Schema | gemini-embedding-2-mcp-server

gemini-embedding-2-mcp-server

Describes the environment variables required to run the server.

Name	Required	Description	Default
`FOLDER_PATH`	Yes	Path to the local folder to index
`GEMINI_API_KEY`	Yes	Your Gemini API key for embedding

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_documentsB	Performs a semantic search over your previously indexed local documents AND images using the Gemini 2 Embedding model.
list_indexed_directoriesB	Lists all the file paths that have been indexed in the database.
remove_directory_from_indexC	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.

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.

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/elkalowkey885/gemini-embedding-2-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server