Searches TMDB and retrieves movie, TV show, person, detail, and trending-content data through MCP tools.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent โ or use 1-click editor setup below.
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๐ก Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Inspect callable tools, capabilities, and parameters exposed to AI agents by Wizzy MCP Tmdb.
The drakonkat/wizzy-mcp-tmdb MCP server gives MCP-compatible AI clients access to selected The Movie Database data. It is implemented in JavaScript and focuses on discovery and retrieval rather than modifying TMDB records.
The available capabilities described in the project materials are:
search_tmdb.get_tmdb_details.trending_all.Search requests can include a query, page number, language, and adult-content setting. Detail requests identify the media type and item ID, and can request additional related data such as credits and images. Trending requests support a time window, page, and language.
The server communicates with its MCP client over standard input and output. The client invokes a named tool with structured arguments, and the server makes the corresponding request through the TNL TMDB proxy at production-api.tnl.one.
The project documentation identifies TMDB_AUTH_TOKEN as the bearer token used for proxy access. A typical client configuration starts the JavaScript entry point with Node and passes this value through the process environment. The repository also includes unit, integration, and protocol tests, using mocked API responses for API-related test cases.
Running the drakonkat/wizzy-mcp-tmdb MCP server requires Node.js 18 or later because the application relies on global fetch support. Clone the repository, enter its directory, and install the project dependencies with npm. Set TMDB_AUTH_TOKEN in the shell environment before starting the server.
The documented startup command is:
The README also documents npm start as a way to start the project. In an MCP client configuration, use the Node command, configure stdio transport, and provide the token in the server's environment settings. The repository includes an example using an npm-installed package name, but the local source startup command is the clearest documented option for a checkout.
search_tmdb performs a multi-search over movies, television shows, and people. Use it for broad discovery when the media type is not known in advance.
get_tmdb_details fetches information for a specific movie, TV show, or person. Its example accepts an item type and numeric ID, with an optional append value for related data.
trending_all returns trending items across all supported media types. The example accepts a daily or other time-window value, a page number, and a language code.
The server depends on the TNL TMDB proxy and a bearer token supplied through TMDB_AUTH_TOKEN; the README describes that token as coming from an administrator. The material does not establish API quota, pricing, or availability terms for the proxy.
No hosted endpoint is documented. Clients therefore need to run the server locally and connect to its stdio transport. The README mentions IDEs and chat clients generally but does not identify specific clients from the supported-client list. The project is licensed under MIT.
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