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n-r-w/knowledgegraph-mcp

开发工具

本页由 AI 翻译,技术细节请以原文为准。 查看原文

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MCP 服务器通过知识图谱实现 Claude 的持久性知识存储,后端多存储和模糊搜索

概览

我对这类自动化上下文管理工具感到失望,因为它几乎无法控制。过了一段时间,我总得手动清理混乱或纠正不合适的LLM笔记。相反,我创建了一个工具,让LLM代理访问动态加载的上下文。不过,上下文本身是用户创建的:https://github.com/n-r-w/agent-standards-mcp 一种简单的方法,让LLM在对话中持续记忆。这个服务器让Claude或vscode通过知识图谱记住关于你、你的项目和偏好的信息。 主要功能:- : PostgreSQL(推荐)或 SQLite(本地文件)- : 保持不同项目隔离(通过提示自动检测) - : 通过模糊搜索和分页查找信息 请按照以下步骤让知识图谱在Claude上运行: - 无需安装数据库 - 自动创建在[你的主文件夹]/中的数据库文件。

概述(AI 翻译)

我对这类自动化上下文管理工具感到失望,因为几乎无法控制。过了一段时间,我总得手动清理杂乱或纠正不合适的LLM笔记。 相反,我创建了一个工具,让LLM代理访问动态加载的上下文。不过,上下文本身是用户创建的:https://github.com/n-r-w/agent-standards-mcp

KnowledgeGraph MCP 服务器

一种简单的方法,让LLM在对话中持续记忆。这个服务器让Claude或vscode通过知识图谱记住关于你、你的项目和偏好的信息。

主要特色:

  • 多存储后端:PostgreSQL(推荐)或SQLite(本地文件)
  • 项目分离:保持不同项目隔离(通过提示自动检测)
  • Better Search:通过模糊搜索和分页查找信息

完整设置指南

请按照以下步骤让知识图谱在Claude上运行:

第一步:选择安装方法

选项A:NPX(最简单——无需下载)

选项B:Docker

第二步:选择你的数据库

SQLite(默认设置——无需设置):

  • 无需安装数据库

本页由 AI 翻译,技术细节请以原文为准。

README

以下为原文 README 节选,完整内容请查看原文。

WARNING

I’ve become disillusioned with automated context management tools like this, as it’s nearly impossible to control. After a while, I always have to manually clean up the mess or correct inappropriate LLM notes. Instead, I created a tool that gives the LLM agent access to dynamically loaded context. However, the context itself is user-created: https://github.com/n-r-w/agent-standards-mcp

KnowledgeGraph MCP Server

A simple way to give LLMs persistent memory across conversations. This server lets Claude or vscode remember information about you, your projects, and your preferences using a knowledge graph.

Key Features:

  • Multiple Storage Backends: PostgreSQL (recommended) or SQLite (local file)
  • Project Separation: Keep different projects isolated (auto-detected using prompts)
  • Better Search: Find information with fuzzy search and pagination

Complete Setup Guide

Follow these steps in order to get the knowledge graph working with Claude:

Step 1: Choose Your Installation Method

Option A: NPX (Easiest - No download needed)

# Test that it works
npx knowledgegraph-mcp --help

Option B: Docker

# Clone and build
git clone https://github.com/n-r-w/knowledgegraph-mcp.git
cd knowledgegraph-mcp
docker build -t knowledgegraph-mcp .

Step 2: Choose Your Database

SQLite (Default - No setup needed):

  • No database installation required
  • Database file created automatically in [you home folder]/.knowledge-graph/
  • Perfect for personal use and most scenarios
  • This is the default backend

PostgreSQL (For advanced users):

  • Install PostgreSQL on your system
  • Create a database: CREATE DATABASE knowledgegraph;
  • Better for production use with multiple concurrent users

Step 3: Configure client

Claude Desktop

Edit your Claude Desktop configuration file:

Find your config file:

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
  • Windows: %APPDATA%\Claude\claude_desktop_config.json
  • Linux: ~/.config/Claude/claude_desktop_config.json

If you chose NPX + SQLite (default and easiest):

{
  "mcpServers": {
    "Knowledge Graph": {
      "command": "npx",
      "args": ["-y", "knowledgegraph-mcp"]
    }
  }
}

Note: SQLite will automatically create the database in [you home folder]/.knowledge-graph/knowledgegraph.db. To use a custom location, add: "KNOWLEDGEGRAPH_SQLITE_PATH": "/path/to/your/database.db"

If you chose Docker + SQLite (default):

{
  "mcpServers": {
    "Knowledge Graph": {
      "command": "docker",
      "args": [
        "run", "-i", "--rm",
        "-v", "[you home folder]/.knowledge-graph:/app/.knowledge-graph",
        "knowledgegraph-mcp"
      ]
    }
  }
}
在 GitHub 查看完整 README

安装

npx -y knowledgegraph-mcp
新手?先看 mcpskill.org 教程 →

配置

{ "mcpServers": { "Knowledge Graph": { "command": "npx", "args": ["-y", "knowledgegraph-mcp"] } } }