Schema | Gemini Embedding 2 MCP Server

Gemini Embedding 2 MCP Server

Describes the environment variables required to run the server.

Name	Required	Description	Default
`GEMINI_API_KEY`	Yes	The Gemini API key from Google AI Studio

Features and capabilities supported by this server

Capability	Details
`tools`	{ "listChanged": false }
`prompts`	{ "listChanged": false }
`resources`	{ "subscribe": false, "listChanged": false }
`experimental`	{}

Functions exposed to the LLM to take actions

Name	Description
index_directoryB	Scans a local directory, extracts text from files (PDF, DOCX, TXT, MD) AND raw video/audio/image bytes, generates semantic embeddings using Gemini 2 and stores them for searching. Args: directory_path: Absolute path to the directory. ignore: Optional list of glob patterns to ignore (e.g., [".log", "drafts", "temp"]).
search_my_documentsC	Performs a semantic search over your previously indexed local documents AND images using the Gemini 2 Embedding model.
preview_directoryB	Summarizes what would be indexed before the server performs a full scan.
list_indexed_directoriesA	Lists indexed parent directories known to the database.
remove_directory_from_indexB	Removes all documents and images belonging to a specific directory path from the index.
sync_indexed_directoriesA	Auto-updates existing folders. It finds all unique parent directories of currently indexed files and re-indexes them to capture new or modified files.
get_result_contextC	Returns nearby chunks or pages for a previously indexed result.

Interactive templates invoked by user choice

Name	Description
No prompts

Contextual data attached and managed by the client

Name	Description
`get_database_stats`	Returns the scale and health of the ChromaDB index for Gemini.

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