google ADK](https://composio.dev/toolkits/ticketmaster/framework/google-adk) - [LangChain](https://composio.dev/toolkits/ticketmaster/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/ticketmaster/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/ticketmaster/framework/mastra-ai) - [CrewAI](https://composio.dev/toolkits/ticketmaster/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 Ticketmaster - Connect LlamaIndex to the Ticketmaster MCP server - Build a Ticketmaster-powered agent using LlamaIndex - Interact with Ticketmaster 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 Ticketmaster MCP server, and what's possible with it? The Ticketmaster MCP server is an implementation of the Model Context Protocol that connects your AI agent and assistants like Claude, Cursor, etc directly to your Ticketmaster account. It provides structured and secure access to Ticketmaster's event and ticketing APIs, so your agent can search events, fetch details for attractions or venues, suggest events, and help manage event classifications on your behalf. - Event discovery and search: Effortlessly ask your agent to find concerts, sports games, or shows by keyword, location, date, or genre using advanced filters. - Attraction and performer lookup: Retrieve detailed information about artists, teams, or performers to help with recommendations and event planning. - Event detail retrieval: Get comprehensive information for any specific event, including venue, time, ticket availability, and more. - Smart suggestions and autocomplete: Instantly get auto-complete suggestions for attractions, venues, or events based on partial queries or interests. - Event classification management: Explore and organize events by classification, genre, segment, or subgenre to power more personalized searches and recommendations. ## Supported Tools | Tool slug | Name | Description | |---|---|---| | `TICKETMASTER_EXECUTE_SEASON_TICKETING_COMMAND` | Execute Season Ticketing Command | Tool to execute Season Ticketing API commands for ticket management operations. Use when you need to interact with Ticketmaster's Archtics Season Ticketing system for administrative tasks, account management, or event discovery. Supports commands: ping (test connectivity), customer_query (get account info), seats_sold (retrieve sold seat details), event_search (search events), event_details (get event attributes), get_attendance (retrieve attendance data). Note: API may return 202 ACCEPTED for asynchronous operations - caller must poll with provided cookies until receiving 200 OK response. | | `TICKETMASTER_GET_ATTRACTION_DETAILS2` | Get Attraction Details V2 | Tool to retrieve detailed information about a specific attraction by ID from Ticketmaster Discovery API v2. Use when you need attraction details with optional licensed content filtering. | | `TICKETMASTER_GET_ATTRACTIONS` | Get Ticketmaster Attractions | Tool to retrieve a list of attractions. Use when you need to search for artists, teams, or performers by various criteria such as keyword, classification, or country. | | `TICKETMASTER_GET_CLASSIFICATION_DETAILS` | Get Classification Details | Tool to retrieve detailed information about a specific classification. Use after obtaining a classification ID. | | `TICKETMASTER_GET_CLASSIFICATIONS` | Get Classifications | Retrieves event classifications from Ticketmaster's Discovery API. Classifications provide a hierarchical taxonomy for categorizing events: - Segment: Top-level category (Music, Sports, Arts & Theater, Family, Film, Miscellaneous) - Genre: Secondary category within a segment (e.g., Rock, Baseball, Comedy) - Subgenre: Tertiary category for specific classification (e.g., Alternative Rock, MLB) Use this tool to discover available categories before searching for events, or to understand how events are organized in the Ticketmaster system. The classifications can be filtered by locale, country, or specific classification ID. | | `TICKETMASTER_GET_EVENT_DETAILS` | Get Event Details | Tool to retrieve detailed information about a specific event by ID. Use when you have an event's unique identifier and need its full details. | | `TICKETMASTER_GET_EVENT_IMAGES` | Get Event Images | Tool to retrieve images for a specific event by ID. Use when you need to fetch image URLs and metadata for an event. | | `TICKETMASTER_GET_EVENTS` | Search Events | Search for events on Ticketmaster using various filters including location, date range, keywords, classifications, and more. This action queries the Ticketmaster Discovery API to find events matching your criteria. Results are paginated and can be sorted. Use this when you need to: search for concerts/shows/games, find events in a specific location, filter by date range, or discover events by artist/venue. Key capabilities: - Location search: by city, state, postal code, lat/long, or radius - Time filtering: events within date ranges or on-sale dates - Classification: filter by segment (Music/Sports/Arts), genre, subgenre - Keyword search: find events by name or description - Venue/Attraction: get events at specific venues or by specific artists/teams Note: Deep paging limit - size * page must be < 1000. Maximum 200 results per page. | | `TICKETMASTER_GET_GENRE_DETAILS` | Get Genre Details | Tool to retrieve detailed information about a specific genre. Use when you need metadata for a single genre before filtering events by genre. | | `TICKETMASTER_GET_SECTION_MAP_IMAGE` | Get Section Map Image | Tool to retrieve the section map image for an event showing venue layout. Use when you need a visual representation of a venue's seating sections for a specific event. Optionally highlights specific sections or seats. | | `TICKETMASTER_GET_SEGMENT_DETAILS` | Get Segment Details | Retrieve detailed information about a specific Ticketmaster event segment, including all associated genres and subgenres. Segments are the top-level classification categories for events (e.g., Music, Sports, Arts & Theatre, Family, Film, Miscellaneous). This action returns the segment's metadata along with a complete list of genres and their subgenres that fall under this segment. Use this action after obtaining a segment ID from Get Classifications or from event classification data. | | `TICKETMASTER_GET_SUBGENRE_DETAILS` | Get Subgenre Details | Tool to retrieve detailed information about a specific subgenre. Use when you have a subgenre ID and need its details. | | `TICKETMASTER_GET_SUGGESTIONS2` | Get Advanced Suggestions | Get advanced auto-complete search suggestions from Ticketmaster's Discovery API. Returns matching attractions (artists, teams, performers), venues (concert halls, stadiums, theaters), and events based on search criteria with extensive filtering options. Use this when you need more control over suggestions including location filtering, source filtering, fuzzy matching, and spell checking. Perfect for implementing type-ahead search functionality with advanced filters or helping users discover entertainment options based on location, segment, and other criteria. | | `TICKETMASTER_GET_VENUE_DETAILS2` | Get Venue Details (Enhanced) | Tool to retrieve comprehensive details about a specific venue by ID. Use when you need detailed venue information including location, box office info, images, and social media data. | | `TICKETMASTER_GET_VENUES` | Get Venues | Tool to retrieve a list of venues based on specified criteria. Use when you need venue details by name, location, or ID. | ## Supported Triggers None listed. ## Creating MCP Server - Stand-alone vs Composio SDK The Ticketmaster MCP server is an implementation of the Model Context Protocol that connects your AI agent to Ticketmaster. It provides structured and secure access so your agent can perform Ticketmaster 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 Ticketmaster account and project - Basic familiarity with async Python/Typescript ### 1. Getting API Keys for OpenAI, Composio, and Ticketmaster 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 Ticketmaster 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, ticketmaster) - 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 Ticketmaster 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=["ticketmaster"], ) 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 Ticketmaster actions." system_prompt = """ You are a helpful assistant connected to Composio Tool Router. Use the available tools to answer user queries and perform Ticketmaster 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: ["ticketmaster"], }, ); 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 Ticketmaster 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) { 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 Ticketmaster ```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 Ticketmaster, 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=["ticketmaster"], ) 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 Ticketmaster actions." system_prompt = """ You are a helpful assistant connected to Composio Tool Router. Use the available tools to answer user queries and perform Ticketmaster 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: ["ticketmaster"], }, ); 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 Ticketmaster actions." , llm, tools, }); return agent; } async function chatLoop(agent: ReturnType) { 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 Ticketmaster to LlamaIndex through Composio's Tool Router MCP layer. Key takeaways: - Tool Router dynamically exposes Ticketmaster 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 Ticketmaster MCP Agent with another framework - [OpenAI Agents SDK](https://composio.dev/toolkits/ticketmaster/framework/open-ai-agents-sdk) - [Claude Agent SDK](https://composio.dev/toolkits/ticketmaster/framework/claude-agents-sdk) - [Claude Code](https://composio.dev/toolkits/ticketmaster/framework/claude-code) - [Claude Cowork](https://composio.dev/toolkits/ticketmaster/framework/claude-cowork) - [Codex](https://composio.dev/toolkits/ticketmaster/framework/codex) - [OpenClaw](https://composio.dev/toolkits/ticketmaster/framework/openclaw) - [Hermes](https://composio.dev/toolkits/ticketmaster/framework/hermes-agent) - [CLI](https://composio.dev/toolkits/ticketmaster/framework/cli) - [Google ADK](https://composio.dev/toolkits/ticketmaster/framework/google-adk) - [LangChain](https://composio.dev/toolkits/ticketmaster/framework/langchain) - [Vercel AI SDK](https://composio.dev/toolkits/ticketmaster/framework/ai-sdk) - [Mastra AI](https://composio.dev/toolkits/ticketmaster/framework/mastra-ai) - [CrewAI](https://composio.dev/toolkits/ticketmaster/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. - [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. - [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 Ticketmaster MCP? With a standalone Ticketmaster MCP server, the agents and LLMs can only access a fixed set of Ticketmaster tools tied to that server. However, with the Composio Tool Router, agents can dynamically load tools from Ticketmaster 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 Ticketmaster tools. ### Can I manage the permissions and scopes for Ticketmaster while using Tool Router? Yes, absolutely. You can configure which Ticketmaster 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 Ticketmaster data and credentials are handled as safely as possible. --- [See all toolkits](https://composio.dev/toolkits) ยท [Composio docs](https://docs.composio.dev/llms.txt)