A Model Context Protocol (MCP) server that creates a bridge between AI language models and the Trakt.tv API, allowing LLMs to access real-time
If you already use Trakt Mcpserver, the trakt mcpserver mcp server is the piece that lets your assistant work with it directly. A Model Context Protocol (MCP) server that creates a bridge between AI language models and the Trakt.tv API, allowing LLMs to access real-time entertainment data and personal Trakt viewing history. Built with a domain-focused architecture.
Configuration is passed through the environment: TRAKT_CLIENT_ID, TRAKT_CLIENT_SECRET, TRAKT_AUTH_TOKEN_PATH. Treat anything key-shaped as a real credential — scope it to the minimum the server needs, and rotate it if it ever lands in a shared config.
Installation goes through your MCP client rather than a global install: point it at invocations. on PyPI and it is fetched when the client starts. The copy-paste blocks for Claude Desktop, Claude Code and Cursor are further down this page.
Among the developer tooling options, the useful question is rarely "what can it do" but "what does it cost you to run" — permissions, credentials, and how much of your context its toolset consumes. It is maintained by wwiens; worth a glance at recent repository activity before you build anything load-bearing on it.
SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.
{
"mcpServers": {
"trakt": {
"command": "python",
"args": ["/path/to/your/server.py"],
"env": {
"TRAKT_CLIENT_ID": "your_client_id",
"TRAKT_CLIENT_SECRET": "your_client_secret"
}
}
}
}Configuration as documented by the project. Restart the client after saving.
| Variable | Description | Required |
|---|---|---|
| TRAKT_CLIENT_ID | Configuration value read at startup. | Optional |
| TRAKT_CLIENT_SECRET | Credential the server authenticates with. | Yes |
| TRAKT_AUTH_TOKEN_PATH | Credential the server authenticates with. | Yes |
A knowledge graph your assistant keeps between sessions — entities, relations and observations that persist.
Kill hallucinated APIs — version-accurate, up-to-date library documentation injected straight into context.
Your workspace, on speaking terms with AI — search, read and write Notion pages and databases.
A structured scratchpad for hard problems — stepwise reasoning with revisions, branches and visible logic.
Symbol-level code navigation, refactoring and memory for coding agents — the IDE brain your assistant has been missing.
Chat with your second brain — search, read and write vault notes through the Local REST API.