dsm-mcp

# 🛰️ DSM: Dynamic Segmented Memory (MCP Server) [](https://modelcontextprotocol.io) [](https://opensource.org/licenses/MIT) []() **DSM** is a high-performance Dynamic Segmented Memory engine implemented as an **MCP (Model Context Protocol)** server. Unlike traditional vector databases, DSM organizes information into a hierarchy of segments, supports hybrid search, and enables multi-hop reasoning directly over your knowledge base. --- ## 🔌 What is MCP? The **Model Context Protocol (MCP)** is an open standard that enables AI agents (like Claude Desktop, Cursor, or Windsurf) to securely connect to external data and tools. By running **DSM as an MCP server**, you give your AI agent a persistent "long-term memory" that it can query, write to, and reason with, using a standardized set of tools. --- ## 🛠️ Features - **Hybrid Search**: Seamlessly combines Dense (semantic) and Sparse (BM25) search for maximum retrieval precision. - **Reasoning**: The `dsm_reason` tool allows agents to traverse the memory graph, finding deep connections instead of just keywords. - **Auto-Sync**: One-click indexing of your entire project via `dsm_sync`. - **Conflict Control**: Automatically detects contradictory information within the memory. --- ## 🚀 Quick Start ### 1. Install ```bash pip install mcp dsm-memory ``` ### 2. Configure MCP Add the server to your `claude_desktop_config.json` or `.claude.json`: ```json { "mcpServers": { "dsm": { "command": "python", "args": ["path/to/mcp_server.py"], "env": { "DSM_PROJECT_ROOT": "/path/to/your/project" } } } } ``` --- ## 🔌 Tools - `dsm_search`: Fast hybrid search over all memory segments. - `dsm_write`: Manually commit new insights or architectural data. - `dsm_reason`: Multi-hop recursive search for deep context. - `dsm_sync`: Full codebase indexing and synchronization. - `dsm_info`: Live statistics about the memory state. --- ## 📄 License MIT ©