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Pingera MCP Server

@pingera

Repository

Basic information

Category

Other

Transports

stdio

Author

pingera

Submitted by

Sergey Pronin

About Pingera MCP Server

An MCP server for Pingera monitoring platform. Geo-distributed monitoring, playwright scripts execution, status pages.

#mcp#monitoring#playwright#statuspages

Pingera MCP Server config

Add this server to your MCP-compatible client using the configuration below.

{
  "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"
      }
    }
  }
}

Pingera MCP Server tools

Tool list not available yet

This listing does not currently have a tool list to display. This does not mean the server has no tools; check its documentation for supported capabilities.

We auto-extract tools from the README. The maintainer can list them under a ## Tools heading to populate this section.

Overview

What is Pingera Mcp?

Pingera Mcp is a Model Context Protocol (MCP) server that integrates AI models with the Pingera monitoring service, enabling agents to access and manage monitoring data through a structured API.

How to use Pingera Mcp?

Install the package globally using UV (uv tool install pingera-mcp-server), then configure the Claude Desktop settings with the required PINGERA_API_KEY environment variable. Run the server with python main.py or use the Claude Desktop integration. The server starts in read‑only mode by default; set PINGERA_MODE=read_write to enable write operations.

Key features of Pingera Mcp

  • Modular Pingera API client library with clean abstractions
  • Read‑only and read‑write operation modes
  • MCP tools for pages, components, checks, alerts, heartbeats, incidents
  • Robust error handling with custom exception hierarchy
  • Real‑time data via Pingera API v1
  • Pydantic models for type‑safe data validation
  • Environment‑based configuration management

Use cases of Pingera Mcp

  • List monitored status pages and view their details
  • Retrieve and analyze monitoring check results
  • Manage components and component groups on a status page
  • Create, update, and delete incidents with status updates (in read‑write mode)
  • Test API connectivity from an AI agent

Frequently asked questions

1

What dependencies does Pingera Mcp require?

Python 3.10 or later, the UV package manager, and a valid Pingera API key.

2

How do I switch between read‑only and read‑write mode?

Set the environment variable `PINGERA_MODE` to `read_only` (default) or `read_write`. In read‑write mode, the server also provides tools for creating, updating, and deleting resources.

3

Which MCP tools are always available?

The server always exposes tools for reading data: `list_pages`, `get_page_details`, `list_component_groups`, `get_component_details`, `list_checks`, `get_check_details`, `list_alert_rules`, `list_heartbeats`, `list_incidents`, and `test_pingera_connection`.

4

Where is the monitoring data stored?

All data is stored on the Pingera servers and accessed live via the Pingera API v1. No local persistence is performed by the MCP server.

5

How is authentication handled?

Authentication requires a `PINGERA_API_KEY` environment variable. The key is passed to the Pingera client for all API requests.

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