ContextOS
Related Servers
Alternatives to ContextOS
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityBmaintenanceStandardize Context, Not Intelligence. An open protocol and native MCP server for preserving, organizing, and serving structured project context (architecture, decision logs, domain rules, and roadmap) to AI coding assistants (Cursor, Claude Desktop, Antigravity) with built-in CLI verificationMIT
- AlicenseNot gradedqualityDmaintenancePersistent memory MCP server for Claude Code that captures and recalls project context across sessions, eliminating the need to re-explain architecture and decisions daily.73 npm1MIT
- AlicenseAqualityBmaintenancePersistent memory MCP server for Claude Code, Cursor, and GitHub Copilot. Semantic search, Git sync, project-based, Persistent memory MCP server for Claude Code, Cursor, and GitHub Copilot. Semantic search, Git sync, project-based organization, and team collaboration via Model Context Protocol.15342 npm2MIT
- AlicenseAqualityCmaintenanceLocal MCP server giving AI coding agents (Claude Code, Cursor, VS Code/JetBrains Copilot) a shared, persistent memory of your projects and every bug/issue faced during development. Stateless, plain-file storage (AGENTS.md + issues.jsonl) — no database.1691 npm1MIT
- AlicenseNot gradedqualityCmaintenancePersistent project memory and task management for AI coding agents through MCP. Lets Claude Code, Cursor, Codex and other MCP clients save decisions and bug fixes, search relevant context, and reuse it across sessions.1MIT
- AlicenseBqualityBmaintenanceEnables AI coding agents to maintain persistent project context, including rules, decisions, environment intelligence, and Git history, using a local-first MCP server with automatic project detection and token-efficient retrieval.13MIT
TDQS
Scored across 4 tools
The four tools have mostly distinct purposes: read summary, save memory, save reusable skill, and search. The only possible confusion is between remember and remember_skill, but the descriptions clearly separate decaying memories from permanent procedures.
All names are lowercase with underscores, but the conventions are mixed: context is a noun, recall and remember are bare verbs, and remember_skill is verb_noun. The set is readable but lacks a predictable naming pattern.
Four tools is a well-scoped surface for a memory context server: one for summary, one for search, and two for persistence. Each tool earns its place without bloat.
The surface covers creating memories/skills, reading a summary, and searching, but lacks update, delete/forget, and targeted retrieval by ID. Agents cannot manage or correct stored memories beyond adding new ones.