Rememex by Illegal Instruction Co is an MCP server built with Rust, designed to provide AI agents with advanced memory capabilities. Operating on the mcp platform, this free program enables AI agents to perform semantic searches across local files and enhance Retrieval-Augmented Generation (RAG) workflows. It supports over 120 file types, including OCR on images and reverse geocoding of GPS data, helping agents efficiently find relevant information and reduce token usage for faster task completion.

What does Rememex connect to?

Rememex connects directly to a local file system, functioning as an MCP server for AI agents. Its core purpose is to offer semantic search and long-term memory features. This server is categorized as an MCP server, providing a critical interface for AI agents to interact with stored information. It processes various file types and data, enhancing agent capabilities by making local data accessible and searchable based on meaning rather than just keywords.

Core features and tools

The MCP surface of Rememex is designed as "tools-only," advertising available tools during the initialize call. It supports two explicit transport modes: stdio for native integration with local agents and HTTP/SSE for concurrent AI agents to access the memory pool over a network. Claude Desktop is a confirmed compatible AI client. Authentication uses token-based access control for protected namespaces.

Who is it for?

Rememex is primarily for AI agents, offering them advanced capabilities for interacting with local data. It provides long-term memory and semantic search, allowing agents to process and retrieve information more effectively. This program enhances AI agent performance by reducing token usage and speeding up task completion through efficient information retrieval. This is not the right fit if your agents require a non-Windows operating environment.

How to get started

The server authenticates using token-based access control for protected namespaces. It supports stdio for native integration and HTTP/SSE for network access.

Use cases

• Performing semantic search across local files, enabling agents to find information by meaning across over 120 file types, including OCR on images and reverse geocoding of GPS data.
• Providing Retrieval-Augmented Generation (RAG) and long-term memory capabilities to AI agents.
• Enabling AI agents to use significantly fewer tokens and complete tasks faster by efficiently finding relevant information.

Rememex by Illegal Instruction Co provides AI agents with essential semantic search and long-term memory functions through an MCP server. Its ability to process diverse file types and support both local and network agent interactions makes it a valuable resource for enhancing AI agent efficiency. The Windows 10+ platform ensures agents can quickly access and process information for improved task performance. Try configuring an AI agent to perform a semantic search across your local files.