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darktw/usecortex-mcp

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UseCortex MCP Server — Give your AI coding agent a persistent memory. Read and write knowledge from any tool.

D

MCP

darktw/usecortex-mcp

Added 1 June 2026

#ai-memory #ai-tools #context #developer-tools #encrypted #knowledge-management #mcp #mcp-server

Overview

UseCortex MCP Server provides a persistent memory layer for AI coding agents. It allows reading and writing knowledge from any tool that supports the Model Context Protocol. The server is written in JavaScript and is available on GitHub.

Best for

Best for
Developers building AI coding agents that need a lightweight persistent memory solution

Use cases

  • Give an AI coding agent persistent memory across sessions
  • Store and retrieve context or knowledge from any MCP-compatible tool
  • Enable AI agents to remember user preferences or project details

Notes

UseCortex MCP Server provides a persistent memory layer for AI coding agents. It allows reading and writing knowledge from any tool that supports the Model Context Protocol. The server is written in JavaScript and is available on GitHub.

0 stars on GitHub. Last updated 2026-03-17. Licensed MIT.

Use cases

  • Give an AI coding agent persistent memory across sessions
  • Store and retrieve context or knowledge from any MCP-compatible tool
  • Enable AI agents to remember user preferences or project details

Pros

  • Provides persistent memory for AI agents without external databases
  • Works with any tool that supports the Model Context Protocol
  • Simple read/write interface for knowledge storage

Cons

  • Zero stars on GitHub indicates very limited adoption or early stage
  • Lack of community support or documentation may hinder troubleshooting
  • Unproven reliability and potential instability due to low usage

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Provides persistent memory for AI agents without external databases
  • Works with any tool that supports the Model Context Protocol
  • Simple read/write interface for knowledge storage

Cons

  • Zero stars on GitHub indicates very limited adoption or early stage
  • Lack of community support or documentation may hinder troubleshooting
  • Unproven reliability and potential instability due to low usage