Which integrations are available for this server?

Uses SQLite with FTS5 for data storage and fast full-text search, providing persistent memory storage in a local database file with zero external dependencies.

How do I use Memory Search MCP Server?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Memory Search MCP Server search for user's UI preferences from last week" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

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Memory Search MCP Server

by CSOAI-ORG

Overview Schema Related Servers Score Discussions

Python

Local

Memory Search MCP

MCP server for memory search mcp operations

Overview

Memory Search MCP provides AI-powered tools via the Model Context Protocol (MCP).

Tools

Tool	Description
`record_memory`	Record a memory episode with care-weighting and emotional valence.
`search_memory`	Semantic search across all memories using full-text search with relevance rankin
`add_knowledge`	Add a knowledge entry to the persistent knowledge base.
`search_knowledge`	Search the knowledge base by topic or content. Returns facts and reference
`list_memories`	List recent memories, optionally filtered by type. Sort by created_at,
`get_memory_stats`	Get statistics about the memory store: total count, type breakdown,
`get_temporal_chain`	Follow the temporal chain from a memory episode forward or backward in time.
`consolidate_memories`	Consolidate old, low-access memories by summarizing and archiving them.
`semantic_search`	Semantic search using TF-IDF cosine similarity (no external deps).

Installation

pip install meok-memory-search-mcp

Usage with Claude Desktop

Add to your Claude Desktop MCP config (claude_desktop_config.json):

{
  "mcpServers": {
    "memory-search-mcp": {
      "command": "python",
      "args": ["-m", "meok_memory_search_mcp.server"]
    }
  }
}

Usage with FastMCP

from mcp.server.fastmcp import FastMCP

# This server exposes 9 tool(s) via MCP
# See server.py for full implementation

License

MIT © MEOK AI Labs

This server cannot be installed

license - permissive license

quality - not tested

maintenance

How are these scores calculated?

Maintenance

–Maintainers

–Response time

–Release cycle

1Releases (12mo)

Resources

GitHub Repository

Need Help?

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