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cachly-dev/cachly-mcp

by Various

AI memory brain for Claude Code, Cursor, Copilot & Windsurf — 51 MCP tools. Persistent sessions, lessons learned, semantic search, Team Brain, managed Valkey/Redis. Free tier.

C

MCP

cachly-dev/cachly-mcp

Added 1 June 2026

#ai-memory #causal-trace #claude-code #cursor #developer-tools #github-copilot #mcp #mcp-server

Overview

Cachly MCP provides 51 MCP tools that give Claude Code, Cursor, Copilot, and Windsurf persistent memory across sessions. It stores lessons learned and enables semantic search, with a Team Brain feature and managed Valkey/Redis backend. A free tier is available.

Best for

Best for
Developers using multiple AI coding assistants who need persistent, shareable memory across sessions.

Use cases

  • Maintain context and learned patterns across multiple AI coding sessions
  • Share project knowledge among team members via Team Brain
  • Retrieve past solutions or decisions using semantic search

Notes

Cachly MCP provides 51 MCP tools that give Claude Code, Cursor, Copilot, and Windsurf persistent memory across sessions. It stores lessons learned and enables semantic search, with a Team Brain feature and managed Valkey/Redis backend. A free tier is available.

1 stars on GitHub. Last updated 2026-05-30. Licensed Apache-2.0.

Use cases

  • Maintain context and learned patterns across multiple AI coding sessions
  • Share project knowledge among team members via Team Brain
  • Retrieve past solutions or decisions using semantic search

Pros

  • Large toolset (51 MCP tools) for flexible memory management
  • Supports multiple popular AI coding assistants
  • Free tier lowers barrier to entry

Cons

  • Low community adoption (1 star on GitHub)
  • Dependency on managed Valkey/Redis may add operational complexity
  • Limited documentation or community support due to early stage

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

Pros

  • Large toolset (51 MCP tools) for flexible memory management
  • Supports multiple popular AI coding assistants
  • Free tier lowers barrier to entry

Cons

  • Low community adoption (1 star on GitHub)
  • Dependency on managed Valkey/Redis may add operational complexity
  • Limited documentation or community support due to early stage
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