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TVMaze MCP Server for LangChain 15 tools — connect in under 2 minutes

Built by Vinkius GDPR 15 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect TVMaze through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Vinkius supports streamable HTTP and SSE.

python
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "tvmaze": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using TVMaze, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())
TVMaze
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Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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.

LangChain's ecosystem of 500+ components combines seamlessly with TVMaze through native MCP adapters. Connect 15 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

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 LangChain 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 LangChain via MCP

Follow these steps to integrate the TVMaze MCP Server with LangChain.

01

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

02

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

03

Run the agent

Save the code and run python agent.py

04

Explore tools

The agent discovers 15 tools from TVMaze via MCP

Why Use LangChain with the TVMaze MCP Server

LangChain provides unique advantages when paired with TVMaze through the Model Context Protocol.

01

The largest ecosystem of integrations, chains, and agents. combine TVMaze MCP tools with 500+ LangChain components

02

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

03

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

04

Memory and conversation persistence let agents maintain context across TVMaze queries for multi-turn workflows

TVMaze + LangChain Use Cases

Practical scenarios where LangChain combined with the TVMaze MCP Server delivers measurable value.

01

RAG with live data: combine TVMaze tool results with vector store retrievals for answers grounded in both real-time and historical data

02

Autonomous research agents: LangChain agents query TVMaze, synthesize findings, and generate comprehensive research reports

03

Multi-tool orchestration: chain TVMaze tools with web scrapers, databases, and calculators in a single agent run

04

Production monitoring: use LangSmith to trace every TVMaze tool call, measure latency, and optimize your agent's performance

TVMaze MCP Tools for LangChain (15)

These 15 tools become available when you connect TVMaze to LangChain via MCP:

01

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

02

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

03

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

04

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

05

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

06

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

07

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

08

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

09

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

10

get_show_images

Each image includes its type, resolution, and URL. Get images for a TV show

11

get_show_seasons

Each season includes its number, name, episode order, premiere date, network and image URL. Get all seasons for a TV show

12

get_shows

Returns only show IDs. Use get_show for details on specific shows. Browse all TV shows in the database

13

search_people

Uses fuzzy matching. Returns multiple results with person names, photos and their notable shows. Search for actors and crew by name

14

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

15

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 LangChain

Ready-to-use prompts you can give your LangChain agent to start working with TVMaze immediately.

01

"Search for 'Breaking Bad' and show me details."

02

"Show me the full cast of The Office."

03

"What's on TV tonight in the US?"

Troubleshooting TVMaze MCP Server with LangChain

Common issues when connecting TVMaze to LangChain through the Vinkius, and how to resolve them.

01

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

TVMaze + LangChain FAQ

Common questions about integrating TVMaze MCP Server with LangChain.

01

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.
02

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.
03

Can I trace MCP tool calls in LangSmith?

Yes. All MCP tool invocations appear as traced steps in LangSmith, showing input parameters, response payloads, latency, and token usage.

Connect TVMaze to LangChain

Get your token, paste the configuration, and start using 15 tools in under 2 minutes. No API key management needed.