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SSD-AI

npm version License: MIT MCP Compatible Tests Coverage

AI Development Assistant based on Model Context Protocol

TypeScript + Python Support · 36 Specialized Tools · Intelligent Memory Management · Code Analysis · Reasoning Framework · Tasks Support

English | 한국어


Table of Contents


Overview

Hi-AI is an AI development assistant that implements the Model Context Protocol (MCP) standard. It provides 36 specialized tools through natural language keyword recognition, helping developers perform complex tasks intuitively.

Core Values

  • Natural Language: Execute tools automatically through Korean/English keywords

  • Intelligent Memory: Context management and compression using SQLite

  • Multi-Language Support: TypeScript, JavaScript, Python code analysis

  • Performance Optimization: Project caching system

  • Enterprise Quality: 100% test coverage and strict type system

  • Long-Running Support: Task management for asynchronous operations

  • Large-Scale Data: Cursor-based pagination


Key Features

1. Memory Management System

10 tools for maintaining context across sessions:

  • Intelligent Storage: Information classification and priority management by category

  • Context Compression: Priority-based context compression system

  • Session Restoration: Perfect recreation of previous work states

  • SQLite-Based: Concurrent control, indexing, transaction support

Key Tools:

  • save_memory - Store information in long-term memory

  • recall_memory - Search stored information

  • auto_save_context - Automatic context saving

  • restore_session_context - Session restoration

  • prioritize_memory - Memory priority management

2. Semantic Code Analysis

AST-based code analysis and navigation tools:

  • Symbol Search: Locate function, class, variable positions across projects

  • Reference Tracking: Track all usages of specific symbols

  • Multi-Language: TypeScript, JavaScript, Python support

  • Project Caching: Performance optimization through LRU cache

Key Tools:

  • find_symbol - Search for symbol definitions

  • find_references - Find symbol references

3. Code Quality Analysis

Comprehensive code metrics and quality evaluation:

  • Complexity Analysis: Cyclomatic, Cognitive, Halstead metrics

  • Coupling/Cohesion: Structural soundness evaluation

  • Quality Scores: A-F grade system

  • Improvement Suggestions: Actionable refactoring recommendations

Key Tools:

  • analyze_complexity - Complexity metric analysis

  • validate_code_quality - Code quality evaluation

  • check_coupling_cohesion - Coupling/cohesion analysis

  • suggest_improvements - Improvement suggestions

  • apply_quality_rules - Quality rule application

  • get_coding_guide - Coding guide lookup

4. Project Planning Tools

Systematic requirements analysis and roadmap generation:

  • PRD Generation: Automatic product requirements document creation

  • User Stories: Story writing including acceptance criteria

  • MoSCoW Analysis: Requirements prioritization

  • Roadmap Creation: Step-by-step development schedule planning

Key Tools:

  • generate_prd - Product requirements document generation

  • create_user_stories - User story creation

  • analyze_requirements - Requirements analysis

  • feature_roadmap - Feature roadmap creation

5. Sequential Thinking Tools

Structured problem solving and decision making support:

  • Problem Decomposition: Break down complex problems step by step

  • Thinking Chains: Sequential reasoning process generation

  • Multiple Perspectives: Analytical/Creative/Systematic/Critical thinking

  • Execution Plans: Convert tasks into executable plans

Key Tools:

  • create_thinking_chain - Thinking chain creation

  • analyze_problem - Problem analysis

  • step_by_step_analysis - Step-by-step analysis

  • break_down_problem - Problem decomposition

  • think_aloud_process - Thinking process expression

  • format_as_plan - Plan formatting

6. Prompt Engineering

Prompt quality improvement and optimization:

  • Automatic Enhancement: Convert vague requests to specific ones

  • Quality Evaluation: Score clarity, specificity, contextuality

  • Structuring: Goal, background, requirements, quality criteria

Key Tools:

  • enhance_prompt - Prompt enhancement

  • analyze_prompt - Prompt quality analysis

7. Browser Automation

Web-based debugging and testing:

  • Console Monitoring: Browser console log capture

  • Network Analysis: HTTP request/response tracking

  • Cross-Platform: Chrome, Edge, Brave support

Key Tools:

  • monitor_console_logs - Console log monitoring

  • inspect_network_requests - Network request analysis

8. UI Preview

Pre-coding UI layout visualization:

  • ASCII Art: Support for 6 layout types

  • Responsive Preview: Desktop/mobile views

  • Pre-Approval: Confirm structure before coding

Key Tools:

  • preview_ui_ascii - ASCII UI preview

9. Time Utilities

Various format time queries:

Key Tools:

  • get_current_time - Current time query (ISO, UTC, timezones, etc.)

10. Tasks and Pagination Support

Long-running operations and large-scale data processing:

  • Tasks: MCP 2025-11-25 experimental feature for long-running task management

  • Pagination: Cursor-based pagination for large dataset processing

  • Asynchronous Operations: Execute complex analysis tasks in background

  • Status Tracking: Real-time task progress monitoring

Tasks-Enabled Tools:

  • find_symbol, find_references (semantic analysis)

  • analyze_complexity, check_coupling_cohesion, validate_code_quality, suggest_improvements (code quality)

  • analyze_requirements, feature_roadmap, generate_prd (project planning)

  • apply_reasoning_framework, enhance_prompt_gemini (reasoning and prompts)


v1.6.0 Update

New Features (2025-01-27)

Tasks Support (Experimental MCP Feature)

Long-Running Task Management

  • Implementation of MCP 2025-11-25 Tasks specification

  • Execute complex analysis tasks in background

  • Real-time task status tracking and monitoring

  • TTL-based automatic cleanup (default 5 minutes, max 1 hour)

Tasks API

  • tasks/get - Query task status

  • tasks/result - Query task result (wait until completion)

  • tasks/list - List all tasks (with pagination)

  • tasks/cancel - Cancel running task

  • notifications/tasks/status - Status change notifications

Task-Enabled Tools (11 tools)

  • Semantic Analysis: find_symbol, find_references

  • Code Quality: analyze_complexity, check_coupling_cohesion, validate_code_quality, suggest_improvements

  • Project Planning: analyze_requirements, feature_roadmap, generate_prd

  • Reasoning/Prompts: apply_reasoning_framework, enhance_prompt_gemini

Pagination Support

Cursor-Based Pagination

  • MCP specification compliant cursor-based implementation

  • Efficient processing of large lists

  • Enhanced security through opaque cursors

Supported List Operations

  • tools/list - Tool list (20 items by default)

  • resources/list - Resource list

  • prompts/list - Prompt list

  • tasks/list - Task list

Integration Effects

  • Asynchronous Operation Support: Execute complex analysis in background

  • Large-Scale Data Processing: Improved memory efficiency through pagination

  • Real-Time Monitoring: Task progress tracking

  • Enhanced User Experience: Perform other tasks during long operations


Installation

System Requirements

  • Node.js 18.0 or higher

  • TypeScript 5.0 or higher

  • MCP-compatible client (Claude Desktop, Cursor, Windsurf)

  • Python 3.x (for Python code analysis)

Installation Methods

NPM Package

# Global installation npm install -g @ssdeanx/ssd-ai # Local installation npm install @ssdeanx/ssd-ai

Smithery Platform

# One-click installation https://smithery.ai/server/@su-record/hi-ai

MCP Client Configuration

Add to your Claude Desktop or other MCP client's configuration file:

{ "mcpServers": { "hi-ai": { "command": "hi-ai", "args": [], "env": {} } } }

Tool Catalog

Complete Tool List (36 tools)

Category

Count

Tool List

Memory

10

save_memory, recall_memory, list_memories, search_memories, delete_memory, update_memory, auto_save_context, restore_session_context, prioritize_memory, start_session

Semantic

2

find_symbol, find_references

Thinking

6

create_thinking_chain, analyze_problem, step_by_step_analysis, break_down_problem, think_aloud_process, format_as_plan

Reasoning

1

apply_reasoning_framework

Code Quality

6

analyze_complexity, validate_code_quality, check_coupling_cohesion, suggest_improvements, apply_quality_rules, get_coding_guide

Planning

4

generate_prd, create_user_stories, analyze_requirements, feature_roadmap

Prompt

2

enhance_prompt, analyze_prompt

Browser

2

monitor_console_logs, inspect_network_requests

UI

1

preview_ui_ascii

Time

1

get_current_time

Tasks-Enabled Tools (11 tools)

The following tools support long-running operations through Tasks:

  • Semantic Analysis: find_symbol, find_references

  • Code Quality: analyze_complexity, check_coupling_cohesion, validate_code_quality, suggest_improvements

  • Project Planning: analyze_requirements, feature_roadmap, generate_prd

  • Reasoning/Prompts: apply_reasoning_framework, enhance_prompt_gemini

Keyword Mapping Examples

Memory Tools

Tool

English

Korean

save_memory

remember, save this

기억해, 저장해

recall_memory

recall, remind me

떠올려, 기억나

auto_save_context

commit, checkpoint

커밋, 저장

Code Analysis Tools

Tool

English

Korean

find_symbol

find function, where is

함수 찾아, 클래스 어디

analyze_complexity

complexity, how complex

복잡도, 복잡한지

validate_code_quality

quality, review

품질, 리뷰

Tasks Tools

Tool

English

Korean

tasks/get

task status, progress

작업 상태, 진행 상황

tasks/result

get result, wait for completion

결과 가져와, 완료될 때까지

tasks/cancel

cancel task, stop

작업 취소, 중지해


Architecture

System Structure

graph TB subgraph "Client Layer" A[Claude Desktop / Cursor / Windsurf] end subgraph "MCP Server" B[Hi-AI v1.6.0] end subgraph "Core Libraries" C1[MemoryManager] C2[ContextCompressor] C3[ProjectCache] C4[PythonParser] C5[TaskManager] end subgraph "Tool Categories" D1[Memory Tools x10] D2[Semantic Tools x2] D3[Thinking Tools x6] D4[Quality Tools x6] D5[Planning Tools x4] D6[Prompt Tools x2] D7[Browser Tools x2] D8[UI Tools x1] D9[Time Tools x1] D10[Tasks Support] end subgraph "Data Layer" E1[(SQLite Database)] E2[Project Files] E3[Task Store] end A <--> B B --> C1 & C2 & C3 & C4 & C5 B --> D1 & D2 & D3 & D4 & D5 & D6 & D7 & D8 & D9 & D10 C1 --> E1 C3 --> E2 C4 --> E2 C5 --> E3 D1 --> C1 & C2 D2 --> C3 & C4 D4 --> C4 D10 --> C5

Core Components

TaskManager

  • Role: Lifecycle management of long-running tasks

  • Features: Task creation, status tracking, result storage, TTL management

  • States: working, input_required, completed, failed, cancelled

  • Notifications: Real-time status change notifications

Pagination System

  • Role: Efficient processing of large list data

  • Method: Cursor-based pagination

  • Security: Prevent data exposure through opaque cursors

Data Flow

User Input (Natural Language) ↓ Keyword Matching (Tool Selection) ↓ Tasks Support Check ↓ Normal Execution or Task Creation ↓ Asynchronous Execution (Tasks) ↓ Status Polling or Real-time Notifications ↓ Result Return

Performance

Major Optimizations

Project Caching

  • Performance improvement for repeated analysis through LRU cache

  • Maintain latest state with 5-minute TTL

  • Resource management through memory limits

Memory Operations

  • Batch operation optimization through SQLite transactions

  • Time complexity improvement: O(n²) → O(n)

  • Fast lookup through indexing

Tasks Optimization

  • Improved UI responsiveness through background execution

  • Prevent memory leaks through TTL-based automatic cleanup

  • Efficient monitoring through status-based polling

Response Format

  • Switch to concise response format

  • Output focused on core information

v1.5.0 Response Example:

{ "action": "save_memory", "key": "test-key", "value": "test-value", "category": "general", "timestamp": "2025-01-16T12:34:56.789Z", "status": "success", "metadata": { ... } }

v1.6.0 Response Example:

✓ Saved: test-key Category: general

Development Guide

Environment Setup

# Clone repository git clone https://github.com/ssdeanx/ssd-ai.git cd ssd-ai # Install dependencies npm install # Build npm run build # Development mode npm run dev

Testing

# Run all tests npm test # Watch mode npm run test:watch # UI mode npm run test:ui # Coverage report npm run test:coverage

Code Style

  • TypeScript: strict mode

  • Types: Use src/types/tool.ts

  • Tests: Maintain 100% coverage

  • Commits: Conventional Commits format

Adding New Tools

  1. Create file in src/tools/category/ directory

  2. Implement ToolDefinition interface

  3. Register tool in src/index.ts

  4. Write tests in tests/unit/ directory

  5. Update README

Pull Request

  1. Create feature branch: feature/tool-name

  2. Write and pass tests

  3. Confirm successful build

  4. Create PR and request review


Contributors

Special Thanks

  • Smithery - MCP server deployment and one-click installation platform


License

MIT License - Free to use, modify, and distribute


Citation

If you use this project for research or commercial purposes:

@software{hi-ai2024, author = {ssdeanx}, title = {Hi-AI: Natural Language MCP Server for AI-Assisted Development}, year = {2024}, version = {1.6.0}, url = {https://github.com/su-record/hi-ai} }

Star History

Star History Chart

Hi-AI v1.6.0

Tasks Support · Cursor-Based Pagination · 36 Specialized Tools · 122 Tests · 100% Coverage

Made with ❤️ by Su

🏠 Homepage · 📚 Documentation · 🐛 Issues · 💬 Discussions

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security - not tested
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license - permissive license
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quality - not tested

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