Trakt MCP Server for LangChain 18 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Trakt through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
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Vinkius supports streamable HTTP and SSE.
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({
"trakt": {
"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 Trakt, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
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 Trakt MCP Server
Connect to Trakt and explore the world's most popular TV and movie tracking platform through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with Trakt through native MCP adapters. Connect 18 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
- Search — Find movies, TV shows, episodes and people by title or name
- Movie Details — Get ratings, cast, crew, genres and related movies
- Show Details — Get seasons, episodes, cast, ratings and related shows
- Trending — See what's currently trending on Trakt in real-time
- Popular — Discover the most popular movies and shows
- Calendar — Get upcoming episode premieres and air dates
The Trakt MCP Server exposes 18 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 Trakt to LangChain via MCP
Follow these steps to integrate the Trakt MCP Server with LangChain.
Install dependencies
Run pip install langchain langchain-mcp-adapters langgraph langchain-openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save the code and run python agent.py
Explore tools
The agent discovers 18 tools from Trakt via MCP
Why Use LangChain with the Trakt MCP Server
LangChain provides unique advantages when paired with Trakt through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Trakt MCP tools with 500+ LangChain components
Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step
LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging
Memory and conversation persistence let agents maintain context across Trakt queries for multi-turn workflows
Trakt + LangChain Use Cases
Practical scenarios where LangChain combined with the Trakt MCP Server delivers measurable value.
RAG with live data: combine Trakt tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Trakt, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Trakt tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Trakt tool call, measure latency, and optimize your agent's performance
Trakt MCP Tools for LangChain (18)
These 18 tools become available when you connect Trakt to LangChain via MCP:
get_calendar
Scope can be "my" (user's watched shows) or "all" (all shows). Returns episodes with air dates, times and show info. Get upcoming episode calendar
get_collection
Requires OAuth access token. Returns collected items with metadata and media info. Get the authenticated user's collection
get_history
Requires OAuth access token. Optionally filter by type and ID. Get the authenticated user's watch history
get_movie
Returns title, year, overview, runtime, rating, genres, languages, certification, trailer and poster URLs. Get detailed info for a specific movie
get_movie_people
Each person includes their name, Trakt ID, character name (for cast) and job title (for crew). Get cast and crew for a specific movie
get_movie_ratings
Returns total ratings, average score and the count of votes for each rating level. Get ratings distribution for a specific movie
get_popular
Popularity is based on overall engagement and activity. Returns paginated results. Get the most popular movies or shows
get_related_movies
Each related movie includes title, year, overview, rating and poster URL. Get movies related to a specific movie
get_related_shows
Each related show includes title, year, overview, rating and poster URL. Get shows related to a specific TV show
get_show
Returns title, year, overview, status, runtime, rating, genres, network, certification, trailer and poster URLs. Get detailed info for a specific TV show
get_show_episodes
Each episode includes episode number, title, overview, runtime, ratings and first aired date. Get all episodes for a specific season of a TV show
get_show_people
Get cast and crew for a TV show
get_show_ratings
Returns total ratings, average score and vote counts per rating level. Get ratings distribution for a TV show
get_show_seasons
Each season includes season number, episode count, air date, rating and overview. Get all seasons for a TV show
get_trending
Trending is based on what users are actively watching and checking in. Returns items with viewer counts. Get currently trending movies or shows
get_watched
Requires OAuth access token. Returns items with play counts and last watched timestamps. Get the authenticated user's watched history
get_watchlist
Requires an OAuth access token. Returns movies and/or shows the user has added to their watchlist. Get the authenticated user's watchlist
search
Returns results with titles, years, ratings, genres, IDs and synopsis. Use type parameter to narrow results: "movie", "show", "episode", "person" or "list". Search for movies, shows, episodes, people or lists on Trakt
Example Prompts for Trakt in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Trakt immediately.
"What movies are trending right now?"
"Show me info about Breaking Bad."
"Who directed The Matrix and who starred in it?"
Troubleshooting Trakt MCP Server with LangChain
Common issues when connecting Trakt to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersTrakt + LangChain FAQ
Common questions about integrating Trakt MCP Server with LangChain.
How does LangChain connect to MCP servers?
langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.Which LangChain agent types work with MCP?
Can I trace MCP tool calls in LangSmith?
Connect Trakt 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 Trakt to LangChain
Get your token, paste the configuration, and start using 18 tools in under 2 minutes. No API key management needed.