"Ram" matching MCP servers:

Enables local Windows file management with allowlisted folder access and integration with Outlook Classic or Microsoft 365 email for AI assistants like Claude Desktop.

Enables Claude Desktop to monitor and control your computer system with 90+ real-time tools covering CPU, RAM, GPU, disk, network, processes, and more, plus extensions for file management, code editing, and web research.

An MCP server that enables Claude Desktop to search and read local documents via full-text and fuzzy search, providing direct access to indexed files without chunking.

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.

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

Enables AI assistants to read, edit, and execute Jupyter notebook files (.ipynb) with live kernel output, without requiring JupyterLab.

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.

Provides local hybrid search over files by combining semantic vector and full-text BM25 retrieval, with MCP stdio/HTTP support, OAuth 2.1 authentication, and tools for reading and converting documents to Markdown.

Provides intelligent retrieval capabilities for local files by scanning directories, generating vector indexes, and enabling semantic search through RAG (Retrieval Augmented Generation) with incremental indexing support.

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.

A focused local-paper RAG MCP server that imports PDFs, indexes them into SQLite and ChromaDB, and retrieves section-aware paper chunks for use with Claude Code, Codex, or any MCP client.

A self-learning knowledge layer for local LLM chat that answers questions from Markdown files, writes new knowledge back every turn, and provides grounding verdicts.

Enables AI assistants to append completed work items to the checklist of the newest daily log file in a configured directory, keeping notes updated without exposing file paths.

Read and filter Excel, CSV, ODS, SQLite, Parquet and MTSV files — or a folder — as plain text

Enables RAG (Retrieval-Augmented Generation) with tools for vector search, document access, and OpenAI integration, plus MySQL storage and file system operations via MCP.