Prompt MCP Server for Amazon Q
An MCP server for the Amazon Q Developer CLI to manage local prompt files.
Prompt MCP Server for Amazon Q
A single-file Model Context Protocol (MCP) server for Amazon Q Developer CLI that manages prompt files (*.md) from local directories.
Features
- π Real-time File Monitoring: Automatically detects file changes and updates prompt list
- π’ MCP Notifications: Sends notifications to Amazon Q CLI for automatic refresh
- π Prompt Discovery: Lists all
*.mdfiles from configured directories - π Default Directory:
~/.aws/amazonq/prompts(created automatically) - π― Custom Directories: Override with
PROMPTS_PATHenvironment variable (PATH-like format) - π§ Variable Substitution: Supports
{variable}placeholders in prompts - π Configurable Logging: Production-safe defaults with comprehensive debug mode
- π Cross-Platform: Works on Unix/Linux/macOS (Windows compatible)
- β‘ Error Handling: Comprehensive error handling and logging
- π¦ No Dependencies: Pure Python 3.8+ implementation
Installation & Usage
Quick Start with uvx (Recommended)
# Install and run directly (after publishing to PyPI)
uvx prompt-mcp-server
# Or install from local build
pyproject-build
uvx --from ./dist/prompt_mcp_server-2.0.3-py3-none-any.whl prompt-mcp-server
Direct Usage
# Run the server directly
python3 mcp_server/prompt_mcp_server.py
# With custom prompt directories
PROMPTS_PATH="./my-prompts:~/.aws/amazonq/prompts" python3 mcp_server/prompt_mcp_server.py
Amazon Q Integration
# The workspace is configured to use uvx with the built package
q mcp list # Verify configuration (should show: prompt-server uvx)
q chat # Start Amazon Q CLI
/prompts # List available prompts
@debug_code # Use a prompt
Configuration files:
.amazonq/mcp.json- Uses local development pathtests/.amazonq/mcp.json- Uses local built packagetests/.amazonq/mcp-published.json- For published package (copy tomcp.jsonafter publishing)
Building and Testing
# Build package
pyproject-build
# Test with uvx
echo '{"jsonrpc": "2.0", "id": 1, "method": "initialize"}' | uvx --from ./dist/prompt_mcp_server-2.0.0-py3-none-any.whl prompt-mcp-server
Configuration
Environment Variables
PROMPTS_PATH: Colon-separated list of directories (Unix) or semicolon-separated (Windows)- Default:
~/.aws/amazonq/prompts
Workspace Configuration
The .amazonq/mcp.json file configures Amazon Q to use this server:
Development Configuration (Local)
{
"mcpServers": {
"prompt-server": {
"command": "python3",
"args": ["mcp_server/prompt_mcp_server.py"],
"timeout": 10000
}
}
}
Production Configuration (PyPI)
{
"mcpServers": {
"prompt-server": {
"command": "uvx",
"args": ["prompt-mcp-server@latest"],
"disabled": false,
"autoApprove": []
}
}
}
Environment Variables
PROMPTS_PATH
- Purpose: Specify custom directories to search for prompt files
- Format: Colon-separated list of directories (Unix/Linux/macOS) or semicolon-separated (Windows)
- Default:
~/.aws/amazonq/prompts - Example:
export PROMPTS_PATH="/path/to/prompts1:/path/to/prompts2"
MCP_LOG_LEVEL
- Purpose: Set the logging level for the MCP server
- Values:
DEBUG,INFO,WARNING,ERROR,CRITICAL - Default:
WARNING(production level - only warnings and errors) - Example:
export MCP_LOG_LEVEL=INFO
MCP_DEBUG_LOGGING
- Purpose: Enable comprehensive debug logging with detailed request/response tracing
- Values:
1,true,yes,on(case-insensitive) - Default: Disabled
- When enabled:
- Forces
INFOlevel logging regardless ofMCP_LOG_LEVEL - Creates debug log file for easy monitoring
- Logs all MCP requests and responses with full JSON details
- Logs file monitoring activity and cache operations
- Color-coded log messages with emojis for easy identification
- Forces
- Example:
export MCP_DEBUG_LOGGING=1 # Then monitor logs with: tail -f /tmp/mcp_server_debug.log
MCP_LOG_FILE
- Purpose: Set custom path for the debug log file
- Default:
/tmp/mcp_server_debug.log - Only used when:
MCP_DEBUG_LOGGINGis enabled - Example:
export MCP_DEBUG_LOGGING=1 export MCP_LOG_FILE=/path/to/custom/mcp_debug.log # Then monitor logs with: tail -f /path/to/custom/mcp_debug.log
Debug Logging Usage
To enable debug logging for troubleshooting:
# Enable debug logging with default log file
export MCP_DEBUG_LOGGING=1
# Or enable with custom log file location
export MCP_DEBUG_LOGGING=1
export MCP_LOG_FILE=/path/to/custom/debug.log
# Start Amazon Q CLI
q chat
# In another terminal, monitor detailed logs
tail -f /tmp/mcp_server_debug.log
# Or if using custom log file:
tail -f /path/to/custom/debug.log
# Test file changes
echo "# Test" > ~/.aws/amazonq/prompts/test.md
rm ~/.aws/amazonq/prompts/test.md
The debug logs will show:
- π₯ Raw requests received from Amazon Q CLI
- π΅ Parsed incoming requests with details
- π’ Outgoing responses with full content
- π€ Raw responses sent to Amazon Q CLI
- π’ MCP notifications sent (e.g., prompts list changed)
- File monitoring activity and cache operations
Testing
The project includes comprehensive unit and functional tests:
Run All Tests
# Run both unit and functional tests
python3 tests/run_all_tests.py
# Run only unit tests
python3 tests/run_all_tests.py --unit-only
# Run only functional tests
python3 tests/run_all_tests.py --functional-only
Individual Test Suites
# Unit tests (31 tests)
python3 tests/test_prompt_mcp_server.py
# Functional tests (14 tests)
python3 tests/test_functional.py
# UVX integration tests (8 tests)
python3 tests/test_uvx_integration.py
Test Results
- Current Status: β All 53 tests passing (100% success rate)
- Detailed Results: See
tests/results/directory for comprehensive reports - Performance: Complete test suite runs in ~10.5 seconds
Test Coverage
- Unit Tests: 31 tests covering all server components
- Functional Tests: 14 end-to-end integration tests
- UVX Integration: 8 tests for package execution scenarios
- Total Coverage: 53 comprehensive tests
Creating Prompts
Simple Prompt
Create ~/.aws/amazonq/prompts/debug_code.md:
# Debug Code Issues
Help me debug code by identifying issues and suggesting fixes.
Parameterized Prompt
Create ~/.aws/amazonq/prompts/create_function.md:
# Create {language} Function
Create a {language} function named {function_name} that {description}.
Requirements:
- Follow {language} best practices
- Include error handling
- Add comprehensive tests
Usage Examples
List Available Prompts
echo '{"jsonrpc": "2.0", "id": 1, "method": "prompts/list"}' | python3 mcp_server/prompt_mcp_server.py
Get a Prompt with Variables
echo '{"jsonrpc": "2.0", "id": 2, "method": "prompts/get", "params": {"name": "create_function", "arguments": {"language": "Python", "function_name": "calculate", "description": "adds two numbers"}}}' | python3 mcp_server/prompt_mcp_server.py
Requirements
- Python 3.6+
- No external dependencies
- Cross-platform support
Error Handling
The server includes comprehensive error handling:
- File permission validation
- File size limits (1MB max)
- Unicode encoding support (UTF-8 with latin-1 fallback)
- Directory access validation
- Graceful fallback to default directories
- Detailed logging to stderr
Testing
All core features have been tested:
- β MCP protocol compliance (initialize, prompts/list, prompts/get)
- β Prompt discovery and variable extraction
- β PROMPTS_PATH environment variable support
- β Cross-platform path handling
- β Error handling and edge cases
- β Amazon Q CLI integration
Project Structure
mcp-prompts-local/
βββ mcp_server/ # Main package
β βββ __init__.py # Package initialization
β βββ prompt_mcp_server.py # MCP server implementation
βββ tools/ # Development tools
β βββ publish.py # Automated publishing script
β βββ README.md # Tools documentation
βββ tests/ # Test suite
β βββ test_prompt_mcp_server.py # Unit tests (31 tests)
β βββ test_functional.py # Functional tests (14 tests)
β βββ test_uvx_integration.py # UVX integration tests (8 tests)
β βββ results/ # Test execution results
β β βββ FULL_TEST_RESULTS.md # Initial test results
β β βββ FINAL_TEST_RESULTS.md # Final test results (100% success)
β β βββ README.md # Test results documentation
β βββ .amazonq/ # Test configurations
βββ .amazonq/ # Workspace configuration
β βββ mcp.json # Development MCP config
βββ dist/ # Built packages
βββ pyproject.toml # Package configuration
βββ README.md # This file
βββ LICENSE # MIT license
Architecture
This is a single-file implementation that:
- Reads JSON-RPC requests from stdin
- Scans configured directories for
*.mdfiles - Extracts variables using regex (
{variable}pattern) - Substitutes variables in prompt content
- Returns responses via stdout
- Logs to stderr
Version History
For detailed version information, release notes, and changelog, see CHANGELOG.md.
For more information about the Model Context Protocol, see the MCP specification.
Related Servers
Scout Monitoring MCP
sponsorPut performance and error data directly in the hands of your AI assistant.
Alpha Vantage MCP Server
sponsorAccess financial market data: realtime & historical stock, ETF, options, forex, crypto, commodities, fundamentals, technical indicators, & more
QuantConnect
A server for local interactions with the QuantConnect API.
Kai
Kai provides a bridge between large language models (LLMs) and your Kubernetes clusters, enabling natural language interaction with Kubernetes resources. The server exposes a comprehensive set of tools for managing clusters, namespaces, pods, deployments, services, and other Kubernetes resources
NeoCoder
Enables AI assistants to use a Neo4j knowledge graph for standardized coding workflows, acting as a dynamic instruction manual and project memory.
Last9
Seamlessly bring real-time production contextβlogs, metrics, and tracesβinto your local environment to auto-fix code faster.
mcproc
Manage background processes for AI agents using the Model Context Protocol (MCP).
x402engine
50+ pay-per-call APIs for AI agents via HTTP 402 crypto micropayments. $0.001β$0.12 per call with USDC and USDm.
MCP Server + Asgardeo
A sample MCP server that uses Asgardeo for client authentication and connection.
VSCode Maestro MCP
The most comprehensive MCP server for VS Code β 100+ tools across 25 categories. File ops, terminal, git, LSP providers (hover, completion, definition, references), and more. Free core + premium features.
Claude-FAF-MCP
Only Persistent Project Context MCP Server - Official Anthropic Registry
Solana Dev MCP
An MCP server for Solana development providing basic RPC methods and helpful prompts.