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enola
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enola

Active·★ 277·Apache-2.0·Updated 2026-10-22

Enola is a local Model Context Protocol (MCP) server that generates compact architectural snapshots of code repositories, providing a structured overview of modules, symbols, and dependencies before AI agents read individual files. This upfront context helps AI coding agents like Claude Code, Cursor, or Copilot understand the codebase structure, making their exploration and code generation more effective.

enola sits in the Code Assistant category, so it is usually better judged by workflow fit, deployment style, and team needs than by isolated features alone. Based on the available metadata, it leans most clearly toward Generates compact architectural snapshots of repositories for AI agents.. A representative use case is Onboarding new developers: Quickly get a structural tour of a codebase for new team members.. The listed license is Apache-2.0. GitHub stars are currently 277. Relevant tags include AI Agent Tooling, Codebase Analysis.

This write-up is based on the project's README and public repository data. We have not hand-tested the tool.

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#AI Agent Tooling#Codebase Analysis#Architectural Snapshot#Model Context Protocol#Multi-language#Dependency Graph#LLM Context Generation#Dev Tooling
$ Install
$ go install ./cmd/enola
↗ Visit site★ GitHub
01

Features

01Generates compact architectural snapshots of repositories for AI agents.
02Supports multiple programming languages including Go, Kotlin, Python, TypeScript, Swift, Ruby, and OpenAPI.
03Integrates with MCP-compatible AI coding agents (e.g., Claude Code, Cursor) to provide upfront context.
04Enables cross-repository analysis by building a combined fact store and linking dependencies between services.
05Provides tools for querying facts, exploring code, traversing dependency graphs, and performing impact analysis.
02

Why choose it

+Generates compact architectural snapshots of repositories for AI agents.
+Supports multiple programming languages including Go, Kotlin, Python, TypeScript, Swift, Ruby, and OpenAPI.
+Onboarding new developers: Quickly get a structural tour of a codebase for new team members.
+Supports 9 platforms or runtime environments.
03

Trade-offs

!The final decision should still be made through side-by-side comparison with similar tools.
04

Compatibility

Go
Runtime
Verified via docs
Go
Extractor
Verified via docs
Kotlin
Extractor
Verified via docs
Python
Extractor
Verified via docs
TypeScript
Extractor
Verified via docs
Swift
Extractor
Verified via docs
05

Quick start

1
$ go install ./cmd/enola
06

Use cases

↳Onboarding new developers: Quickly get a structural tour of a codebase for new team members.
↳Refactoring planning: Understand transitive dependencies and impact of changes before code modifications.
↳Debugging complex systems: Trace call chains and understand how different modules or services interact.
↳Multi-repo development: Analyze and query dependencies across multiple microservices or monorepos.
↳AI agent enhancement: Provide AI coding agents with deep architectural context to improve code understanding and generation.
07

Alternatives

⚡Top VS:
VSenola★277→VSkin★68→VSCALM★17→VSsrclight

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On this page
01Features02Why choose it03Trade-offs04Compatibility05Quick start06Use cases
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07
Alternatives
enola-labs /
enola
↗

enola - MCP Architectural Snapshot Server and Knowledge Graph

277Apache-2.0
Last commit1d ago
StatusActive
CategoryCode Assistant
Links
Documentation↗Discussion↗Issues↗Releases↗
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