Pingera MCP Server
A Model Context Protocol (MCP) server for the Pingera monitoring service, providing seamless integration between AI models and monitoring data.
Features
- Modular Architecture: Separate Pingera API client library with clean abstractions
- Flexible Operation Modes: Run in read-only or read-write mode
- MCP Tools: Execute monitoring operations through tools (list_pages, get_page_details, test_connection)
- Robust Error Handling: Comprehensive error handling with custom exception hierarchy
- Real-time Data: Direct integration with Pingera API v1 for live monitoring data
- Type Safety: Pydantic models for data validation and serialization
- Configurable: Environment-based configuration management
Quick Start
Prerequisites
- Python 3.10+
- UV package manager
- Pingera API key - get one at app.pingera.ru
Installation and Setup
uv sync
python -m pingera_mcp
The server will start in read-only mode by default and connect to the Pingera API.
Operation Modes
The Pingera MCP Server supports two transport modes:
1. Stdio Mode (Default)
Used for local integration with Claude Desktop and other stdio-based MCP clients. Authentication is configured via environment variables.
python -m pingera_mcp
2. HTTP/SSE Mode
Enables web-based access through HTTP with Server-Sent Events. Perfect for remote clients, web applications, and programmatic access.
export PINGERA_TRANSPORT_MODE=sse
export PINGERA_HTTP_HOST=0.0.0.0
export PINGERA_HTTP_PORT=5000
python -m pingera_mcp
The server will be accessible at http://0.0.0.0:5000/mcp/
Authentication in SSE Mode
SSE mode supports two authentication methods via the Authorization header:
-
API Key Authentication (recommended for testing):
Authorization: YOUR_API_KEY
-
JWT Bearer Token Authentication:
Authorization: Bearer YOUR_JWT_TOKEN
Example: Python Client for SSE Mode
import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
async def main():
client = MultiServerMCPClient({
"pingera": {
"url": "http://0.0.0.0:5000/mcp/",
"transport": "streamable_http",
"headers": {
"Authorization": "YOUR_API_KEY",
}
}
})
tools = await client.get_tools()
print(f"Available tools: {len(tools)}")
asyncio.run(main())
SSE Mode Configuration Options
PINGERA_TRANSPORT_MODE - Set to sse to enable HTTP/SSE mode (default: stdio)
PINGERA_HTTP_HOST - Host to bind to (default: 0.0.0.0)
PINGERA_HTTP_PORT - Port to listen on (default: 5000)
PINGERA_REQUIRE_AUTH_HEADER - Require Authorization header (default: false)
Note: In SSE mode, you can either:
- Provide credentials via environment variables (PINGERA_API_KEY or PINGERA_JWT_TOKEN) as fallback
- Send credentials in the Authorization header with each request (recommended)
When REQUIRE_AUTH_HEADER=true, the server will only accept requests with valid Authorization headers.
Claude Desktop Integration
To use this MCP server with Claude Desktop, you need to configure it in your Claude Desktop settings.
Installation
First, install the package globally using UV:
uv tool install pingera-mcp-server
Configuration
Open the Claude Desktop configuration file:
- macOS:
~/Library/Application Support/Claude/claude_desktop_config.json
- Windows:
%APPDATA%/Claude/claude_desktop_config.json
Add the following configuration:
{
"mcpServers": {
"pingera": {
"command": "uv",
"args": [
"run",
"--with",
"pingera-mcp-server",
"--python",
"3.10",
"python",
"-m",
"pingera_mcp"
],
"env": {
"PINGERA_API_KEY": "your_api_key_here",
"PINGERA_MODE": "read_only",
"PINGERA_BASE_URL": "https://api.pingera.ru/v1",
"PINGERA_TIMEOUT": "30",
"PINGERA_MAX_RETRIES": "3",
"PINGERA_DEBUG": "false",
"PINGERA_SERVER_NAME": "Pingera MCP Server"
}
}
}
}
Required Environment Variables
PINGERA_API_KEY - Your Pingera API key (required)
Optional Environment Variables
PINGERA_MODE - Operation mode: read_only (default) or read_write
PINGERA_BASE_URL - API endpoint (default: https://api.pingera.ru/v1)
PINGERA_TIMEOUT - Request timeout in seconds (default: 30)
PINGERA_MAX_RETRIES - Maximum retry attempts (default: 3)
PINGERA_DEBUG - Enable debug logging (default: false)
PINGERA_SERVER_NAME - Server display name (default: Pingera MCP Server)
Restart Claude Desktop
After updating the configuration file, restart Claude Desktop to load the new MCP server. You should now be able to access your Pingera monitoring data directly through Claude's interface.
Verify Installation
Once configured, you can ask Claude to:
- "What are my status pages and their names?"
- "Show details of a page with id ..."
- "When was the last failed check for check ..."
- "Run a simple synthetic check for the website with URL https://"
Configuration
Configure the server using environment variables:
PINGERA_API_KEY=your_api_key_here
PINGERA_JWT_TOKEN=your_jwt_token_here
PINGERA_TRANSPORT_MODE=stdio
PINGERA_HTTP_HOST=0.0.0.0
PINGERA_HTTP_PORT=5000
PINGERA_REQUIRE_AUTH_HEADER=false
PINGERA_MODE=read_only
PINGERA_BASE_URL=https://api.pingera.ru/v1
PINGERA_TIMEOUT=30
PINGERA_MAX_RETRIES=3
PINGERA_DEBUG=false
PINGERA_SERVER_NAME=Pingera MCP Server
MCP Tools
Available tools for AI agents:
Pages Management
list_pages - Get paginated list of monitored pages
- Parameters:
page, per_page, status
get_page_details - Get detailed information about a specific page
Component Management
list_component_groups - List all component groups for monitoring organization
get_component_details - Get detailed information about a specific component
Monitoring Checks
list_checks - List all monitoring checks (HTTP, TCP, ping, etc.)
- Parameters:
page, page_size, status, check_type
get_check_details - Get detailed information about a specific check
Alert Rules
list_alert_rules - List all alert rules and their trigger conditions
Heartbeat Monitoring
list_heartbeats - List all heartbeat monitors for cron jobs and scheduled tasks
- Parameters:
page, page_size, status
Incident Management
list_incidents - List all incidents and their current status
- Parameters:
page, page_size, status
Connection Testing
test_pingera_connection - Test API connectivity
Write Operations
Available only in read-write mode (PINGERA_MODE=read_write):
Pages Management
create_page - Create a new status page
- Parameters:
name (required), subdomain, domain, url, language
update_page - Update existing status page configuration
- Parameters:
page_id (required), name, subdomain, domain, url, language, additional kwargs
patch_page - Partially update specific page fields
- Parameters:
page_id (required), kwargs for specific fields
delete_page - Permanently delete a status page
- Parameters:
page_id (required)
Component Management
create_component - Create new component or component group
- Parameters:
page_id (required), name (required), description, group, group_id, only_show_if_degraded, position, showcase, status
update_component - Update existing component configuration
- Parameters:
page_id (required), component_id (required), name, description, group, group_id, only_show_if_degraded, position, showcase, status, additional kwargs
patch_component - Partially update specific component fields
- Parameters:
page_id (required), component_id (required), kwargs for specific fields
delete_component - Delete a component permanently
- Parameters:
page_id (required), component_id (required)
Monitoring Checks
create_check - Create new monitoring check
- Parameters:
check_data (dict with check configuration)
update_check - Update existing monitoring check
- Parameters:
check_id (required), check_data (dict with updated configuration)
delete_check - Delete monitoring check permanently
- Parameters:
check_id (required)
pause_check - Temporarily pause monitoring check
- Parameters:
check_id (required)
resume_check - Resume paused monitoring check
- Parameters:
check_id (required)
Alert Rules
create_alert - Create new alert rule
- Parameters:
alert_data (dict with alert configuration)
update_alert - Update existing alert rule
- Parameters:
alert_id (required), alert_data (dict with updated configuration)
delete_alert - Delete alert rule permanently
- Parameters:
alert_id (required)
Heartbeat Management
create_heartbeat - Create new heartbeat monitor
- Parameters:
heartbeat_data (dict with heartbeat configuration)
update_heartbeat - Update existing heartbeat monitor
- Parameters:
heartbeat_id (required), heartbeat_data (dict with updated configuration)
delete_heartbeat - Delete heartbeat monitor permanently
- Parameters:
heartbeat_id (required)
send_heartbeat_ping - Manually send ping to heartbeat
- Parameters:
heartbeat_id (required)
Incident Management
create_incident - Create new incident on status page
- Parameters:
page_id (required), incident_data (dict with incident details)
update_incident - Update existing incident details
- Parameters:
page_id (required), incident_id (required), incident_data (dict with updated details)
delete_incident - Delete incident permanently
- Parameters:
page_id (required), incident_id (required)
add_incident_update - Add status update to incident
- Parameters:
page_id (required), incident_id (required), update_data (dict with update details)
update_incident_update - Edit existing incident update
- Parameters:
page_id (required), incident_id (required), update_id (required), update_data (dict with updated content)
delete_incident_update - Delete specific incident update
- Parameters:
page_id (required), incident_id (required), update_id (required)
Access Control Modes
The server supports two levels of access control:
Read-Only Mode (Default)
- Access monitoring data
- View status pages and their configurations
- Test API connectivity
- No modification capabilities
Read-Write Mode
- All read-only features
- Create, update and delete resources: status pages, checks, alerts, heartbeats
- Execute checks and get their results
- Manage incidents and notifications
Set PINGERA_MODE=read_write to enable write operations.
Note: Access control mode is independent of transport mode. You can run the server in read-write mode with either stdio or SSE transport.
Architecture
Pingera API Client Library
Located in pingera/, this modular library provides:
- PingeraClient: Main API client with authentication and error handling
- Models: Pydantic data models for type-safe API responses
- Exceptions: Custom exception hierarchy for error handling
MCP Server Implementation
- FastMCP Framework: Modern MCP server implementation
- Resource Management: Structured access to monitoring data
- Tool Registration: Executable operations for AI agents
- Configuration: Environment-based settings management
Testing
Running the Test Suite
Run all tests:
uv run pytest
Run tests with verbose output:
uv run pytest -v
Run specific test files:
uv run pytest tests/test_models.py
uv run pytest tests/test_config.py
uv run pytest tests/test_mcp_server.py
Run tests with coverage:
uv run pytest --cov=pingera --cov=config --cov=mcp_server
Test Structure
The test suite includes:
- Unit Tests: Testing individual components (models, config, client)
- Integration Tests: Testing MCP server functionality
- Mock Tests: Testing with simulated API responses
Testing with MCP Inspector
The MCP Inspector is an official debugging tool that provides a web interface to test MCP servers interactively. It allows you to explore available resources, execute tools, and inspect the server's responses in real-time.
Setup Inspector
- Create an
mcp.json configuration file:
{
"mcpServers": {
"pingera": {
"command": "uv",
"args": [
"run",
"--with",
"pingera-mcp-server",
"--python",
"3.10",
"python",
"-m",
"pingera_mcp"
],
"env": {
"PINGERA_API_KEY": "your_pingera_api_key",
"PINGERA_MODE": "read_only",
"PINGERA_BASE_URL": "https://api.pingera.ru/v1",
"PINGERA_TIMEOUT": "30",
"PINGERA_MAX_RETRIES": "3",
"PINGERA_DEBUG": "false"
}
}
}
}
npx @modelcontextprotocol/inspector --config mcp.json
- Open your browser to the provided URL (typically
http://localhost:6274)
Using Inspector
The inspector provides:
- Resources Tab: Browse available monitoring data resources
- Tools Tab: Execute MCP tools like
list_pages, get_page_details, etc.
- Logs Tab: View detailed communication logs between the inspector and server
- Interactive Testing: Test tool parameters and see real-time responses
This is the recommended way to test your MCP server integration before deploying with Claude Desktop or other MCP clients.
Manual Testing with mcp_client.py
mcp_client.py uses Gemini models and integrates with the MCP server to execute various tools. It is just an example and can be easly modified to use any other Large Language Model.
python mcp_client.py "Show me my status pages"
Error Handling
The system includes comprehensive error handling:
PingeraError: Base exception for all client errors
PingeraAPIError: API response errors with status codes
PingeraAuthError: Authentication failures
PingeraConnectionError: Network connectivity issues
PingeraTimeoutError: Request timeout handling