apecloud/ApeRAG C MCP Server Stale
Production-ready RAG platform combining Graph RAG, vector search, and full-text search. Best choice for building your own Knowledge Graph and for Context Engineering
Browse all Model Context Protocol servers with quality scores, stars, languages and maintenance activity.
Production-ready RAG platform combining Graph RAG, vector search, and full-text search. Best choice for building your own Knowledge Graph and for Context Engineering
Self-hosted mem0 MCP server for Claude Code with Qdrant vector search, Neo4j knowledge graph, and Ollama embeddings. Zero-config OAT auth, split-model graph routing, session hooks for automatic cross-session memory, and 11 tools. Supports both Anthropic and fully local Ollama setups.
Local FAISS vector database for RAG with document ingestion (PDF/TXT/MD/DOCX), semantic search, re-ranking, and CLI tools for indexing and querying
AI-powered paper annotation MCP server. Reads papers, highlights key findings with semantic color coding, explains formulas, and writes structured reading notes — all saved back to Zotero. Features two-phase workflow for large PDFs (63–80% context savings) and batch annotations.
Persistent 4-tier AI memory (episodic, semantic, project, procedural) with temporal scoring, contradiction detection, entity tracking, and real-time desktop visualization orb.
Persistent identity architecture for AI agents. 16 MCP servers covering drives, emotional relationships, semantic memory with decay, working threads, learned patterns, journal, genesis (identity discovery), creative collision engine, forecasting, and voice. Zero dependencies beyond Python 3.8. Built across 938 conversations.
Persistent, searchable context storage across Claude Code sessions using SQLite FTS5. Save sessions with AI-generated summaries, two-tier full-text search, checkpoint recovery, and a web dashboard.
Local workspace memory for Claude Desktop. Indexes your documents (Markdown, CSV, session logs) into a vector store with hybrid search, cross-session memory, auto-learn, and knowledge graph visualization. Zero external dependencies — fastembed + LanceDB, no Ollama or Docker required. 15 MCP tools.
Enable AI assistants to conduct structured, persona-driven sessions including interview preparation, personal reflection, and coaching conversations. Built-in timer management and performance evaluation tools.
Governed memory for coding agents with trust lifecycle (hypothesis → active → validated → deprecated), conflict detection, staleness tracking, and health scoring. SQLite + FTS5, zero infrastructure. `pip install quilmem[mcp]`
RAG for PDFs, YouTube, GitHub repos, Discord exports; index documents and query with citations.
Three-layer memory system for agents (identity/active/archive) with semantic search, graph relationships, conflict detection, and LearningMachine. Built by an agent, for agents. No API keys required.
Self-organizing neural graph memory with Hebbian learning for AI systems. Connections strengthen through co-activation and weaken through temporal decay. 118+ learning nodes, dual-write architecture, and sub-millisecond reads.
Your AI agents' home directory — privacy-first MCP server for portable AI identity. Configure once, use everywhere. It supports profile management, skills, resume import, and team sync.