Which AI coding assistants and IDEs can integrate with Linggen?

Linggen exposes an MCP server (Memory Component Protocol) which allows integration with compatible IDEs and AI agents like Cursor, Zed, and Windsurf, enabling them to leverage Linggen's enhanced memory capabilities.

How does Linggen ensure data privacy and security?

Linggen runs entirely on your machine. All your data, including embeddings, indexes, and search operations, are processed locally, ensuring that nothing leaves your computer by default.

What kind of content can Linggen index?

Linggen can index a wide range of local content, including local folders, entire codebases, documentation sets, and personal notes, allowing for semantic search and AI chat over all your indexed data.

Linggen is a local-first RAG (Retrieval-Augmented Generation) + MCP (Memory Component Protocol) memory layer specifically designed for AI coding assistants. It helps enhance project navigation and knowledge recall across your local development environment.

Is Linggen free to use?

Yes, Linggen is free for both individuals and teams, making advanced local-first RAG and AI memory accessible for all developers.

Linggen

Name: Linggen
Author: linggen

bylinggen

開発者ツール

生産性とワークフロー

データサイエンスとML

Provides a local-first RAG + MCP memory layer designed for AI coding assistants, enabling enhanced project navigation and knowledge recall.

概要

Linggen operates as a local-first RAG (Retrieval-Augmented Generation) and MCP (Memory and Context Protocol) memory layer specifically for AI coding assistants. Running entirely on your machine and free for both individuals and teams, it's engineered to help users work seamlessly across numerous projects with a unified memory layer and efficiently navigate large codebases and documentation sets. The tool facilitates connecting multiple IDEs and agents like Cursor, Zed, and Windsurf via MCP, ensuring all embeddings, indexes, and search operations remain local by default. It allows users to index their local folders, codebases, documents, and notes, then perform semantic search and AI chat over all indexed content, or expose an MCP server for compatible tools.

主な機能

Runs entirely on your machine with all data processed locally
0 GitHub stars
Index local folders, codebases, documentation, and notes
Semantic search and AI chat over all indexed content
Local-first RAG + MCP memory layer for AI coding assistants
Exposes an MCP server for integration with compatible IDEs/agents

ユースケース

Managing a shared memory layer for developers working across multiple projects
Efficiently navigating and querying large codebases and documentation sets
Connecting various IDEs and AI agents to a unified memory and context system

概要

主な機能

Runs entirely on your machine with all data processed locally
0 GitHub stars
Index local folders, codebases, documentation, and notes
Semantic search and AI chat over all indexed content
Local-first RAG + MCP memory layer for AI coding assistants
Exposes an MCP server for integration with compatible IDEs/agents

ユースケース

Managing a shared memory layer for developers working across multiple projects
Efficiently navigating and querying large codebases and documentation sets
Connecting various IDEs and AI agents to a unified memory and context system