Trakt MCP Server for Pydantic AI 18 tools — connect in under 2 minutes
Pydantic AI brings type-safe agent development to Python with first-class MCP support. Connect Trakt through Vinkius and every tool is automatically validated against Pydantic schemas. catch errors at build time, not in production.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import asyncio
from pydantic_ai import Agent
from pydantic_ai.mcp import MCPServerHTTP
async def main():
# Your Vinkius token. get it at cloud.vinkius.com
server = MCPServerHTTP(url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp")
agent = Agent(
model="openai:gpt-4o",
mcp_servers=[server],
system_prompt=(
"You are an assistant with access to Trakt "
"(18 tools)."
),
)
result = await agent.run(
"What tools are available in Trakt?"
)
print(result.data)
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.
Pydantic AI validates every Trakt tool response against typed schemas, catching data inconsistencies at build time. Connect 18 tools through Vinkius and switch between OpenAI, Anthropic, or Gemini without changing your integration code. full type safety, structured output guarantees, and dependency injection for testable agents.
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 Pydantic AI 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 Pydantic AI via MCP
Follow these steps to integrate the Trakt MCP Server with Pydantic AI.
Install Pydantic AI
Run pip install pydantic-ai
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 with type-safe schemas
Why Use Pydantic AI with the Trakt MCP Server
Pydantic AI provides unique advantages when paired with Trakt through the Model Context Protocol.
Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Trakt integration code
Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
Dependency injection system cleanly separates your Trakt connection logic from agent behavior for testable, maintainable code
Trakt + Pydantic AI Use Cases
Practical scenarios where Pydantic AI combined with the Trakt MCP Server delivers measurable value.
Type-safe data pipelines: query Trakt with guaranteed response schemas, feeding validated data into downstream processing
API orchestration: chain multiple Trakt tool calls with Pydantic validation at each step to ensure data integrity end-to-end
Production monitoring: build validated alert agents that query Trakt and output structured, schema-compliant notifications
Testing and QA: use Pydantic AI's dependency injection to mock Trakt responses and write comprehensive agent tests
Trakt MCP Tools for Pydantic AI (18)
These 18 tools become available when you connect Trakt to Pydantic AI 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 Pydantic AI
Ready-to-use prompts you can give your Pydantic AI 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 Pydantic AI
Common issues when connecting Trakt to Pydantic AI through the Vinkius, and how to resolve them.
MCPServerHTTP not found
pip install --upgrade pydantic-aiTrakt + Pydantic AI FAQ
Common questions about integrating Trakt MCP Server with Pydantic AI.
How does Pydantic AI discover MCP tools?
MCPServerHTTP instance with the server URL. Pydantic AI connects, discovers all tools, and generates typed Python interfaces automatically.Does Pydantic AI validate MCP tool responses?
Can I switch LLM providers without changing MCP code?
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 Pydantic AI
Get your token, paste the configuration, and start using 18 tools in under 2 minutes. No API key management needed.