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Aica

STDIO

AI-powered code analyzer with review, agent, and MCP server capabilities

aica - AI Code Analyzer

Motivation

There are already excellent code review tools such as pr-agent and cursor. However, pr-agent relies on code hosting services like GitHub, which limits its usability, and cursor is not open source, meaning it cannot be fully customized or integrated with other tools.

So, I decided to create a new tool with the following characteristics:

  • Customizable
  • Open Source
  • Platform Independent

Features

  • AI Coding Agent
  • AI Code Review
  • MCP(Model Context Protocol) supported. stdio and SSE transports are supported.
  • Automatic knowledge retrieving for code review
  • Symbol based code search for retrieving knowledge
  • Vector based document search for retrieving knowledge
  • Generate summary of changes
  • Generate commit message
  • Create pull request with AI-generated title and body
  • Prompt customization
  • Slack notification
  • Single binary executable by bun build --compile
  • GitHub Actions integration. (See wiki page to setup actions.)

Install

Build and install a binary:

# Install bun before build aica. # # Official Install Document: # https://bun.sh/docs/installation#installing git clone https://github.com/dotneet/aica.git cd aica bun install bun run build cp ./dist/aica path-to-your-bin-directory

Setup GitHub Token:

# if GITHUB_TOKEN is not set, aica try to get token from `gh auth token`. export GITHUB_TOKEN=your_github_token

Setup LLM:

# You can set the following items in your environment variables or aica.toml file. # Configure at least one of the following providers: # Anthropic (If you use agent, strongly recommend to use claude sonnet model) export AICA_LLM_PROVIDER=anthropic export ANTHROPIC_API_KEY=your_api_key export ANTHROPIC_MODEL=claude-3-5-sonnet-20241022 # OpenAI export AICA_LLM_PROVIDER=openai export OPENAI_API_KEY=your_api_key export OPENAI_MODEL=o3-mini # Gemini export AICA_LLM_PROVIDER=google export GOOGLE_API_KEY=your_api_key export GOOGLE_MODEL=gemini-2.0-flash

Configuration

You can customize the configuration by creating a aica.toml file.

See aica.example.toml.

aica.toml must be placed in one of the following directories.

  • root directory of the repository
  • ${HOME}/.config/aica/aica.toml
  • ${GITHUB_WORKSPACE}/aica.toml

Language

You can specify the language for AI output. The language can be specified either through AICA_LANGUAGE or in the language section of aica.toml. By default, the language is automatically detected from the LANG environment variable.

export AICA_LANGUAGE=Japanese

Priority:

  1. AICA_LANGUAGE
  2. language.language in aica.toml
  3. Automatic detection from LANG

Usage

Review

# review the diff from HEAD aica review [options] [pattern] # review specific files aica review src/main.ts # review the files matching the specific glob pattern aica review "src/**/*.ts"

Options:

  • --dir: Target directory path
  • --slack: Send notification to Slack

Agent

# execute AI agent with a prompt aica agent "your prompt here" # execute AI agent with a instruction file aica agent -f instruction.txt # conversation mode. You can interact with AI agent by typing your prompt. aica agent

This command executes a task using an AI agent. The agent automatically determines and executes the necessary actions based on the given prompt.

Recommend to use anthropic claude 3.5 sonnet for agent.

NOTE: This command has potential to break your file system. Please be careful.

Aica Agent as an MCP Server

# start a MCP server aica mcp server # start a MCP server with a config file aica mcp server --config aica.toml

Reindex

# reindex the code and document databases aica reindex

Summary

# generate a summary of the diff from HEAD aica summary [options]

Options:

  • --dir: Target directory path

Commit Changes

This command commits changes with an AI-generated commit message.

# commit all changes(including untracked and unstaged changes) with an AI-generated commit message aica commit [options] # commits all changes (including untracked and unstaged changes) with an AI-generated commit message aica commit --staged # commits only staged changes with an AI-generated commit message aica commit --push # commits all changes and pushes to remote repository

Options:

  • --staged: commit only staged changes.
  • --dryRun: Show result without execution
  • --push: Push to remote repository after committing

Create Pull Request

This command creates a pull request on GitHub.

# Creates a pull request. If there are changes, they will be committed automatically. aica create-pr [options] # Creates a pull request with only staged changes aica create-pr --staged

Options:

  • --withSummary: Generate summary of diff from HEAD (default: true)
  • --body: Pull request body
  • --dryRun: Show result without execution
  • --staged: Only include staged changes

Generate Commit Message

# generate a one-line commit message based on the diff from HEAD aica commit-message [options]

Options:

  • --dir: Target directory path

Show Configuration

# show current configuration aica show-config [options]

Options:

  • --default: Show default configuration

Other Commands

  • aica --version: Show version information
  • aica --help [command]: Show help information for a specific command or general help

Add Context

.cursorrules and .clinerules are automatically added to the context. To customize the context, configure the [rules] section in aica.toml.

Additionally, .cursor/rules/*.mdc files are supported by default. This function can be disabled through the settings.

MCP(Model Context Protocol)

create a mcp.json file to define the MCP server.

example:

[ { "name": "example-server", "type": "stdio", "command": "node", "args": ["./server.js"] }, { "name": "example-server", "type": "sse", "url": "http://localhost:3001/sse" } ]

set setupFile in aica.toml like below.

[mcp] setupFile = "mcp.json"

GitHub Actions

Setup

See wiki page for details.

Commands

You can interact with AI features by leaving comments with the following commands.

# edit the code with AI
/aica edit "your prompt here"

# update summary in the pull request body
/aica summary

# review the latest diff
/aica review

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