Overseerr
About
Integrates with Overseerr to enable media searching, retrieval, request management, and personalized recommendations for Plex libraries.
Details
- Author
- jmagar
- Downloads
- 122
- Categories
- Developer Tools, Design, AI, Media, Search, Infrastructure, Automation, Frontend, Other
- Tags
- #integration
Jump to
- Search movies, TV shows, and people with natural language queries.
- Get detailed media info: title, release date, plot, availability, request status.
- Filter searches by media type (movie / TV / person).
- Request movies or TV shows, specifying individual seasons for TV.
- Track request status and receive updates.
- Secure API key handling and rate limiting.
Setting up with Highlight
This MCP is not yet compatible with Highlight’s one-click setup. However, you can still use it with Highlight by following these steps:
- Download and install Highlight from highlightai.com/download
- Navigate to the plugins tab and select "Add Custom Plugin"
-
Configure the plugin with the settings below
Plugin Name
OverseerrCommand (node, npx, python, etc.)npxArguments-
Argument 1
-y -
Argument 2
@highlight/mcp-server
Please refer to the README for specific instructions on how to obtain API keys or other required environment variables.
-
Argument 1
- Enable "Start Automatically" if you want the plugin to start when Highlight launches
From the repository
Install dependencies with pnpm install, build the project with pnpm build, copy .env.template to .env and set OVERSEERR_URL and OVERSEERR_API_KEY, then configure Claude Desktop with a stdio transport pointing to the built server. Start the server with pnpm start. Once connected, Claude can invoke tools like overseerr:search (to search movies, TV shows, or people) and overseerr:request (to request a movie or TV show by TMDB ID, optionally specifying which seasons for TV).
Claude Desktop / Cursor
Paste into your MCP client config file to install this server.
{
"mcpServers": {
"overseerr": {
"env": {},
"args": [
"-y",
"@highlight/mcp-server"
],
"command": "npx"
}
}
}
Linux
{
"env": [],
"args": [
"-y",
"@highlight/mcp-server"
],
"command": "npx"
}
Macos
{
"env": [],
"args": [
"-y",
"@highlight/mcp-server"
],
"command": "npx"
}
Windows
{
"env": [],
"args": [
"/c",
"npx",
"-y",
"@highlight/mcp-server"
],
"command": "cmd"
}
Overseerr MCP
A Model Context Protocol (MCP) integration for Overseerr that enables natural language interaction with your media request system through Claude AI. This server allows you to search for movies and TV shows, make media requests, and manage your Overseerr instance using conversational language.
Example Conversations
Here are some example conversations you can have with Claude using this server:
You: Can you find any recent sci-fi movies?
Claude: Let me search for recent science fiction films...
[Uses overseerr:search to find recent sci-fi movies]
You: That looks good! Can you request the second one?
Claude: I'll request that movie for you...
[Uses overseerr:request to submit the media request]
You: What TV shows are available about cooking?
Claude: I'll search for cooking-related TV shows...
[Uses overseerr:search with type='tv' to find cooking shows]
Features
Media Search
- Search across movies, TV shows, and people - Get detailed information about media including: - Title and release date - Plot overview - Availability status - Request status - Filter by media type (movie/TV/person) - Natural language queries (e.g., "find recent sci-fi movies" or "search for shows like Breaking Bad")Media Requests
- Request movies and TV shows - Specify individual seasons for TV shows - Track request status - Get notifications about request updates - Natural language requests (e.g., "request the latest Batman movie" or "add Succession to my watchlist")Integration
- Seamless Claude AI integration through stdio transport - Real-time interaction with your Overseerr instance - Secure API key handling - Rate limiting and error handling - Easy configuration through environment variablesSetup
Prerequisites
- Node.js - pnpm - Claude Desktop - Overseerr instanceQuick Start
1. Install dependencies:
pnpm install
2. Build the project:
pnpm build
3. Configure environment:
```bash
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