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memstate-ai/memstate-mcp

by Various

memstate-ai/memstate-mcp — indexed from awesome-mcp-servers-punkpeye

M

MCP

memstate-ai/memstate-mcp

Added 1 June 2026

#agent-memory #ai-agents #ai-memory #claude #cline #cursor #mcp #memory-management

Overview

memstate-ai/memstate-mcp is a Model Context Protocol server for managing memory state, built in TypeScript. It is listed in the awesome-mcp-servers collection and has 3 GitHub stars.

Best for

Best for
Developers exploring MCP-based memory solutions in early-stage projects

Use cases

  • Integrating persistent memory into AI agent workflows
  • Storing and retrieving context across MCP sessions
  • Experimenting with stateful MCP server implementations

How to use

Install

claude mcp add memstate npx @memstate/mcp -e MEMSTATE_API_KEY=YOUR_API_KEY_HERE

Tools exposed

  • memstate_remember
  • memstate_set
  • memstate_get
  • memstate_search
  • memstate_history
  • memstate_delete
  • memstate_delete_project
  • MEMSTATE_API_KEY
  • MEMSTATE_MCP_URL

Tested with

Claude Desktop, Claude Code, Cursor, Windsurf, Cline

Example client config

{\n  "mcpServers": {\n    "memstate": {\n      "command": "npx",\n      "args": ["-y", "@memstate/mcp"],\n      "env": {\n        "MEMSTATE_API_KEY": "YOUR_API_KEY_HERE"\n      }\n    }\n  }\n}

Notes

memstate-ai/memstate-mcp is a Model Context Protocol server for managing memory state, built in TypeScript. It is listed in the awesome-mcp-servers collection and has 3 GitHub stars.

3 stars on GitHub. Last updated 2026-04-01. Licensed Apache-2.0.

Use cases

  • Integrating persistent memory into AI agent workflows
  • Storing and retrieving context across MCP sessions
  • Experimenting with stateful MCP server implementations

Pros

  • Written in TypeScript for type safety
  • Follows the MCP standard for interoperability

Cons

  • Very low community adoption (3 stars)
  • Limited documentation and examples
  • Unclear production readiness

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

Pros

  • Written in TypeScript for type safety
  • Follows the MCP standard for interoperability

Cons

  • Very low community adoption (3 stars)
  • Limited documentation and examples
  • Unclear production readiness

Pairs with

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