Compatible with every major AI agent and IDE
What is the Radarr (Movies) MCP Server?
Connect your Radarr instance to any AI agent to take full control of your movie collection and PVR workflows through natural conversation.
What you can do
- Library Management — List all movies in your collection, fetch detailed metadata, and update movie configurations.
- Discovery & Search — Search for new movies using TMDB integration and add them to your library with specific quality profiles.
- Download Monitoring — Track your active download queue, view history of grabs/imports, and manage queue items.
- System Operations — Check disk space, system status, and execute internal commands like library refreshes.
- Infrastructure Mapping — Retrieve root folders and quality profiles to ensure correct organization of your media files.
How it works
- Subscribe to this server
- Enter your Radarr URL and API Key
- Start managing your media library from Claude, Cursor, or any MCP-compatible client
Who is this for?
- Home Lab Enthusiasts — manage your media server without opening the web UI
- Content Collectors — quickly search and add movies to your watchlist via chat
- System Administrators — monitor disk space and download health across your media stack
Built-in capabilities (15)
Requires TMDB ID, quality profile, and root folder path. Add a new movie to Radarr
Remove a movie from Radarr
Remove an item from the download queue
g., RescanMovie, MovieSearch, RefreshMovie, RenameMovie). Execute a specific system command
List active or recently completed commands
Get disk space information
View the history of grabs and imports
Get details for a specific movie
g., HD-1080p, Ultra-HD) configured in Radarr. Get available quality profiles
Get the current download queue
Get configured root folders
Get Radarr system status
List all movies in the Radarr library
g., "term=Inception" or "term=tmdb:27205"). Search for movies to add to Radarr
Provide the full movie object payload. Update an existing movie in Radarr
Why Pydantic AI?
Pydantic AI validates every Radarr (Movies) tool response against typed schemas, catching data inconsistencies at build time. Connect 15 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.
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Full type safety: every MCP tool response is validated against Pydantic models, catching data inconsistencies before they reach your application
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Model-agnostic architecture. switch between OpenAI, Anthropic, or Gemini without changing your Radarr (Movies) integration code
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Structured output guarantee: Pydantic AI ensures tool results conform to defined schemas, eliminating runtime type errors
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Dependency injection system cleanly separates your Radarr (Movies) connection logic from agent behavior for testable, maintainable code
Radarr (Movies) in Pydantic AI
Radarr (Movies) and 4,000+ other MCP servers. One platform. One governance layer.
Teams that connect Radarr (Movies) to Pydantic AI through Vinkius don't need to source, host, or maintain individual MCP servers. Every tool call runs inside a hardened runtime with credential isolation, DLP, and a signed audit chain.
Raw MCP | Vinkius | |
|---|---|---|
| Server catalog | Find and host yourself | 4,000+ managed |
| Infrastructure | Self-hosted | Sandboxed V8 isolates |
| Credential handling | Plaintext in config | Vault + runtime injection |
| Data loss prevention | None | Configurable DLP policies |
| Kill switch | None | Global instant shutdown |
| Financial circuit breakers | None | Per-server limits + alerts |
| Audit trail | None | Ed25519 signed logs |
| SIEM log streaming | None | Splunk, Datadog, Webhook |
| Honeytokens | None | Canary alerts on leak |
| Custom domains | Not applicable | DNS challenge verified |
| GDPR compliance | Manual effort | Automated purge + export |
Why teams choose Vinkius for Radarr (Movies) in Pydantic AI
The Radarr (Movies) 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. All 15 tools execute in hardened sandboxes optimized for native MCP execution.
Your AI agents in Pydantic AI only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure, zero maintenance.

* 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
How Vinkius secures
Radarr (Movies) for Pydantic AI
Every tool call from Pydantic AI to the Radarr (Movies) MCP Server is protected by DLP redaction, cryptographic audit chains, V8 sandbox isolation, kill switch, and financial circuit breakers.
Frequently asked questions
Can I search for movies on TMDB before adding them to my library?
Yes! Use the lookup_movie tool with a search term. The agent will return potential matches from TMDB, which you can then add using add_movie.
How do I check if I have enough disk space for new downloads?
Simply ask the agent to run the get_disk_space tool. It will provide a list of all connected drives and their available capacity.
Is it possible to remove a movie and its files from the disk simultaneously?
Yes. When using the delete_movie tool, you can set the deleteFiles parameter to true to ensure the media is wiped from your storage.
How does Pydantic AI discover MCP tools?
Create an 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?
Yes. When you define result types as Pydantic models, every tool response is validated against the schema. Invalid data raises a clear error instead of silently corrupting your pipeline.
Can I switch LLM providers without changing MCP code?
Absolutely. Pydantic AI abstracts the model layer. your Radarr (Movies) MCP integration works identically with OpenAI, Anthropic, Google, or any supported provider.
MCPServerHTTP not found
Update: pip install --upgrade pydantic-ai
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