Schema | vault-rag-mcp

vault-rag-mcp

Describes the environment variables required to run the server.

Name	Required	Description	Default
`QDRANT_URL`	Yes	Qdrant instance URL (HTTPS requires the :443 port; appended automatically if missing)
`GOOGLE_API_KEY`	Yes	Google AI API key
`QDRANT_API_KEY`	Yes	Qdrant API key
`EMBEDDING_MODEL`	No	Gemini embedding model	gemini-embedding-001

Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.

This server publishes no instructions, or was last inspected before Glama recorded them.

Features and capabilities supported by this server

Protocol revision2025-11-25

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

Functions exposed to the LLM to take actions

Name	Description
search_vaultA	Search the vault semantically. Returns the most relevant notes. Args: query: Natural language search query (works in French and English) limit: Maximum number of results (default 10) para_folder: Filter by PARA folder (1_Projects, 2_Areas, 3_Resources, 4_Archives) note_type: Filter by note type (memo, glossary, howto, meeting-note, etc.)
search_glossaryB	Search the glossary (1878 term definitions in 3_Resources/definitions/). Args: query: Term or concept to look up (works in French and English) limit: Maximum number of results (default 5)
get_noteA	Retrieve the full content of a specific note by its file path. Args: file_path: Path relative to vault root (e.g. '3_Resources/definitions/p/powerflex.md')

Interactive templates invoked by user choice

Name	Description
No prompts

Contextual data attached and managed by the client

Name	Description
No resources

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

curl -X GET 'https://glama.ai/api/mcp/v1/servers/fjacquet/vault-rag-mcp'

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