MCP 服务器

Memsolus MCP Server

Provides persistent long-term memory for AI agents through semantic search and automated knowledge graph extraction. It enables agents to store, recall, and reason over facts, preferences, and relationships across multiple conversations and sessions.

README

@memsolus/mcp

Persistent memory for AI agents. One line to install, zero config to remember everything.

Give your AI agents the ability to store, recall, and reason over long-term memory — preferences, facts, decisions, relationships, and structured knowledge — across conversations and sessions.

Built on the Model Context Protocol, works with Claude, GPT, and any MCP-compatible client.

Why Memsolus?

Semantic search — Find memories by meaning, not just keywords. Hybrid search combines both for best results.
Knowledge graph — Entities and relationships are automatically extracted. Ask "Who works on Project X?" and get structured answers.
Auto-consolidation — Raw memories are processed into structured knowledge profiles, versioned and categorized.
Memory pools — Shared memory spaces for teams and multi-agent collaboration.
Priority-aware — Mark critical rules as HIGH priority. They rank higher in search and resist pruning.
Multi-tenant — Isolate context per user, agent, or workspace. Fine-grained scoping built in.

Setup

Get your API key at app.memsolus.com/api-keys, then add the server to your tool:

Claude Desktop

Add to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):

{
  "mcpServers": {
    "memsolus": {
      "command": "npx",
      "args": ["-y", "@memsolus/mcp"],
      "env": {
        "MEMSOLUS_API_KEY": "mk_live_..."
      }
    }
  }
}

Claude Code

claude mcp add memsolus -- npx -y @memsolus/mcp

Then set your key in .claude/settings.local.json:

{
  "env": {
    "MEMSOLUS_API_KEY": "mk_live_..."
  }
}

Cursor

Add to .cursor/mcp.json in your project root:

{
  "mcpServers": {
    "memsolus": {
      "command": "npx",
      "args": ["-y", "@memsolus/mcp"],
      "env": {
        "MEMSOLUS_API_KEY": "mk_live_..."
      }
    }
  }
}

Windsurf

Add to ~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "memsolus": {
      "command": "npx",
      "args": ["-y", "@memsolus/mcp"],
      "env": {
        "MEMSOLUS_API_KEY": "mk_live_..."
      }
    }
  }
}

VS Code (Copilot)

Add to .vscode/mcp.json in your project:

{
  "servers": {
    "memsolus": {
      "command": "npx",
      "args": ["-y", "@memsolus/mcp"],
      "env": {
        "MEMSOLUS_API_KEY": "mk_live_..."
      }
    }
  }
}

Zed

Add to Zed settings (Cmd+, > assistant > mcp):

{
  "context_servers": {
    "memsolus": {
      "command": {
        "path": "npx",
        "args": ["-y", "@memsolus/mcp"],
        "env": {
          "MEMSOLUS_API_KEY": "mk_live_..."
        }
      }
    }
  }
}

Any MCP-compatible client

The server runs over stdio by default. Point your client to:

npx -y @memsolus/mcp

With the environment variable MEMSOLUS_API_KEY set.

What your agent can do

Capability	Tools
Store & retrieve	`add_memory`, `get_memory`, `get_memories`, `update_memory`, `delete_memory`
Semantic search	`search_memories` — hybrid, semantic, or keyword mode
Knowledge profiles	`get_knowledge` — auto-compiled from memories, merged as Markdown
Shared pools	`list_pools`, `add_memory_to_pool`, `search_pool`
Knowledge graph	`graph_search`, `graph_traverse`, `graph_query`
Housekeeping	`list_entities`, `delete_all_memories`

15 tools total. All exposed automatically via MCP.

Use Cases

Personalized assistants — Remember user preferences, past decisions, and context across sessions
Multi-agent systems — Shared memory pools let agents collaborate with common context
Knowledge management — Auto-extract entities and relationships from unstructured text
Customer support — Recall full interaction history and customer preferences instantly
Research agents — Accumulate findings across sessions, search by concept

Self-Hosting

If you're running your own Memsolus API instance, use the MEMSOLUS_API_URL variable to point to it:

{
  "mcpServers": {
    "memsolus": {
      "command": "npx",
      "args": ["-y", "@memsolus/mcp"],
      "env": {
        "MEMSOLUS_API_KEY": "mk_live_...",
        "MEMSOLUS_API_URL": "https://your-instance.example.com"
      }
    }
  }
}

Programmatic Usage

import { createServer } from '@memsolus/mcp';
import { StdioServerTransport } from '@modelcontextprotocol/sdk/server/stdio.js';

const server = createServer({
  baseUrl: 'https://api.memsolus.com',
  apiKey: process.env.MEMSOLUS_API_KEY,
});

const transport = new StdioServerTransport();
await server.connect(transport);