"How to add, remove, and edit files on a local laptop" matching MCP servers:

Local-only MCP server for saving and restoring conversation context across AI agent sessions using JSON files on disk.

Privacy-first local document search using semantic search. Runs entirely on your machine with no cloud services, supporting PDF, DOCX, TXT, and Markdown files.

A-MEM is a self-evolving memory system for coding agents that automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships, enabling semantic and structural search.

一个基于FastMCP协议的文件向量化服务，支持自动目录监控、多格式文件处理和高效向量搜索，帮助构建个人或团队知识库。

Enables AI consciousness continuity and self-knowledge preservation across sessions using the Cognitive Hoffman Compression Framework (CHOFF) notation. Provides tools to save checkpoints, retrieve relevant memories with intelligent search, and access semantic anchors for decisions, breakthroughs, and questions.

A local-first MCP server providing persistent, project-scoped and global memory for AI agents using ChromaDB and Ollama embeddings, fully offline.

Provides read-only access to your local Zotero library via the Zotero Local API, enabling search, retrieval, and bibliography generation without API keys.

Enables storing and retrieving text passages based on semantic meaning using local embeddings (Ollama) and vector storage (ChromaDB), allowing conversational memorization and retrieval of information.

A local-first MCP server for PageIndex — the vectorless, reasoning-based RAG framework. It lets local AI agents index and query local PDF and Markdown documents through a self-hosted PageIndex installation, without requiring any PageIndex cloud API key.

MCP server that exposes local Granola meeting notes, summaries, and transcripts to AI assistants via SQLite-backed search and retrieval.

A local-first MCP memory server that gives AI coding agents persistent memory with hybrid semantic and keyword retrieval, working fully offline.

Provides fully local long-term memory for AI agents by enabling semantic search over notes and session logs using Ollama embeddings, with no external APIs or databases.

Local-first memory daemon for AI coding agents that captures session transcripts, distills typed memories (decisions, facts, lessons, commands, todos), and serves them via hybrid search through MCP tools.

A fully local, self-hosted memory server for MCP clients (Claude Code, Cursor, etc.) that provides persistent memory storage with semantic search, using local embeddings and a local Qdrant vector store.

A headless local knowledge library and RAG substrate that enables LLM clients to search, retrieve chunks, and list documentation packs through read-only MCP tools.

Provides persistent long-term memory and local RAG document search for Claude Desktop, fully offline. Enables memory save/search and document retrieval via MCP.

Description: Persistent local memory for Claude, Cursor and Codex. 13 MCP tools, SQLite + FTS5 + Knowledge Graph. No cloud, no API keys. One command: npx @studiomeyer/local-memory-mcp.

A Model Context Protocol server implementing Graph RAG with local, embedded Knowledge Graph using FAISS for vector search and NetworkX for graph traversal, enabling hybrid retrieval through anchor discovery and relationship expansion.

A local MCP server for RGPD-compliant document Q&A, enabling Claude Code to ingest, query, search, delete, and audit personal documents entirely on-device.

A lightweight, powerful local memory server for AI agents supporting text, entities, and relations. Enables persistent codebase understanding and user preference management.