OpenExp
Related Servers
Alternatives to OpenExp
No user-submitted related servers found.
Related Servers
- AlicenseAqualityCmaintenancePersistent memory for Claude Code. Automatically indexes every conversation and provides production-grade hybrid search (BM25 + vectors + reranker) via MCP tools. 100% local, zero config, zero API keys, zero invoice.1617 npm7MIT
- FlicenseNot gradedqualityAmaintenanceEnables Claude Code to persistently store, search, update, and delete memories backed by self-hosted Qdrant, Neo4j, and Ollama, using Anthropic or a fully local LLM. Exposes 11 MCP tools plus session hooks that automatically inject relevant context on startup and save session summaries on exit.-
- FlicenseNot gradedqualityAmaintenanceGives Claude Code persistent cross-session memory backed by self-hosted Qdrant vector storage, optional Neo4j knowledge graphs, and Ollama embeddings, using either an Anthropic subscription token or a fully local LLM for fact extraction. Exposes 11 tools for adding, searching, updating, and deleting memories plus graph entity exploration, along with session hooks that inject context on startup and save summaries on exit.-
- AlicenseBqualityAmaintenancePersistent, local memory for AI coding agents that learns how you work, not just what you said. Supports Claude Code, Codex CLI, Cursor, and any MCP client.79292 PyPI73MIT
- AlicenseNot gradedqualityAmaintenanceGives Claude Code persistent cross-session memory with semantic search, automatic detection and classification of user corrections into behavioral patterns, and self-evolving frameworks that refine judgment over time. Everything runs locally through hooks and MCP tools, with no cloud, API keys, or telemetry.6 npmMIT
- AlicenseNot gradedqualityAmaintenanceGives Claude Code persistent cross-session memory with semantic search over facts, decisions, and lessons, plus automatic tracking of user corrections and behavioral patterns. Enables a Claude that evolves reusable frameworks over time — promoting what works and retiring what doesn't — all locally through MCP tools and hooks.6 npmMIT
TDQS
Scored across 5 tools
Each tool maps to a distinct concern: memory system health, memory search, memory creation, prediction logging, and outcome resolution. The prediction/outcome pair is clearly separated by their lifecycle roles.
search_memory, add_memory, log_prediction, and log_outcome all follow a verb_noun pattern. memory_stats deviates by starting with a noun, making get_memory_stats the more consistent equivalent.
Five tools is appropriately scoped for a memory plus prediction-logging server. Each tool covers a necessary function without redundancy.
The memory surface covers add, search, and health stats, while predictions cover both logging and outcome resolution. Missing prediction retrieval/listing and memory mutation/deletion are minor gaps rather than critical dead ends.