Knowledge_vault
@fak111
About Knowledge_vault
A local knowledge management MCP server built with FastMCP framework.
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"knowledge-vault": {
"command": "uv",
"args": [
"--directory",
"/path/to/your/local_store_mcp",
"run",
"python",
"start_server_new.py"
],
"cwd": "/path/to/your/local_store_mcp",
"description": "Local Knowledge Management MCP Server"
}
}
}Tools
No tools detected
We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.
Overview
What is Knowledge_vault?
Knowledge_vault is a local knowledge management MCP server built with the FastMCP framework and Python. It enables users to store, search, and manage knowledge records directly on their machine, with features like automatic title generation, tag suggestion, and fuzzy search. It is intended for developers and power users who want a private, file-based knowledge base integrated with MCP-compatible clients (e.g., Claude Desktop).
How to use Knowledge_vault?
After installing dependencies with uv, add the server configuration to your Claude Desktop config file (~/.config/claude_desktop_config.json) using the provided JSON snippet, then restart Claude Desktop. Use natural language commands like “Store a programming tip: …” or “Search for Python knowledge” to interact with the server.
Key features of Knowledge_vault
- Smart storage with auto-generated titles and tags
- Fuzzy search and tag filtering
- AI-suggested tags based on content
- Knowledge base usage statistics
- Data stored securely in user home directory
- Thread-safe concurrent access with file locking
Use cases of Knowledge_vault
- Save programming tips and retrieve them later via search
- Organize notes by auto-suggested tags for quick filtering
- View statistics on how many records have been stored
- Retrieve a specific knowledge record by its ID
- Search across the knowledge base using fuzzy matching
FAQ from Knowledge_vault
Where does Knowledge_vault store data?
Data is stored in the user’s home directory at ~/.knowledge-vault/knowledge.jsonl in JSON Lines format.
How do I install Knowledge_vault for use with Claude Desktop?
Use uv to sync dependencies, then add the server configuration to ~/.config/claude_desktop_config.json as shown in the README, and restart Claude Desktop.
What tools does Knowledge_vault expose?
It provides seven tools: store_knowledge, search_knowledge, list_recent, get_knowledge, suggest_tags, search_by_tags, and get_stats.
Is Knowledge_vault safe to use concurrently?
Yes, the server is thread safe and uses file locking for concurrent access.
What runtime does Knowledge_vault require?
Python 3.10 or newer, along with the uv package manager for dependency management.
Frequently asked questions
Where does Knowledge_vault store data?
Data is stored in the user’s home directory at `~/.knowledge-vault/knowledge.jsonl` in JSON Lines format.
How do I install Knowledge_vault for use with Claude Desktop?
Use `uv` to sync dependencies, then add the server configuration to `~/.config/claude_desktop_config.json` as shown in the README, and restart Claude Desktop.
What tools does Knowledge_vault expose?
It provides seven tools: `store_knowledge`, `search_knowledge`, `list_recent`, `get_knowledge`, `suggest_tags`, `search_by_tags`, and `get_stats`.
Is Knowledge_vault safe to use concurrently?
Yes, the server is thread safe and uses file locking for concurrent access.
What runtime does Knowledge_vault require?
Python 3.10 or newer, along with the `uv` package manager for dependency management.
Basic information
More Memory & Knowledge MCP servers
Snipara
alopez3006MCP connector for Snipara, the Project Brain for AI coding agents
Notion MCP Server
suekouA Model Context Protocol server for connecting Notion to MCP-compatible clients
Context Portal MCP (ConPort)
GreatScottyMacContext Portal (ConPort): A memory bank MCP server building a project-specific knowledge graph to supercharge AI assistants. Enables powerful Retrieval Augmented Generation (RAG) for context-aware development in your IDE.
RAG Documentation MCP Server
hannesrudolphAn MCP server implementation that provides tools for retrieving and processing documentation through vector search, enabling AI assistants to augment their responses with relevant documentation context.
Rust Docs MCP Server
Govcraft🦀 Prevents outdated Rust code suggestions from AI assistants. This MCP server fetches current crate docs, uses embeddings/LLMs, and provides accurate context via a tool call.
Comments