Trakt MCP Server for LlamaIndex 18 tools — connect in under 2 minutes
LlamaIndex specializes in data-aware AI agents that connect LLMs to structured and unstructured sources. Add Trakt as an MCP tool provider through Vinkius and your agents can query, analyze, and act on live data alongside your existing indexes.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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 Trakt. "
"You have 18 tools available."
),
)
response = await agent.run(
"What tools are available in Trakt?"
)
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 Trakt MCP Server
Connect to Trakt and explore the world's most popular TV and movie tracking platform through natural conversation.
LlamaIndex agents combine Trakt tool responses with indexed documents for comprehensive, grounded answers. Connect 18 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
- 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 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 Trakt to LlamaIndex via MCP
Follow these steps to integrate the Trakt 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 18 tools from Trakt
Why Use LlamaIndex with the Trakt MCP Server
LlamaIndex provides unique advantages when paired with Trakt through the Model Context Protocol.
Data-first architecture: LlamaIndex agents combine Trakt tool responses with indexed documents for comprehensive, grounded answers
Query pipeline framework lets you chain Trakt tool calls with transformations, filters, and re-rankers in a typed pipeline
Multi-source reasoning: agents can query Trakt, a vector store, and a SQL database in a single turn and synthesize results
Observability integrations show exactly what Trakt tools were called, what data was returned, and how it influenced the final answer
Trakt + LlamaIndex Use Cases
Practical scenarios where LlamaIndex combined with the Trakt MCP Server delivers measurable value.
Hybrid search: combine Trakt real-time data with embedded document indexes for answers that are both current and comprehensive
Data enrichment: query Trakt 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 Trakt for fresh data
Analytical workflows: chain Trakt queries with LlamaIndex's data connectors to build multi-source analytical reports
Trakt MCP Tools for LlamaIndex (18)
These 18 tools become available when you connect Trakt to LlamaIndex 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 LlamaIndex
Ready-to-use prompts you can give your LlamaIndex 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 LlamaIndex
Common issues when connecting Trakt to LlamaIndex through the Vinkius, and how to resolve them.
BasicMCPClient not found
pip install llama-index-tools-mcpTrakt + LlamaIndex FAQ
Common questions about integrating Trakt 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 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 LlamaIndex
Get your token, paste the configuration, and start using 18 tools in under 2 minutes. No API key management needed.