TVMaze MCP Server for LlamaIndex 15 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add TVMaze as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
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import asyncio
from llama_index.tools.mcp import BasicMCPClient, McpToolSpec
from llama_index.core.agent.workflow import FunctionAgent
from llama_index.llms.openai import OpenAI
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
mcp_client = BasicMCPClient("https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
mcp_tool_spec = McpToolSpec(client=mcp_client)
tools = await mcp_tool_spec.to_tool_list_async()
agent = FunctionAgent(
tools=tools,
llm=OpenAI(model="gpt-4o"),
system_prompt=(
"You are an assistant with access to TVMaze. "
"You have 15 tools available."
),
)
response = await agent.run(
"What tools are available in TVMaze?"
)
print(response)
asyncio.run(main())
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About TVMaze MCP Server
Connect to TVMaze and explore the world's TV database through natural conversation — no API key needed.
LlamaIndex agents combine TVMaze tool responses with indexed documents for comprehensive, grounded answers. Connect 15 tools through Vinkius and query live data alongside vector stores and SQL databases in a single turn. ideal for hybrid search, data enrichment, and analytical workflows.
What you can do
- Show Search — Search for TV shows by title with fuzzy matching and typo tolerance
- Show Details — Get complete info including genres, network, ratings, status and external IDs (IMDb, TheTVDB)
- Episode Guides — Browse all episodes with season/episode numbers, air dates and summaries
- Cast & Crew — Discover who starred in a show and find directors, writers and producers
- TV Schedule — Check what's airing today or on any date, filtered by country
- People Search — Find actors and crew members with their full filmography
- Show Images — Access posters, banners and background images for any show
The TVMaze MCP Server exposes 15 tools through the Vinkius. Connect it to LlamaIndex in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect TVMaze to LlamaIndex via MCP
Follow these steps to integrate the TVMaze MCP Server with LlamaIndex.
Install dependencies
Run pip install llama-index-tools-mcp llama-index-llms-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.py and run: python agent.py
Explore tools
The agent discovers 15 tools from TVMaze
Why Use LlamaIndex with the TVMaze MCP Server
LlamaIndex provides unique advantages when paired with TVMaze through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine TVMaze tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain TVMaze tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query TVMaze, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what TVMaze tools were called, what data was returned, and how it influenced the final answer
TVMaze + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the TVMaze MCP Server delivers measurable value.
Hybrid search: combine TVMaze real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query TVMaze to augment indexed data with live information before generating user-facing responses
Knowledge base agents: build agents that maintain and update knowledge bases by periodically querying TVMaze for fresh data
Analytical workflows: chain TVMaze queries with LlamaIndex's data connectors to build multi-source analytical reports
TVMaze MCP Tools for LlamaIndex (15)
These 15 tools become available when you connect TVMaze to LlamaIndex via MCP:
get_episode
Returns the episode name, season and number, air date, summary, runtime, image URL and show link. Get detailed info for a specific episode by ID
get_full_schedule
Returns all known future episodes across all shows and networks. This is a large response (multiple MB). Optionally filter by country code. Get the full future TV schedule
get_person
) by their numeric ID. Returns the person's name, birthday, birthplace, gender, photo, bio and external IDs (IMDb, Wikipedia, TVRage). Get detailed info for a specific person
get_person_cast_credits
Each credit includes the show name, character name, episode count and whether the role was main or recurring. Get all cast credits for a person
get_schedule
Each entry includes the show name, episode name, airtime, network and episode info. Optionally set country (ISO 3166-1 alpha-2 code, e.g. "US", "GB", "BR") and date (YYYY-MM-DD, default today). Get TV schedule for a specific date and country
get_show
Returns the show name, genres, network, premiered date, ended date, rating, image URL, summary, runtime, status (running, ended, in development) and external IDs (IMDb, TheTVDB, TVRage). Get detailed info for a specific TV show by ID
get_show_cast
Each cast member includes the person's name, character name and a link to their photo. Useful for discovering who starred in a show. Get the cast for a TV show
get_show_crew
) for a TV show. Each crew member includes their name, role type and credit type. Useful for finding directors, creators and key production staff. Get the crew for a TV show
get_show_episodes
Each episode includes the season and episode number, air date, name, summary, runtime and image URL. By default, special episodes are excluded; set specials=true to include them. Get all episodes for a TV show
get_show_images
Each image includes its type, resolution, and URL. Get images for a TV show
get_show_seasons
Each season includes its number, name, episode order, premiere date, network and image URL. Get all seasons for a TV show
get_shows
Returns only show IDs. Use get_show for details on specific shows. Browse all TV shows in the database
search_people
Uses fuzzy matching. Returns multiple results with person names, photos and their notable shows. Search for actors and crew by name
search_shows
Uses fuzzy matching with tolerance for typos. Returns multiple results ranked by relevance. Each result includes the show's name, genres, network, premiered year, rating, image URL and summary. Use single_search for exact single match. Search for TV shows by name
single_search
Returns exactly one result or none. Includes embedded details like episodes, cast and network info. Use this when you want the best match for a specific show name. Search for a single TV show with full details
Example Prompts for TVMaze in LlamaIndex
Ready-to-use prompts you can give your LlamaIndex agent to start working with TVMaze immediately.
"Search for 'Breaking Bad' and show me details."
"Show me the full cast of The Office."
"What's on TV tonight in the US?"
Troubleshooting TVMaze MCP Server with LlamaIndex
Common issues when connecting TVMaze to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpTVMaze + LlamaIndex FAQ
Common questions about integrating TVMaze MCP Server with LlamaIndex.
How does LlamaIndex connect to MCP servers?
Can I combine MCP tools with vector stores?
Does LlamaIndex support async MCP calls?
Connect TVMaze with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect TVMaze to LlamaIndex
Get your token, paste the configuration, and start using 15 tools in under 2 minutes. No API key management needed.