n1x-cortex: AI-queryable knowledge graph from code

Turns any codebase or markdown vault into an AI-queryable knowledge graph, with web viewer and MCP server.

n1x-cortex: AI-Queryable Knowledge Graph from Code

n1x-cortex is a powerful tool designed to transform your codebase or markdown vault into an AI-queryable knowledge graph. This enables developers to interact with their projects and documentation in entirely new ways, leveraging AI to extract insights and understand complex relationships within their data. By converting structured and unstructured text into a queryable graph, n1x-cortex unlocks deeper understanding and facilitates more efficient development workflows.

What it Does

n1x-cortex ingests your code repositories or markdown files and constructs a knowledge graph. This graph represents the entities within your data (e.g., functions, classes, variables, concepts) and the relationships between them. Once the graph is built, you can query it using natural language or structured queries, allowing you to ask complex questions about your project's architecture, dependencies, or documentation. It provides a web viewer for easy exploration and includes an MCP server for programmatic access.

Key Features

Codebase to Knowledge Graph: Converts any codebase (e.g., Python, JavaScript, Go) into a structured knowledge graph.
Markdown Vault Integration: Processes markdown files to build a knowledge graph of your documentation and notes.
AI-Queryable: Enables natural language and structured querying of the generated knowledge graph.
Web Viewer: Includes an intuitive web interface for visualizing and exploring the knowledge graph.
MCP Server: Provides an MCP server for seamless integration with other AI agents and tools.
Source Code Available: Hosted on GitHub, allowing for transparency and community contributions.

Who it's For

n1x-cortex is an essential tool for AI builders , software developers , and technical writers . It's particularly beneficial for teams working on large or complex codebases who need to understand interdependencies, identify potential issues, or quickly find specific information within their documentation. Developers building AI agents that require deep contextual understanding of code or project documentation will find the MCP server integration invaluable.