A dynamic, agent/LLM-friendly SQLite memory bank for MCP servers with semantic search capabilities.
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# mcp_sqlite_memory_bank    ## Overview **mcp_sqlite_memory_bank** is a dynamic, agent- and LLM-friendly SQLite memory bank designed for Model Context Protocol (MCP) servers and modern AI agent platforms. This project provides a robust, discoverable API for creating, exploring, and managing SQLite tables and knowledge graphs. It enables Claude, Anthropic, Github Copilot, Claude Desktop, VS Code, Cursor, and other LLM-powered tools to interact with structured data in a safe, explicit, and extensible way. **Key Use Cases:** - Build and query knowledge graphs for semantic search and reasoning - Store, retrieve, and organize notes or structured data for LLM agents - Enable natural language workflows for database management and exploration - Intelligent content discovery with semantic search capabilities - Access memory content through standardized MCP Resources and Prompts - Integrate with FastMCP, Claude Desktop, and other agent platforms for seamless tool discovery **Why mcp_sqlite_memory_bank?** - **Full MCP Compliance:** Resources, Prompts, and 40+ organized tools - **Semantic Search:** Natural language content discovery with AI-powered similarity matching - **Explicit, discoverable APIs** for LLMs and agents with enhanced categorization - Safe, parameterized queries and schema management - Designed for extensibility and open source collaboration --- ## Quick Start Get started with SQLite Memory Bank in your IDE in under 2 minutes: ### 1. Install and Run ```bash # Install uvx if you don't have it pip install uvx # Run SQLite Memory Bank uvx mcp-sqlite-memory-bank ``` ### 2. Configure Your IDE **VS Code / Cursor:** Add to `.vscode/mcp.json`: ```jsonc { "servers": { "SQLite_Memor…
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