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

Enables natural-language Q&A over multi-source documents (PDF/Markdown/web) with a self-reflective retrieval-augmented agent that cites sources, retries on poor retrieval or grounding, and supports multi-turn memory.

MCP server for the Solid protocol enabling AI models to read, write, search, and manage resources in Solid pods.

Provides 12 tools to query South Korean building register data, including title sheets, floor details, and official house prices via the data.go.kr API. It enables users to perform smart building lookups and region code searches using natural language.

Gives agents a stable interface for durable memory, combining exact, lexical, semantic, and graph search results.

Provides read-only hybrid RAG search and discovery over a local-first AI knowledge corpus, enabling semantic and keyword search, browse, digest, and status tools.

A persistent, searchable memory layer for AI assistants, exposed as an MCP server. It supports CRUD, namespaces, hybrid ranked search, relationships, chat-context assembly, import/export, and optional LLM-powered auto-extraction.

Provides comprehensive building and office address information queries for enterprises in China, including fuzzy enterprise search, office address details and statistics, and building information queries to support geographical distribution and occupancy analysis.

A knowledge base MCP server that aggregates team knowledge from multiple sources into Postgres. It provides hybrid search (full-text + vector + RRF) via MCP tools, and enables direct recording of decisions, learnings, and pitfalls.

Exposes a knowledge base to LLM clients through tools, resources, and prompts.

A cross-project knowledge base MCP server supporting three-layer search (text matching, TF-IDF, and semantic vectors) with a Web UI for management.

Pay-per-call web search for AI agents, settled in USDC on Base via the x402 protocol. No API key or subscription required; users fund a wallet and get a web_search tool.

A persistent memory system that captures, classifies, synthesizes, and retrieves knowledge for AI agents, turning raw information into refined, retrievable knowledge that compounds intelligence over time.

A local knowledge base server that connects to AI assistants, turning markdown files into a semantically searchable memory layer via OpenAI embeddings and SQLite.

Enables local full-text and semantic search over saved content, providing search and retrieval capabilities via MCP for AI assistants.

Provides semantic search over a self-building personal technical knowledge base that automatically collects and distills content from GitHub Trending, AI news, and arXiv.

A local MCP server that gives AI assistants persistent long-term memory using a biological neural architecture with cortex, synapses, and hippocampus.

An MCP server for searching and downloading books from Library Genesis, supporting EPUB, MOBI, PDF, and more through natural language queries.

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.

A zero-dependency, file-based persistent memory system for AI agents with tiered memory, Ebbinghaus decay, and keyword retrieval.

Provides persistent memory for AI assistants via MCP, enabling them to store and recall facts, preferences, and tasks across conversations using either local file storage or a cloud backend with semantic search.