MCP.so
Sign In

Conxt Memory Layer

@pgavali0318

About Conxt Memory Layer

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

Basic information

Category

AI & Agents

Transports

stdio

Publisher

pgavali0318

Submitted by

Priyadarshi Gavali

Config

Add this server to your MCP-compatible client using the configuration below.

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

Tools

No tools detected

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

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

FAQ from Conxt Memory Layer

Which AI platforms does it work with?

Claude, ChatGPT, Gemini, Cursor, and Windsurf.

What tools does it provide?

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

Is it for individual or team use?

It supports both individual and team workspaces.

What kind of data does it store?

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

Are there any known limitations?

Comments

More AI & Agents MCP servers