# Dsm Mcp

> Dynamic Segmented Memory (DSM) engine for AI agents via Model Context Protocol (MCP).

- **Type:** MCP server
- **Install:** `agentstack add mcp-narelabs-dsm-mcp`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [narelabs](https://agentstack.voostack.com/s/narelabs)
- **Installs:** 0
- **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [narelabs](https://github.com/narelabs)
- **Source:** https://github.com/narelabs/dsm-mcp
- **Website:** https://narelabs.com

## Install

```sh
agentstack add mcp-narelabs-dsm-mcp
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# 🛰️ 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 ©

## Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [narelabs](https://github.com/narelabs)
- **Source:** [narelabs/dsm-mcp](https://github.com/narelabs/dsm-mcp)
- **License:** MIT
- **Homepage:** https://narelabs.com

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/mcp-narelabs-dsm-mcp
- Seller: https://agentstack.voostack.com/s/narelabs
- Browse the marketplace: https://agentstack.voostack.com/browse

---
Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.