Maverick MCP Server

Maverick MCP Server

An MCP server that enables Amazon Q CLI users to create, query, and manage Maverick sites through natural language commands.

Category
Visit Server

README

Maverick MCP Server

An MCP (Model Context Protocol) server for managing Maverick sites through Amazon Q CLI.

Features

  • Create Sites: Create new Maverick sites with comprehensive configuration options
  • Query Sites: Search and filter sites using various criteria
  • Get Site Details: Retrieve detailed information about specific sites

Installation

  1. Install the package:
cd /Users/vigneshwaran.rajesh/companyWork/EE-hackathon/maverick-mcp
pip install -e .
pip install -r requirements.txt
  1. Test the installation:
python3 test_server.py
  1. Set up environment variables:
export MAVERICK_BASE_URL="https://maverick-staging.appiancloud.com"
export MAVERICK_API_TOKEN="your-api-token-here"

Configuration for Amazon Q CLI

Add to your Q CLI MCP configuration file at ~/.aws/amazonq/mcp.json:

{
  "mcpServers": {
    "maverick": {
      "command": "python3",
      "args": ["/Users/vigneshwaran.rajesh/companyWork/EE-hackathon/maverick-mcp/server.py"],
      "env": {
        "MAVERICK_BASE_URL": "https://maverick-staging.appiancloud.com",
        "MAVERICK_API_TOKEN": "your-actual-api-token-here"
      }
    }
  }
}

Note: Use the full path to your server.py file in the configuration.

Available Tools

1. maverick___create_site

Creates a new Maverick site with specified configuration.

Required Parameters:

  • subdomain: The site name/subdomain

Optional Parameters:

  • installer: Appian version (e.g., "22.1.235.0")
  • installerLabel: Installer label (e.g., "22.1-latest")
  • region: AWS region (e.g., "us-east-1")
  • serverSize: Server size (e.g., "m5.large")
  • purpose: Site purpose (development, hackathon, etc.)
  • customerName: Customer name
  • dryRun: Validate without creating (boolean)
  • And many more configuration options...

2. maverick___query_sites

Query sites using various filters and criteria.

Filter Options:

  • siteList: Array of site IDs
  • purpose: Array of purposes to filter by
  • region: Array of regions to filter by
  • accountName: Array of account names
  • createdAfter: Sites created after specified time
  • createdBefore: Sites created before specified time
  • modifiedAfter: Sites modified after specified time
  • status: Site status (Active, Shutdown, etc.)
  • labelName + labelValue: Filter by labels
  • startIndex: Pagination start (default: 1)
  • batchSize: Results per page (default: 20)

3. maverick___get_site_by_id

Get detailed information about a specific site.

Parameters:

  • identifier: Site ID (numeric) or site name/subdomain

4. maverick___manage_site

Perform various actions on existing Maverick sites.

Required Parameters:

  • identifier: Site ID (numeric) or site name/subdomain
  • action: Action to perform

Supported Actions:

  • start: Start a stopped site
  • restart: Restart a running site
  • stop: Stop a running site (data persists)
  • force-stop: Force stop (bypasses standard checks)
  • force-restart: Force restart (force stop + start)
  • delete: Permanently delete a site
  • revert: Revert site to a specific snapshot
  • on-demand-backup: Take an on-demand backup
  • edit: Edit site configuration
  • clone: Create a copy of the site
  • move: Move site to different region
  • resize: Increase site volume size

Action-Specific Parameters:

  • Edit: installer, serverSize, purpose, siteProperties, etc.
  • Revert: restoreSpec (with siteID and createdAt)
  • Clone: reason, requestorFirstName, requestorLastName, requestorEmail, supportCase
  • Move: region, email (optional)
  • Resize: volumeSize

5. maverick___get_site_resize_status

Check the status of an ongoing site resize operation.

Parameters:

  • siteId: Site ID to check resize status for

Usage Examples

Create a Simple Site

Create a new Maverick site with subdomain "my-test-site"

Create an Advanced Site

Create a Maverick site with subdomain "hackathon-site", purpose "hackathon", customer "Appian Engineering", server size "m5.large", and region "us-east-1"

Query Sites by Purpose

Find all Maverick sites with purpose "development"

Query Sites by Region

Show me all sites in us-east-1 and us-west-2 regions

Query Recent Sites

Find all sites created after 01/01/2024

Get Specific Site

Get details for Maverick site with ID 1004544

Query with Pagination

Show me the first 10 active sites

Site Management Actions

Start Maverick site with ID 1004544
Stop site "my-test-site" gracefully
Restart site 1004544 with force restart
Delete site "old-test-site" permanently
Take an on-demand backup of site 1004544

Edit Site Configuration

Edit site 1004544 to change server size to "m5.xlarge" and purpose to "hackathon"
Update site "my-site" to use installer label "23.1-latest"

Clone Site

Clone site 1004544 for debugging with reason "Reproduce customer issue" and support case "CN-1234"

Move and Resize Sites

Move site 1004544 to region "us-west-2"
Resize site 1004544 volume to 100 GB
Check resize status for site 1004544

Testing

Run the test script to verify everything is working:

python3 test_server.py

This will test all three tools and show you what to expect.

Response Format

The server provides formatted, human-readable responses with:

  • ✅ Success indicators
  • ❌ Error indicators
  • 📊 Structured site information with emojis for easy reading
  • Pagination information when applicable
  • Total count of matching results

Error Handling

The server handles various error scenarios:

  • Missing API tokens
  • Validation errors (400)
  • Not found errors (404)
  • Server errors (500)
  • Network timeouts
  • Invalid parameters

Files in this Project

  • server.py - Main MCP server implementation with all 5 tools
  • requirements.txt - Python dependencies
  • setup.py - Package configuration
  • test_server.py - Test script to verify all functionality
  • test_auth.py - Authentication testing script
  • q-config-example.json - Example Q CLI configuration
  • README.md - This documentation

Next Steps

  1. Get your Maverick API token from your Maverick instance
  2. Set the environment variables with your actual token
  3. Add the MCP server configuration to ~/.aws/amazonq/mcp.json
  4. Restart Amazon Q CLI and test with: q chat
  5. Try the example commands to verify everything works

Development

To extend the server with additional Maverick APIs:

  1. Add new tool definitions to handle_list_tools()
  2. Add corresponding handlers to handle_call_tool()
  3. Implement the API call functions
  4. Update this README with the new functionality

Environment Variables

  • MAVERICK_BASE_URL: Base URL for Maverick API (default: staging)
  • MAVERICK_API_TOKEN: Authentication token for Maverick API (required)

Note: The server uses the appian-api-key header for authentication, which is one of the supported methods in Maverick API. Other supported methods include:

  • appian-api-key header (used by this server)
  • Authorization: Bearer header
  • Basic Authentication with null username
  • Basic Authentication with null password

Authentication Setup

To get your API token:

  1. Configure object security for a service account in your Maverick instance
  2. Generate an API key for that service account
  3. Set the MAVERICK_API_TOKEN environment variable with your key

Example:

export MAVERICK_API_TOKEN="your-actual-api-key-here"

Dependencies

  • mcp>=1.10.0: Model Context Protocol library
  • httpx>=0.25.0: Async HTTP client
  • Python 3.8+

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured