by jhomen368
Integrate Overseerr with your Jellyfin media server for easy automated search, requests, and approval workflows for Plex
Connects AI assistants to Overseerr/Seerr instances to search for movies and TV shows, submit download requests, and manage media workflows for Plex/Jellyfin servers.
Overseerr is a community-built MCP server published by jhomen368 that provides AI assistants with tools and capabilities via the Model Context Protocol. Integrate Overseerr with your Jellyfin media server for easy automated search, requests, and approval workflows for Plex It is categorized under other.
You can install Overseerr in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
MIT
Overseerr is released under the MIT license. This is a permissive open-source license, meaning you can freely use, modify, and distribute the software.
Add new capabilities to Claude beyond text generation
Example
Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example
Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example
Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Share your MCP server with the developer community
I recommend Overseerr for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
I recommend Overseerr for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
According to our notes, Overseerr benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
Useful MCP listing: Overseerr is the kind of server we cite when onboarding engineers to host + tool permissions.
Overseerr has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Overseerr reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
According to our notes, Overseerr benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
According to our notes, Overseerr benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
I recommend Overseerr for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
We evaluated Overseerr against two servers with overlapping tools; this profile had the clearer scope statement.
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A Model Context Protocol (MCP) server for Overseerr and Seerr (the unified successor) that enables AI assistants to search, request, and manage media through the Model Context Protocol.
| Tool | Purpose | Key Features |
|---|---|---|
| search_media | Search & dedupe | Single/batch search, dedupe mode for 50-100 titles, franchise awareness |
| request_media | Request movies/TV | Batch requests, season validation, multi-season confirmation, dry-run mode |
| manage_media_requests | Manage requests | List/approve/decline/delete, filtering, summary statistics |
| get_media_details | Get media info | Batch lookup, flexible detail levels (basic/standard/full) |
npm install -g @jhomen368/overseerr-mcp
Configure with Claude Desktop:
Add to your configuration file:
~/Library/Application Support/Claude/claude_desktop_config.json%APPDATA%\Claude\claude_desktop_config.json{
"mcpServers": {
"seerr": {
"command": "npx",
"args": ["-y", "@jhomen368/overseerr-mcp"],
"env": {
"SEERR_URL": "https://seerr.example.com",
"SEERR_API_KEY": "your-api-key-here"
}
}
}
}
Legacy Overseerr Users: If you're still using Overseerr (not Seerr), you can continue using the legacy variables:
{ "env": { "OVERSEERR_URL": "https://overseerr.example.com", "OVERSEERR_API_KEY": "your-api-key-here" } }Both
OVERSEERR_*andSEERR_*variables are supported for backward compatibility. Legacy variables will be removed in v3.0.0.
docker run -d \
--name seerr-mcp \
-p 8085:8085 \
-e SEERR_URL=https://your-seerr-instance.com \
-e SEERR_API_KEY=your-api-key-here \
ghcr.io/jhomen368/overseerr-mcp:latest
Docker Compose:
services:
seerr-mcp:
image: ghcr.io/jhomen368/overseerr-mcp:latest
container_name: seerr-mcp
ports:
- "8085:8085"
environment:
- SEERR_URL=https://your-seerr-instance.com
- SEERR_API_KEY=your-api-key-here
restart: unless-stopped
Test the server:
curl http://localhost:8085/health
Connect MCP clients:
http://localhost:8085/mcpgit clone https://github.com/jhomen368/overseerr-mcp.git
cd overseerr-mcp
npm install
npm run build
node build/index.js
// Check 50-100 titles in ONE API call
search_media({
dedupeMode: true,
titles: [
"Frieren: Beyond Journey's End",
"My Hero Academia Season 7",
"Demon Slayer Season 4",
// ... 47 more titles
],
autoNormalize: true // Strips "Season N", "Part N", etc.
})
Response:
{
"summary": {
"total": 50,
"pass": 35,
"blocked": 15,
"passRate": "70%"
},
"results": [
{ "title": "Frieren", "status": "pass", "id": 209867 },
{ "title": "My Hero Academia S7", "status": "pass", "franchiseInfo": "S1-S6 in library" },
{ "title": "Demon Slayer S4", "status": "blocked", "reason": "Already requested" }
]
}
// Single movie request
request_media({
mediaType: "movie",
mediaId: 438631
})
// TV show with specific seasons
request_media({
mediaType: "tv",
mediaId: 82856,
seasons: [1, 2]
})
// All seasons (excludes season 0 by default)
request_media({
mediaType: "tv",
mediaId: 82856,
seasons: "all"
})
// List with filters
manage_media_requests({
action: "list",
filter: "pending",
take: 20
})
// Batch approve
manage_media_requests({
action: "approve",
requestIds: [123, 124, 125]
})
// Get summary statistics
manage_media_requests({
action: "list",
summary: true
})
Simply ask your AI assistant:
Required:
SEERR_URL - Your Seerr/Overseerr instance URLSEERR_API_KEY - API key from Settings → GeneralLegacy (deprecated, will be removed in v3.0.0):
OVERSEERR_URL - Use SEERR_URL insteadOVERSEERR_API_KEY - Use SEERR_API_KEY insteadOptional (with defaults):
CACHE_ENABLED=true # Enable caching
CACHE_SEARCH_TTL=300000 # Search cache: 5 min
CACHE_MEDIA_TTL=1800000 # Media cache: 30 min
CACHE_REQUESTS_TTL=60000 # Request cache: 1 min
CACHE_MAX_SIZE=1000 # Max cache entries
REQUIRE_MULTI_SEASON_CONFIRM=true # Confirm >24 episodes
HTTP_MODE=false # Enable HTTP transport
PORT=8085 # HTTP server port
# Check logs
docker logs seerr-mcp
# Verify health
curl http://localhost:8085/health
# Restart container
docker restart seerr-mcp
# Ensure Node.js 18+
node --version
# Clean rebuild
rm -rf node_modules build
npm install
npm run build
Contributions welcome! Please see CONTRIBUTING.md for guidelines.
MIT License - see LICENSE for details
Support this project:
Prerequisites
Time Estimate
15-60 minutes depending on server complexity
Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.