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Wizzy Mcp Tmdb

Wizzy Mcp Tmdb

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github.com/drakonkatGames & Entertainment4Updated 56w ago

About Wizzy Mcp Tmdb

A JavaScript MCP server that provides AI clients with TMDB movie, TV, and person information. Its tools cover multi-category search, item details, and trending content.

Key features

  1. 01Search movies, TV shows, and people
  2. 02Retrieve details for a specific item
  3. 03Fetch trending content across media types

Use cases

  1. 01Search TMDB for a title or person
  2. 02Retrieve details about a movie or show
  3. 03Check trending content across media types

MCP support

Exposes `search_tmdb`, `get_tmdb_details`, and `trending_all` as tools for MCP-compatible clients over stdio. The server uses a TMDB API token supplied through `TMDB_AUTH_TOKEN`.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"wizzy-mcp-tmdb": {
"command": "npx",
"args": [
"-y",
"wizzy-mcp-tmdb"
],
"env": {
"TMDB_AUTH_TOKEN": "<TMDB_AUTH_TOKEN>"
}
}
}
}
Run commandnpx -y wizzy-mcp-tmdb
Environment variables to set
TMDB_AUTH_TOKENSecret

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
npmwizzy-mcp-tmdb

Tools

No tool list yet

Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.

Details

From the project README

wizzy-mcp-tmdb

Build Status

Coverage

Project Overview and Purpose

The wizzy-mcp-tmdb project is an MCP (Model Context Protocol) server implemented in JavaScript that provides tools to search and retrieve information from The Movie Database (TMDB). It allows AI clients to access movie, TV show, and person data through a standardized protocol.

Key Features

  • Search Movies: Perform multi-search across movies, TV shows, and people using the search_tmdb tool.
  • Get Details: Fetch detailed information for specific items using the get_tmdb_details tool.
  • Trending Content: Retrieve trending content across all media types with the trending_all tool.

Installation

Prerequisites
  • Node.js version 18 or higher (required for global fetch support)
  • A TMDB API key (Bearer token) from your admin, used with the TNL TMDB proxy (production-api.tnl.one)
Setup
  1. Clone the repository and navigate to the project directory.

  2. Install dependencies:

    npm install
    
  3. Set up your TMDB API key as an environment variable:

    • On Windows PowerShell:

      $env:TMDB_AUTH_TOKEN="YOUR_TNL_PROXY_BEARER_TOKEN"
      
    • On macOS/Linux:

      export TMDB_AUTH_TOKEN="YOUR_TNL_PROXY_BEARER_TOKEN"
      

Usage

Starting the MCP Server

To start the server:

npm start

The server communicates over stdio and should be configured in your MCP-compatible client (e.g., IDE or chat client) with the command node mcp-tmdb-server.js and the TMDB_AUTH_TOKEN environment variable.

MCP Integration Examples

Here are code snippets showing how to integrate with the MCP tools:

Search for Movies
// Example MCP tool call for searching
{
  "method": "tools/call",
  "params": {
    "name": "search_tmdb",
    "arguments": {
      "query": "dune",
      "page": 1,
      "language": "en-US",
      "include_adult": false
    }
  }
}
Get Movie Details
// Example MCP tool call for getting details
{
  "method": "tools/call",
  "params": {
    "name": "get_tmdb_details",
    "arguments": {
      "type": "movie",
      "id": 438631,
      "append": "credits,images"
    }
  }
}
Get Trending Content
// Example MCP tool call for trending content
{
  "method": "tools/call",
  "params": {
    "name": "trending_all",
    "arguments": {
      "time_window": "day",
      "page": 1,
      "language": "en-US"
    }
  }
}

MCP Client Integration

Per integrare questo MCP server nel tuo client MCP (come un IDE o un client di chat compatibile), segui questi passi:

  1. Installa il pacchetto npm se necessario:

    npm install -g wizzy-mcp-tmdb
    
  2. Crea o aggiorna il file mcp.json nel tuo client MCP con la seguente configurazione:

    {
      "mcpServers": {
        "tmdb": {
          "command": "npx",
          "args": ["wizzy-mcp-tmdb"],
          "env": {
            "TMDB_AUTH_TOKEN": "YOUR_TNL_PROXY_BEARER_TOKEN"
          },
          "alwaysAllow": [
            "get_watch_providers",
            "discover_tv",
            "discover_by_provider"
          ]
        }
      }
    }
    

    Nota: Il TMDB_AUTH_TOKEN può essere impostato a un valore casuale per ora, poiché le chiamate API TMDB sono gratuite e non richiedono autenticazione obbligatoria.

Testing Strategy

The project uses Jest for comprehensive testing, including:

  • Unit Tests: Validate individual handler functions, input validation, and response formatting (see tests/unit/handlers.test.js).
  • Integration Tests: Test API interactions with mocked responses, error handling, and network failures (see tests/integration/api.test.js).
  • Protocol Tests: Ensure MCP protocol compliance, including tool listing and calling (see tests/protocol/mcp.test.js).

Run the test suite with:

npm test

For watch mode:

npm run test:watch

Project Structure

wizzy-mcp-tmdb/
├── mcp-tmdb-server.js          # Main MCP server implementation
├── package.json                # Project configuration and dependencies
├── MCP_GUIDE.md                # Detailed MCP integration guide
├── babel.config.cjs            # Babel configuration for Jest
├── tests/
│   ├── unit/
│   │   └── handlers.test.js    # Unit tests for handlers
│   ├── integration/
│   │   └── api.test.js         # Integration tests for API calls
│   └── protocol/
│       └── mcp.test.js         # MCP protocol compliance tests
└── tests/fixtures/             # Mock data for tests
    ├── movieDetails.json
    ├── searchMultiResponse.json
    └── trendingAllResponse.json

Contributing

We welcome contributions! Please follow these guidelines:

  1. Fork the repository.
  2. Create a feature branch.
  3. Make your changes and add tests.
  4. Ensure all tests pass.
  5. Submit a pull request.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Acknowledgments

  • Thanks to The Movie Database (TMDB) for providing the API.
  • Built using the Model Context Protocol SDK.

Contact

For questions or support, please open an issue on GitHub.

Comments

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New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.