"Semantic search, RAG, and memory systems" matching MCP servers:

MCP server that enables local hybrid semantic and keyword search over private PDF, DOCX, Markdown, and text documents without sending data to embedding APIs.

MCP server that exposes agent-memory-daemon to any MCP-compatible client — Kiro (CLI & IDE), Claude Desktop, Cursor, and others. The daemon does the thinking (consolidation + extraction); this server is a thin filesystem bridge so agents can read, append, and search memory through the Model Context Protocol.

Provides persistent memory for Claude with hierarchical categorization, cross-corpus recall, session journals, and customizable persona, enabling memory continuity across sessions.

A TypeScript MCP server that allows querying documents using LLMs with context from locally stored repositories and text files through a RAG (Retrieval-Augmented Generation) system.

A local MCP server that provides agents with tools to list, read, search, inspect history and diffs, and capture unstructured text in a user-owned Git repository of durable memory.

Provides project memory management for Claude Desktop, storing memories as Markdown files with intelligent keyword-based retrieval and automatic creation/update decisions by LLM.

A local hybrid-search MCP server that enables coding agents to query files and folders using natural language, returning relevant code chunks with exact source paths. Everything runs on-device with no API keys or network calls.

A local-first Graph-RAG system that combines ChromaDB with metadata-based graph relationships and Gemini 2.5 Flash for intelligent Q\&A over your Obsidian vault.

Provides a local markdown-based memory system for coding agents through MCP, enabling search, add, register, inventory, sync, and ingest operations across user and project memory. It gives any agent tool a durable, provider-agnostic shared memory stored in folders you own.

Provides fully local, privacy-preserving semantic search over file names and paths via MCP, using BGE embeddings for fuzzy matching and supporting incremental updates, watch mode, and a loopback-only HTTP server.

Enables reading, writing, and searching a local markdown-based memory store using MCP tools, with safety checks and index consistency.

A memory, docs, and repo context layer for engineering agents, providing typed persistent memory, RAG document retrieval, and repository-aware tools to recall decisions, runbooks, and operational knowledge across sessions.

Enables advanced semantic search and document management by integrating the GroundX API with Claude Desktop and GitHub Copilot. It supports local file uploads, website crawling, and Google Drive synchronization for RAG workflows.

An MCP-compatible system that handles large files (up to 200MB) with intelligent chunking and multi-format document support for advanced retrieval-augmented generation.

A local-first MCP server that enables semantic search over PDF and DOCX documents using structure-aware parsing and vector storage. It allows users to query their local knowledge base through Claude Code without cloud dependencies or GPU requirements.

A local-first, Markdown-native AI agent layered memory system that provides MCP tools for storing, recalling, exporting, and importing memories with types like working, persona, and fact.

Exposes local memory vaults as 6 MCP tools over stdio, enabling clients like Windsurf, Zed, and Claude Desktop to read and write memory.

An MCP server that gives AI models a persistent notebook backed by a folder of Markdown files, with tools to discover, read, write, edit, and delete notes.

MCP server for full-text search across PDF document collections with offline indexing, ranked results, snippets, and page rendering.

Enables blazingly fast file and content searching in large codebases using ripgrep, with intelligent filtering, fuzzy finding, and directory tree visualization while respecting .gitignore and avoiding common bloat directories.