hypernmnesia-mcp-viz
Related Servers
Alternatives to hypernmnesia-mcp-viz
No user-submitted related servers found.
Related Servers
- AlicenseAqualityAmaintenanceOpen-source operational brain that fuses an AI system's agents, memory, knowledge and automations into one rooted, privacy-walled graph, served over MCP with stats, search, node dossiers, neighbors and pathfinding. The same snapshot also renders up to a million nodes in a 3D browser view.81MIT
- AlicenseBqualityCmaintenancePersistent 4-tier AI memory (episodic, semantic, project, procedural) with temporal scoring, contradiction detection, entity tracking, and real-time desktop visualization orb.722MIT
- AlicenseAqualityAmaintenancePersistent memory with knowledge graph visualization, semantic/hybrid search, importance scoring, and cloud sync (S3/R2) for cross-session context management.43725MIT
- FlicenseBqualityDmaintenanceTransforms markdown documents into immersive 3D visualizations using semantic analysis and spatial layout, enabling navigable knowledge structures.72-
- FlicenseBqualityBmaintenanceTurns local code repositories into a queryable dependency graph built from AST parsing and git co-edit history, then exposes it alongside an Obsidian vault as persistent memory. Enables context retrieval, impact analysis of proposed changes, and curation of durable prose knowledge through full-text search and Personalized PageRank classification—all fully offline without API keys or embeddings.30-
- FlicenseNot gradedqualityDmaintenanceProvides screen capture, OCR text extraction, and visual language model scene understanding capabilities with continuous monitoring and automatic memory storage integration.-
TDQS
Scored across 2 tools
The two tools are unmistakably distinct: one launches the bundled browser visualization with side effects, the other returns JSON graph data for a custom client. The descriptions even provide explicit contrasts, so an agent should not confuse them.
Both names follow the same lowercase snake_case verb_noun pattern: open_visualization and get_methodology_graph. The verb choice maps cleanly to each tool's behavior (open vs. get).
Two tools is at the thin end of the scale, though each is broad and covers a distinct access path (human-facing UI vs. JSON data). The descriptions reference list_domains and get_causal_chain, which are not exposed here, making the set feel like a slice of a larger system.
The core visualization workflows are covered: launch the full browser UI and fetch the methodology graph as JSON for a custom client. Minor gaps include no JSON endpoints for the other bundled views and no explicit stop/status API, though auto-shutdown mitigates the latter.