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Conxt Memory Layer MCP Server

@pgavali0318

代码仓库

基本信息

分类

AI 与智能体

传输方式

stdio

作者

pgavali0318

提交者

Priyadarshi Gavali

关于 Conxt Memory Layer MCP Server

Persistent AI memory layer for developers. Stores decisions, coding rules, preferences, tool choices, and workflows across Claude, ChatGPT, Gemini, Cursor, and Windsurf. 8 MCP tools including get_context, add_memory, search_decisions, and team workspaces. Never re-explain your st

#memory#developer-tools#productivity#cursor#claude#ai-agents

Conxt Memory Layer MCP Server 配置

使用下面的配置,将此服务器添加到你的 MCP 客户端。

{
  "mcpServers": {
    "conxt": {
      "url": "https://mcp.conxt.dev/mcp/",
      "headers": {
        "Authorization": "Bearer YOUR_CNXT_API_KEY"
      }
    }
  }
}

Conxt Memory Layer MCP Server 工具

工具列表暂未提供

当前收录暂时没有可展示的工具列表，不代表服务没有工具。请查阅项目文档了解支持的能力。

点击上方按钮,直接连接服务器端点实时获取工具列表。

概览

What is Conxt Memory Layer?

Conxt Memory Layer is a persistent AI memory layer for developers. It stores decisions, coding rules, preferences, tool choices, and workflows across Claude, ChatGPT, Gemini, Cursor, and Windsurf, providing 8 MCP tools including get_context, add_memory, search_decisions, and team workspaces.

How to use Conxt Memory Layer?

The README does not provide installation, configuration, or invocation instructions. Refer to the server's documentation for details.

Key features of Conxt Memory Layer

  • Persistent AI memory across multiple platforms
  • Supports Claude, ChatGPT, Gemini, Cursor, Windsurf
  • 8 MCP tools: get_context, add_memory, search_decisions
  • Team workspaces for shared memory
  • Stores decisions, coding rules, preferences, workflows

Use cases of Conxt Memory Layer

  • Avoid re-explaining your preferences to different AI assistants
  • Maintain consistent coding rules across tools and sessions
  • Share team memory for collaborative development workflows

常见问题

1

Which AI platforms does it work with?

Claude, ChatGPT, Gemini, Cursor, and Windsurf.

2

What tools does it provide?

8 MCP tools including get_context, add_memory, search_decisions, and team workspaces.

3

Is it for individual or team use?

It supports both individual and team workspaces.

4

What kind of data does it store?

Decisions, coding rules, preferences, tool choices, and workflows.

评论

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