movie-agent
Allows filtering trending movies by UK streaming availability on Apple TV+ and retrieving subscription pricing.
Allows filtering trending movies by UK streaming availability on Netflix and retrieving subscription pricing.
Allows filtering trending movies by UK streaming availability on Amazon Prime Video and retrieving subscription pricing.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@movie-agentWhat are the top trending sci-fi movies on Netflix rated above 7?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
UK Trending Movie Agent MCP
โจ Features
Dual-Protocol Support: Exposes both a standard FastAPI REST API (with auto-generated
openapi.json) and an MCP v2 SSE Server on a single port (8000).Multi-Client Architecture: Supports Open WebUI (Docker) via HTTP REST/OpenAPI schemas AND Claude Desktop via native MCP protocol.
UK-Specific Movie Intelligence: Filters trending films by IMDb rating, genre, and UK streaming availability (Netflix, Amazon Prime Video, Disney+, Apple TV+, etc.).
Dynamic Schema Generation: Generates
openapi.jsonon disk automatically at startup for one-click import into Open WebUI.
Related MCP server: TMDB MCP Server
๐ Prerequisites
Python 3.13+
Docker Desktop (if using Open WebUI)
Claude Desktop App (if using Claude Sonnet 5)
TMDB API Key (for fetching trending movie data)
Supported LLMs:
Ollama local models:
gemma4:e2b(verified)Claude Desktop: Claude Sonnet 5 (verified)
๐ Installation & Setup
1. Environment Setup
Clone or navigate to the project workspace and set up your virtual environment:
cd /Users/matt/Projects/workspace-py/movie_agent_mcp
python -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt2. Database Initialization
Ensure your SQLite database (movies.db) is populated:
python db_sync.py3. Running the Unified Server
Start the dual REST / MCP server:
python unified_server.pyUpon startup, the server will:
Listen on http://0.0.0.0:8000.
Automatically write openapi.json to the project root.
Expose the MCP SSE endpoint at http://localhost:8000/sse.
Client Integrations
1. Claude Desktop App Setup
To use Claude Sonnet 5 with your movie database tools:
Open or create your Claude Desktop config file:
code ~/Library/Application\ Support/Claude/claude_desktop_config.json2. Add the MCP server configuration:
{
"mcpServers": {
"movie-agent": {
"command": "/Users/matt/Projects/workspace-py/movie_agent_mcp/.venv/bin/python",
"args": [
"/Users/matt/Projects/workspace-py/movie_agent_mcp/unified_server.py"
]
}
}
}3. Restart the Claude Desktop App.
The hammer icon in Claude will confirm the tools (search_trending_movies, list_available_platforms, get_subscription_pricing) are loaded.
2. Open WebUI Integration
User(Left bottom) -> Settings -> (Tools) Integrations -> External Tool Servers -> Click Add+ Name: Movie Agent Description: Movie Agent url: http://host.docker.internal:8000
Select Model -> Tools -> Make the tool default
๐งช Testing & Verification
Check the endpoints directly from your terminal:
# Verify REST OpenAPI schema
curl http://localhost:8000/openapi.json
# Test database movie search
curl "http://localhost:8000/search_trending_movies?genre=horror&min_rating=7.0"
# Verify MCP SSE stream connection
curl http://localhost:8000/sseSonnet
Gemma4
This server cannot be deployed
Maintenance
Related MCP Connectors
Pay-per-use tool marketplace for AI agents. Search, price-check, and call APIs via MCP.
Your agent needs to know where a brand or a phrase is being talked about across the web โ with the trend line, the sentiment and the ratings attached. **What you can ask for** โข "Where is our brand cited across the web this quarter, and is that rising?" โข "What is the sentiment around this phrase?" โข "How do ratings for this product distribute?" โข "Which categories is this topic trending in?" โข "Summarise everything published about this term." **How to use it** Point any MCP client at https://mcp.aisa.one/seo-content/mcp and sign in with OAuth โ there is no key to create or paste. 10 tools: content search, summary, phrase and category trends, sentiment analysis, rating distribution, plus the filters, categories, languages and locations behind them. **It is also a door to the rest** The same login reaches 26 sources and 580+ operations. Find where you are mentioned here, then ask the same agent who links to those pages โ without adding a second server. **What it costs** Finding and inspecting an operation is free. Running one is billed per call at API prices, with no seat and no monthly minimum, and every call takes max_price_usd so an agent cannot overspend by accident. **Where else it reaches** https://mcp.aisa.one/seo/mcp for all of it at once โ rankings, keywords, backlinks, site health and AI-answer visibility across DataForSEO, Semrush and Ahrefs.
Hosted MCP with 91 agent tools: X, domains, SEO, Maps, Trends, Search, YouTube, TikTok, and more.
Independent directory of agentic AI tools โ search, compare & recommend via MCP. Read-only.
Related MCP Servers
- AlicenseBqualityDmaintenanceEnables AI assistants like Claude to interact with The Movie Database (TMDB) API, providing capabilities for searching movies, retrieving movie details, and generating customized movie reviews and recommendations.4138 npm4MIT
- AlicenseNot gradedqualityDmaintenanceProvides integration with The Movie Database (TMDB) API for searching movies, TV shows, and people, accessing detailed information, and discovering popular and trending content. Enables AI assistants to access comprehensive movie and television metadata including ratings, cast, crew, and overviews.35 npm1MIT
- FlicenseAqualityDmaintenanceProvides Claude AI with direct access to The Movie Database (TMDB) for searching movies, trending content, and reviews through natural language.6-
- AlicenseNot gradedqualityCmaintenanceEnables AI agents to query TV and movie metadata from Trakt, including details, trending, popular content, and watch tracking signals through MCP tools.1 npmMIT