"Understanding Cursor or Cline Context in Long-term Memory Systems" matching MCP servers:

A persistent, human-like memory system for AI companions in LM Studio, using SQLite and ChromaDB for hybrid storage, enabling seamless recall across sessions and models.

Personal memory service using semantic vector retrieval and knowledge graphs to persist long-term context, supporting memory evolution and conflict labeling for the same entity.

Enables AI agents to maintain long-term, cross-session memory by extracting facts, reconciling state conflicts, and retrieving relevant memories via vector search.

Local-first MCP server for long-term memory of dev sessions. It indexes session metadata with embeddings in Postgres/pgvector, enables semantic search over past sessions, and resolves only relevant session files for context.

MCP Memory is a MCP Server that gives clients like Cursor and Claude the ability to remember user preferences and behaviors across conversations using vector search.

Claude Context is an MCP plugin that adds semantic code search to Claude Code and other AI coding agents, giving them deep context from your entire codebase.

Enables Claude to index and retrieve context from codebases using self-hosted Milvus for semantic search, with hardened reliability and security for production use.

Context Portal (ConPort): A memory bank MCP server building a project-specific knowledge graph to supercharge AI assistants. Enables powerful Retrieval Augmented Generation (RAG) for context-aware development in your IDE.

Enables AI coding assistants to automatically scan, store, and query API endpoints from codebases, providing instant lookup and semantic search to reduce context switching and token consumption.

Implements long-term memory capabilities for AI assistants using PostgreSQL with pgvector for efficient vector similarity search, enabling semantic retrieval of stored information.

Enables personal memory management through tools to find people, get profiles, remember notes, and perform semantic search, integrated with Claude via SSE.

Provides AI coding agents with persistent, long-term memory through local semantic search and SQLite storage. It enables agents to save and retrieve architectural decisions or project context across different conversation sessions without requiring cloud services.

A general-purpose MCP memory server that gives AI clients long-term memory with semantic search, memory classification, priority management, and progressive injection, supporting local JSON or cloud PostgreSQL storage.

Provides AI-assisted long-term memory storage and retrieval with exact-phrase and semantic hybrid search, enabling save, read, delete, and admin recovery via MCP tools.

An MCP server that enables semantic search over local files or GitHub repositories by indexing content into a serverless vector database, allowing AI assistants to understand meaning rather than just keywords.

Enables AI assistants to store and retrieve long-term memories with semantic search, supporting various memory types and tags via PostgreSQL and pgvector.

Enables AI agents to use a neuro-symbolic memory fabric with bi-temporal knowledge graph and holographic VSA, providing tools for adding, searching, temporal queries, auditing, and proving memories with cryptographic provenance and zero-LLM ingest.

A fully-local AI memory system that saves notes, code, and terminal output to a vector database via Ollama and LanceDB, enabling context retrieval from terminal, API calls, or inside Claude Code.

Enables searching through vectorized Cursor IDE chat history via a FastAPI service powered by LanceDB and Ollama.

Enables AI assistants to store and retrieve long-term memories using PostgreSQL with vector similarity search. Supports semantic memory operations, tagging, and real-time updates for persistent learning across conversations.