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Arbor

Arbor is a locally prioritized codebase impact analysis engine that accurately tracks function calls, imports, and inheritance relationships by building a semantic dependency graph, helping developers understand the actual impact scope of changes before refactoring.
Developer toolsVersion control#Code analysis#Dependency tracking#Refactoring assistance#Graphical interface.Rust
3 points
3.4K
Open Site

Overview

Content Details

Alternatives

What is Arbor?

Arbor is an intelligent code analysis tool. Unlike traditional tools that simply search for text, it deeply parses your codebase and builds a complete semantic dependency graph. This graph contains real execution paths such as function calls, class inheritance, and file imports, allowing you to accurately predict the impact scope of code changes.

How to use Arbor?

Arbor provides two usage methods: command-line tools and a graphical interface. After installation, simply run a few simple commands in the project root directory to start analyzing code dependencies. It can automatically recognize the project structure without complex configuration.

Applicable scenarios

Arbor is particularly suitable for the following scenarios: refactoring large codebases, collaborative team development, maintaining legacy systems, conducting code reviews, and any development tasks that require ensuring the safety of changes.

Main features

Accurate semantic analysis
Use tiktoken for accurate token counting, replacing traditional heuristic estimation to ensure the accuracy of the LLM context budget.
Intelligent symbol suggestion
It has a built-in fuzzy matching function. Even if there are spelling errors in the input, it can intelligently recommend the correct symbol name (e.g., autth → auth).
Git integrated workflow
It provides Git-aware commands such as arbor diff and arbor check to help you assess the risk of changes before branch merging.
Incremental index update
It supports the --changed-only parameter, which only re-indexes the changed files, significantly improving the analysis speed of large projects.
Visual graphical interface
It has a built-in GUI tool that displays code dependencies in an interactive graph, supporting search, exploration, and export functions.
Deep integration with MCP/AI
It provides a rich JSON output format, including confidence levels, role descriptions, and dependency explanations, which is perfectly compatible with AI tools such as Claude and Cursor.
Advantages
Analysis based on real execution paths is more accurate and reliable than text search.
Locally prioritized design ensures that code data does not leave your development environment.
It supports both command-line and graphical interfaces to meet different usage habits.
Deep integration with the Git workflow makes it suitable for modern development processes.
The incremental update mechanism enables large projects to quickly respond to changes.
Limitations
Currently, it mainly supports mainstream languages such as Python, with limited support for other languages.
It takes a certain amount of time to build the dependency graph for the first time (especially for large projects).
It requires a certain learning cost to understand the analysis results of the dependency graph.
Dynamic language features (such as runtime reflection) may not be fully captured.

How to use

Install Arbor
Install using a package manager or quickly deploy through a one-click installation script.
Initialize the project
Enter your project directory and run the initialization command to create an index.
Analyze code impact
Use the refactor command to analyze the impact of changes to a specific symbol.
Check Git changes
Before committing or merging, evaluate the risk of changes in the current branch.
Use the graphical interface
Start the GUI tool to explore code dependencies in a visual way.

Usage examples

Safely refactor a function
Before modifying a key function, understand which code will be affected to avoid accidentally breaking existing functions.
Assist in code review
When reviewing a Pull Request, quickly understand the impact scope of the changes and focus on high-risk areas.
Explore the codebase structure
When joining a new project, use the GUI tool to quickly understand the dependencies between modules.
Preventive quality check
Integrate Arbor into the CI/CD process to ensure that each commit does not introduce excessive change risks.

Frequently Asked Questions

Which programming languages does Arbor support?
Will Arbor collect my code data?
How to handle large projects? Will the first indexing be slow?
What is the difference between Arbor and traditional IDE code analysis tools?
How to integrate Arbor into my development workflow?

Related resources

GitHub repository
The source code and latest version of Arbor
Installation guide
Detailed installation instructions and version management
Quick start guide
Step-by-step guide on using the core functions of Arbor
Glama MCP directory
View the server information of Arbor in the MCP directory
Issue feedback
Report bugs or propose feature suggestions

Installation

Copy the following command to your Client for configuration
Note: Your key is sensitive information, do not share it with anyone.

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