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GASSAPI MCP Server

by martin-1103
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GASSAPI MCP v2

Model Context Protocol (MCP) server untuk integrasi GASSAPI dengan AI assistants.

🚀 Quick Start

Prerequisites

  • Node.js >= 16.0.0

  • npm atau yarn

  • Akses ke GASSAPI backend

📦 Installation

Step 1: Install Package

npm install martin-1103/mcp2

Step 2: Installation Method

Method 1: Global Install (Recommended)

npm install -g gassapi-mcp2 claude mcp add gassapi-mcp2

Method 2: Local Install

npm install gassapi-mcp2 claude mcp add gassapi-mcp2

📋 Simple Setup (3 Steps)

Step 1: Login ke GASSAPI Backend

Login ke backend GASSAPI untuk mendapatkan access token:

curl -X POST "http://mapi.gass.web.id/?act=login" \ -H "Content-Type: application/json" \ -d '{"email": "your-email@example.com", "password": "YourPassword"}'

Step 2: Dapatkan Project ID

List projects untuk mendapatkan project ID:

curl -X GET "http://mapi.gass.web.id/?act=projects" \ -H "Authorization: Bearer YOUR_ACCESS_TOKEN"

Step 3: Buat gassapi.json File

Buat file gassapi.json di working directory Anda dengan template:

{ "project": { "id": "YOUR_PROJECT_ID_HERE", "name": "Your Project Name", "description": "Your project description" }, "mcpClient": { "token": "YOUR_TOKEN_HERE" } }

Ganti dengan:

  • YOUR_PROJECT_ID_HERE → Project ID dari Step 2

  • YOUR_TOKEN_HERE → Token dari Step 1

Note: Base URL sudah hardcoded ke http://mapi.gass.web.id - tidak perlu konfigurasi API URL.

✅ Verification

Test MCP Server

# Test help command gassapi-mcp2 --help # Test version gassapi-mcp2 --version # Test status gassapi-mcp2 --status

Claude Code Integration

# List MCP servers claude mcp list # Test connection # Restart Claude Code dan coba gunakan GASSAPI tools

🛠️ Development

Local Development

# Clone repository git clone <repository-url> cd gassapi-mcp2 # Install dependencies npm install # Build npm run build # Development mode npm run dev # Type checking npm run typecheck

🔧 Configuration Format

gassapi.json Structure

{ "project": { "id": "proj_abc123def456", "name": "Project Name", "description": "Project description" }, "mcpClient": { "token": "plain_text_mcp_token_here" } }

Note: Base URL sudah hardcoded ke http://mapi.gass.web.id - tidak perlu api_base_url configuration.

Auto-Detection

MCP server akan otomatis mencari gassapi.json di:

  • Current working directory

  • Parent directories (hingga 5 levels up)

🛠️ Available MCP Tools

Authentication & Project Context

  • get_project_context - Get project info with environments and folders

  • health_check - Check MCP server status

Environment Management

  • list_environments - List all environments

  • get_environment_details - Get detailed environment info

  • create_environment - Create new environment

  • update_environment_variables - Update environment variables

  • set_default_environment - Set default environment

  • delete_environment - Delete environment

Folder Management

  • list_folders - List project folders

  • create_folder - Create new folder

  • update_folder - Update folder details

  • move_folder - Move folder to different parent

  • delete_folder - Delete folder

  • get_folder_details - Get folder details

Endpoint Management

  • list_endpoints - List all endpoints

  • get_endpoint_details - Get detailed endpoint configuration

  • create_endpoint - Create endpoint with semantic context

  • update_endpoint - Update endpoint configuration

Flow Management

  • create_flow - Create automation flow

  • execute_flow - Execute flow

  • get_flow_details - Get flow details

  • list_flows - List all flows

  • delete_flow - Delete flow

Testing Tools

  • test_endpoint - Test single endpoint

  • test_multiple_endpoints - Test multiple endpoints

  • create_test_suite - Create test suite

  • list_test_suites - List test suites

📝 Endpoint Documentation & Cataloging

Mencatat Endpoint yang Sudah Ada

create_endpoint( name: "User Registration", method: "POST", url: "/api/auth/register", folder_id: "folder_authentication", description: "Endpoint untuk registrasi user baru dengan email verification", purpose: "Public user registration dengan email verification required", headers: { "Content-Type": "application/json" }, body: '{"name": "{{userName}}", "email": "{{userEmail}}", "password": "{{password}}"}', request_params: { "name": "Full name untuk display", "email": "Email address untuk login dan communication", "password": "User password (min 8 chars, include uppercase, lowercase, numbers)" }, response_schema: { "user_id": "Unique user identifier", "name": "User display name", "email": "User email address", "status": "Account status (active|inactive|suspended)", "verification_required": "Whether email verification needed" } )

Workflow: Backend → MCP Documentation → AI Frontend

1. Backend Developer:

// Di PHP code (sudah ada) public function register() { // Logic untuk registrasi user // Return user data atau error }

2. Documentation Team:

// Gunakan MCP tools untuk catat create_endpoint( name: "User Registration", method: "POST", url: "/api/auth/register", // ... semantic context untuk AI understanding )

3. AI Frontend Team:

// AI dapat endpoint info dan generate UI get_endpoint_details(endpoint_id: "ep_user_reg") // AI understands purpose dan generate appropriate React components

Contoh Endpoint User Registration dengan Semantic Context

create_endpoint( name: "User Registration", method: "POST", url: "/api/auth/register", folder_id: "folder_authentication", description: "Public user registration endpoint dengan email verification", purpose: "New user account creation dengan email verification untuk security", // Request parameters documentation request_params: { "name": "User's full name for display purposes", "email": "User's email address for login and communication", "password": "Password with security requirements (8+ chars, mixed case, numbers)", "confirm_password": "Password confirmation untuk prevent typos" }, // Response schema documentation response_schema: { "user_id": "Unique system identifier untuk user record", "name": "User display name untuk UI", "email": "User email address untuk authentication", "status": "Account status: active|inactive|suspended|pending_verification", "email_verified": "Email verification status flag", "verification_token": "Email verification token (if required)", "created_at": "Account creation timestamp" }, // Important implementation notes header_docs: { "Content-Type": "Application/JSON untuk request body", "Accept": "Application/JSON untuk response format" } )

Semantic Fields untuk AI Understanding

Field

Type

Purpose

Example

AI Benefit

purpose

string

Business purpose (max 250 chars)

"User registration with email verification"

AI understands use case and generates appropriate UI flow

request_params

object

Parameter documentation

{"name": "User's full name for display"}

AI generates correct form fields with validation

response_schema

object

Response field documentation

{"user_id": "Unique user identifier"}

AI handles response data correctly in frontend code

header_docs

object

Header documentation

{"Content-Type": "Application/JSON"}

AI includes proper headers in API calls

🔧 Development

Build & Run

# Build project npm run build # Run development server npm run dev # Run production server npm start # Type checking npm run typecheck # Clean build npm run clean

Testing

# Run basic test npm test # Run all tests node test/runners/run-all-tests.js # Run specific category node test/runners/run-category-tests.js endpoints # Run semantic fields tests node test/unit/endpoints/semantic-test-runner.js

🔍 Configuration Format

gassapi.json Structure

{ "project": { "id": "proj_abc123def456", "name": "Project Name", "description": "Project description" }, "mcpClient": { "token": "plain_text_mcp_token_here" } }

Note: Base URL sudah hardcoded ke http://mapi.gass.web.id - tidak perlu api_base_url configuration.

Auto-Detection

MCP server akan otomatis mencari gassapi.json di:

  • Current working directory

  • Parent directories (hingga 5 levels up)

🚨 Troubleshooting

Common Issues

1. "No configuration found"

  • Pastikan gassapi.json ada di working directory atau parent directory

  • Cek format JSON valid

2. "Invalid token"

  • Login kembali ke backend untuk dapat token baru

  • Pastikan token belum expired

3. "Backend unavailable"

  • Pastikan backend server sudah berjalan di http://mapi.gass.web.id

  • Check koneksi internet dan firewall settings

4. MCP server not found

  • Install globally: npm install -g gassapi-mcp2

  • Atau gunakan npx: npx gassapi-mcp2

Debug Commands

# Check MCP server status gassapi-mcp2 --status # Test help gassapi-mcp2 --help # Test version gassapi-mcp2 --version # Test backend connectivity curl "http://mapi.gass.web.id/?act=health"

📞 Usage Examples

Basic Usage in Claude Code

User: "Show my project" AI: Uses get_project_context tool User: "Create endpoint for user registration" AI: create_endpoint dengan semantic fields User: "Test this endpoint" AI: test_endpoint dengan environment variables

Advanced Usage

User: "Create flow untuk user registration dengan email verification" AI: create_flow dengan multiple steps dan validation User: "List semua endpoints di folder Authentication" AI: list_endpoints dengan filter folder_id

🤝 Contributing

  1. Fork repository

  2. Create feature branch

  3. Run tests: npm test

  4. Submit pull request

📄 License

MIT License

🎯 Key Benefits:

  • ✅ Semantic context untuk AI understanding

  • ✅ Real-time endpoint management

  • ✅ Automated flow creation

  • ✅ Comprehensive testing tools

  • ✅ Easy integration dengan Claude Code/Cursor

Deploy Server
A
security – no known vulnerabilities
F
license - not found
A
quality - confirmed to work

How are these scores calculated?

remote-capable server

The server can be hosted and run remotely because it primarily relies on remote services or has no dependency on the local environment.

Tools

View all tools

Enables AI assistants to manage API endpoints, environments, and testing workflows through the GASSAPI backend. Provides semantic documentation tools for endpoint cataloging and automated flow creation for backend-to-frontend development workflows.

  1. 🚀 Quick Start
    1. Prerequisites
  2. 📦 Installation
    1. Step 1: Install Package
    2. Step 2: Installation Method
    3. Method 1: Global Install (Recommended)
    4. Method 2: Local Install
  3. 📋 Simple Setup (3 Steps)
    1. Step 1: Login ke GASSAPI Backend
    2. Step 2: Dapatkan Project ID
    3. Step 3: Buat gassapi.json File
  4. ✅ Verification
    1. Test MCP Server
    2. Claude Code Integration
  5. 🛠️ Development
    1. Local Development
  6. 🔧 Configuration Format
    1. gassapi.json Structure
    2. Auto-Detection
  7. 🛠️ Available MCP Tools
    1. Authentication & Project Context
    2. Environment Management
    3. Folder Management
    4. Endpoint Management
  8. 📝 Endpoint Documentation & Cataloging
    1. Mencatat Endpoint yang Sudah Ada
    2. Workflow: Backend → MCP Documentation → AI Frontend
    3. Contoh Endpoint User Registration dengan Semantic Context
    4. Semantic Fields untuk AI Understanding
  9. 🔧 Development
    1. Build & Run
    2. Testing
  10. 🔍 Configuration Format
    1. gassapi.json Structure
    2. Auto-Detection
  11. 🚨 Troubleshooting
    1. Common Issues
    2. Debug Commands
  12. 📞 Usage Examples
    1. Basic Usage in Claude Code
    2. Advanced Usage
  13. 🤝 Contributing
    1. 📄 License

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