Enola
Generates compact architectural snapshots of codebases to provide structured context for AI coding agents.
Enola functions as a local server for the Model Context Protocol (MCP), enabling AI coding agents to receive a detailed, structured overview of a repository's architecture before analyzing individual files. It extracts modules, symbols, dependencies, routes, and architectural patterns across various programming languages, empowering LLMs with a "map" of the codebase. This proactive context significantly enhances the efficiency and accuracy of AI agents in tasks like understanding code, planning changes, and identifying architectural issues, especially across multi-repository environments.
主要功能
01Enables cross-repository architectural analysis and querying
02Supports multiple languages: Go, Kotlin, Python, TypeScript, Swift, Ruby, OpenAPI
03Integrates seamlessly with MCP-compatible AI coding agents
0433 GitHub stars
05Generates compact architectural snapshots for LLM consumption
06Identifies architectural insights like cyclic dependencies and layer violations
使用案例
01Facilitating AI-assisted planning for new features, such as API endpoint additions
02Detecting and understanding architectural issues like cyclic dependencies or layer violations
03Onboarding AI agents to new or complex codebases by providing an architectural overview