"Building a solid memory base for AI development" matching MCP servers:

Enables MCP clients to retrieve relevant memories and save confirmed durable facts through authenticated access backed by PostgreSQL provenance and Qdrant semantic search.

Provides a production-ready Model Context Protocol server with dual STDIO and Streamable HTTP transports, enabling file operations, memory, database queries, RAG, web search, GitHub integration, background tasks, and prompt-based workflows.

A Model Context Protocol server that provides LLMs with read and write access to Feishu Base (飞书多维表格) databases, enabling them to inspect schemas and manipulate records through natural language.

This MCP server provides secure access to databases for AI agents, enforcing authentication, authorization, human approval, logging, and notifications to prevent dangerous actions.

Read-only MySQL MCP server that lets AI agents list tables, describe schemas, and run SELECT/SHOW/EXPLAIN queries with a row cap, bound to a single database for safety.

Persistent knowledge graph MCP server with SQLite backend, offering graph traversal, fuzzy search, and temporal queries for entities and relations. It serves as a drop-in replacement for the npm mcp-server-memory with enhanced capabilities.

A drop-in replacement for Anthropic's memory server that utilizes SQLite to ensure data integrity and concurrent access. It enhances the original functionality with semantic search capabilities using vector embeddings and ONNX models.

Enables AI assistants to store, score, recall, pin, sleep, wake, update, delete, and export memories with importance weighting, type-based decay, emotional valence/arousal, and dormant-memory reactivation through 14 MCP tools.

Enables AI chats to keep persistent, private memory between sessions using a local SQLite database with full-text search, duplicate handling, versioning, and soft deletion. It lets assistants store, recall, update, and review memories while rejecting likely secrets.

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

Enables AI assistants to have persistent, self-hosted memory across sessions and devices, storing context in a SQLite database you control.

An MCP server that stores project memory in Supabase, allowing AI tools to persist context, notes, and decisions across sessions. Enables Claude Code, Codex, and similar assistants to maintain long-term project continuity through persistent memory storage.

Provides conversational memory with short/long-term layering, consolidation, and time-decay/capacity/soft-archive forgetting, alongside rule-based slang and internet-slang discovery with optional LLM explanations. Exposes append, query, touch, forget, restore, consolidate, context-render, and slang operations over stdio MCP and a token-guarded loopback HTTP API.

Enables AI agents and LLMs to persist facts, preferences, and observations in a local SQLite store and to build and traverse subject-predicate-object knowledge graphs across sessions. It provides fuzzy keyword search and graph queries so assistants retain context and recall prior project history without repeating prompts.

Enables AI agents to keep durable long-term memory on the user's own machine, writing sessions and messages into a local SQLite database and retrieving them via keyword, exact, or optional semantic search with surrounding context. Runs entirely offline over stdio, so no cloud service or API key is required to give an agent recall across sessions.

Local-first, auditable memory for AI agents. Provides durable context for MCP hosts with SQLite storage, CLI, and MCP tools for memory management.

Enables semantic search and document management with support for text, PDF, and image uploads using your own Supabase database and OpenAI API keys. Supports multi-tenant deployment on Cloudflare Workers or local hosting.

Enables LLMs to interact with Feishu Base (Lark) databases by providing comprehensive tools for managing records, tables, and schemas. It supports full CRUD operations on database entries and structural modifications to table fields through the Model Context Protocol.

Give your AI agent the entire China A-share market: 55 datasets of prices, financials, capital flows, corporate events and futures/options, stored locally and queryable with read-only SQL. Built point-in-time with delisted stocks kept, so backtests don't lie — no account, no API key.

Enables coding agents to query and modify a SQLite database through twelve SQL-based tools, with safety enforced server-side via statement policies, protected tables, result caps, and snapshots. It also provides an append-only, hash-chained memory log with checkpoints so agents can record events and resume context across sessions.

Enables Claude Code and Gemini CLI to save, search, retrieve, and browse recent voice-derived notes and tags stored in SQLite over stdio, while deliberately excluding deletion and arbitrary file reads.

Enables project-scoped agent memory backed by a per-project SQLite index and raw data store, plus a global registry for discovering local memory workspaces. Agents can search summaries, retrieve original records on demand, save new memories, and link related records without sharing memory across projects.

An MCP server for managing agent memory using provenance tracking, decay-weighted retrieval, and feedback loops to optimize information recall. It allows agents to store insights in a local SQLite database and rank them based on confidence, age, and usefulness.

A simple memory system that allows LLMs to store and retrieve information via the Model Context Protocol.

A knowledge graph memory server using SQLite to provide persistent, isolated contexts for organizing information into searchable categories like work and personal projects. It features unique ID-based operations and a token-efficient serialization format designed to optimize interactions with LLMs.

Free local memory for Claude and Cursor: remember, recall and forget tools backed by a single SQLite file. Zero dependencies, MIT licensed. By Jipbap Kitchen.

Stores markdown knowledge notes in SQLite or Postgres and exposes them to AI agents over MCP, letting agents read individual sections, search, and write updates transactionally. Each write is validated, and anything that introduces broken links, missing summaries, or duplicate text is rolled back with a reason.

A Model Context Protocol server that allows users to store, retrieve, update, and delete memories using SQLite storage.

Enables coding agents to save facts, decisions and conventions into a single SQLite file and search them again in later sessions. Recall is ranked by BM25 relevance boosted by recency and scoped per project, with zero native dependencies.

A custom Memory MCP Server that acts as a cache for Infrastructure-as-Code information, allowing users to store, summarize, and manage notes with a custom URI scheme and simple resource handling.

Enables storing and querying memories in a Neo4j knowledge graph with automatic entity extraction. Supports adding episodes, searching entities and relationships, and managing graph data through natural language.

Enables assistants to append immutable, dated assertions and query what was known at a historical cutoff, using namespace-scoped hybrid FTS5/BM25 plus cosine retrieval that excludes future revisions. Exposes search, history auditing, status, and optional write/forget tools over a local stdio MCP server.

An MCP server for neuroanatomically-inspired memory consolidation using Neo4j and semantic search, enabling episodic memory encoding, semantic retrieval, and graph operations.

An MCP server that gives AI agents a private, durable memory of people, providing a personal people graph in PostgreSQL with tools to search, remember, and connect people, plus imports from LinkedIn, Google Contacts, and WhatsApp, and a browser UI.

A lightweight, fully local MCP server that provides AI coding tools with a shared SQLite memory store and built-in conflict arbitration, enabling structured memory sharing across tools like ZCode, Codex, Cursor, and Claude Code without external dependencies.

Gives MCP clients a local, single-tenant SQLite-backed store for saving, searching, bootstrapping and recalling memory records, plus saving and loading session handoffs, using text search by default with optional embeddings. It runs over stdio or an authenticated loopback HTTP gateway with explicit-confirmation pruning, scoped policies, and admin-driven backup, restore-copy and restart-drill verification.

Enables Codex, Claude Code, and other MCP-capable clients on the same computer to share local SQLite long-term memory with Chinese keyword search, project scoping, revision history, and Markdown export. It does not automatically capture conversations or synchronize across devices.

Manages knowledge graph data synchronized with GitHub repositories, enabling remote storage and collaboration of memory entities, relationships, and observations.

Provides persistent memory and knowledge graph capabilities for AI assistants using local SQLite storage. Enables creating, searching, and managing entities, relationships, and observations with vector search support across conversations.

Provides AI assistants with persistent, graph-based memory using Neo4j, enabling semantic search and complex relationship tracking. It features specialized Cloudflare Access support for secure remote connections and isolated multi-database management for different projects.