Hypermnesic
Related Servers
Alternatives to Hypermnesic
No user-submitted related servers found.
Related Servers
- AlicenseNot gradedqualityCmaintenanceEnables AI agents to persist and share durable memory — appending session logs with checkpoints and handoffs, claiming and completing tasks, and recording decision records — all stored as plain Markdown and JSONL files in a git repository. Everything written is full-text searchable, and the server speaks MCP so MCP-aware clients can plug in directly with zero vendor lock-in.MIT
- AlicenseNot gradedqualityCmaintenanceOpen, Git-native memory protocol for MCP agents: stores memories as Markdown files in a Git repo, enabling portability, auditability, and human-editable memory across different AI agents.61 npm15MIT
- AlicenseNot gradedqualityAmaintenanceLocal-first, file-based memory layer for AI agents — one shared Markdown vault across Claude, Codex, Gemini, Cursor and any MCP client. Provides read/write memory tools with an audit trail, per-agent trust levels, and Git sync; no cloud and no lock-in.2MIT
- AlicenseNot gradedqualityBmaintenanceMCP server providing persistent, local-first memory for AI agents via Markdown files in a git repo, with search, branching, and auditability.5 npm2MIT
- AlicenseAqualityAmaintenanceA lightweight, Git-backed permanent memory for AI agents.374 PyPI42MIT
- AlicenseAqualityAmaintenanceLocal-first memory layer for AI coding agents — Markdown as source of truth, MCP server + CLI, human-reviewed capture, team knowledge via git PRs6116,615 npm4Apache 2.0
TDQS
Scored across 7 tools
There are two tools that perform identical search functionality (search and hypermnesic_search), creating ambiguity about which to use. Other tools are distinct but the overlap is confusing.
Most tools follow a verb or verb_noun pattern with consistent lowercase underscore naming. The hypermnesic_search is a namespaced alias that deviates from the pattern, but it is still clear.
With 7 tools covering read-only operations like search, read, resolve, list, and context building, the count is well-scoped for a read-focused knowledge vault assistant.
The tool set lacks any write operations such as creating or updating notes. This is a significant gap for a personal knowledge management system, as agents cannot record new information or modify existing notes.