Vector Memory Mcp Server
@Xsaven
About Vector Memory Mcp Server
Vector Memory MCP Server
Basic information
Config
Add this server to your MCP-compatible client using the configuration below.
{
"mcpServers": {
"vector-memory": {
"command": "uvx",
"args": [
"vector-memory-mcp",
"--working-dir",
"/absolute/path/to/your/project"
]
}
}
}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 Vector Memory MCP Server?
Vector Memory MCP Server is a secure, vector-based memory server for Claude Desktop that uses sqlite-vec and sentence-transformers. It provides persistent semantic memory capabilities to enhance AI coding assistants by remembering and retrieving relevant coding experiences, solutions, and knowledge.
How to use Vector Memory MCP Server?
Install via uvx (recommended) or from source. Configure Claude Desktop by adding a JSON entry pointing to the server and a working directory. Then use available tools such as store_memory, search_memories, list_recent_memories, get_memory_stats, clear_old_memories, get_by_memory_id, and delete_by_memory_id via natural language commands.
Key features of Vector Memory MCP Server
- Semantic search using 384-dimensional embeddings
- Persistent SQLite storage with vector indexing
- Smart organization with categories and tags
- Input validation, path sanitization, and resource limits
- Fast embedding generation with
sentence-transformers - Automatic deduplication via SHA-256 content hashing
- Access tracking with counts and timestamps
- Smart cleanup algorithm based on recency and importance
Use cases of Vector Memory MCP Server
- Store and retrieve code patterns, bug fixes, and architecture decisions
- Maintain team conventions, deployment procedures, and infrastructure knowledge
- Capture learning insights, performance discoveries, and security learnings
- Enable semantic search across past coding experiences and solutions
FAQ from Vector Memory MCP Server
What is the technical stack of Vector Memory MCP Server?
It uses sqlite-vec for vector storage and similarity search, the sentence-transformers/all-MiniLM-L6-v2 model for 384-dimensional embeddings, and the FastMCP framework.
What are the security limits?
Maximum memory content length is 10,000 characters, maximum total memories is 10,000 entries, maximum search results per query is 50, and maximum tags per memory is 10. Path validation blocks suspicious characters.
How does semantic search work?
Memories are converted into 384-dimensional vectors that capture semantic meaning. Search queries are embedded and compared using similarity scoring (0.6–1.0 range) to find relevant matches.
How can I install Vector Memory MCP Server?
You can install via uvx (recommended), from source using uv, or with pipx. Publishing to PyPI is in progress.
What dependencies are required?
Python 3.10 or higher (recommended 3.11), the uv package manager, and the Claude Desktop app.
More Memory & Knowledge MCP servers
Memory Bank MCP Server
alioshrA Model Context Protocol (MCP) server implementation for remote memory bank management, inspired by Cline Memory Bank.
Ultimate Google Docs & Drive MCP Server
a-bonusThe Ultimate Google Docs, Sheets, Drive, Gmail, & Google Calendar MCP Server. This MCP (primarily for use in Claude Desktop) gains full access to your google suite and lets claude do its thing.
minutes
silversteinEvery meeting, every idea, every voice note — searchable by your AI. Open-source, privacy-first conversation memory layer.
Zettelkasten MCP Server
entanglrA Model Context Protocol (MCP) server that implements the Zettelkasten knowledge management methodology, allowing you to create, link, explore and synthesize atomic notes through Claude and other MCP-compatible clients.
Semantic Scholar MCP Server
YUZongminA FastMCP server implementation for the Semantic Scholar API, providing comprehensive access to academic paper data, author information, and citation networks.
Comments