How do I create a Pingdom API Token?

In your Pingdom dashboard (or SolarWinds portal), go to **Settings** > **API Tokens**. Click **Add API Token**, give it a name, and ensure it has the necessary access levels.

Can I see response times for different global regions?

Yes! The `list_check_results` tool returns data from multiple probe locations, allowing you to see how your site performs from different parts of the world.

Does this support pausing multiple checks at once?

The tools handle checks individually, but you can ask the AI agent to 'Pause all checks related to our API' and it will process them sequentially using their IDs.

Pingdom MCP Server for LangChain 10 tools — connect in under 2 minutes

Name: Pingdom
Availability: InStock
Author: Vinkius

python.langchain.com/docs/integrations/tools/mcp

Built by Vinkius GDPR 10 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Pingdom through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.

Get MCP Server for AI Agents

ASK AI ABOUT THIS MCP SERVER

Open in ChatGPT Open in Claude Open in Perplexity

Vinkius supports streamable HTTP and SSE.

python

import asyncio
from langchain_mcp_adapters.client import MultiServerMCPClient
from langchain_openai import ChatOpenAI
from langgraph.prebuilt import create_react_agent

async def main():
    # Your Vinkius token. get it at cloud.vinkius.com
    async with MultiServerMCPClient({
        "pingdom": {
            "transport": "streamable_http",
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
        }
    }) as client:
        tools = client.get_tools()
        agent = create_react_agent(
            ChatOpenAI(model="gpt-4o"),
            tools,
        )
        response = await agent.ainvoke({
            "messages": [{
                "role": "user",
                "content": "Using Pingdom, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

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* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure

About Pingdom MCP Server

Connect your Pingdom account to any AI agent and take full control of your website monitoring and reliability workflows through natural conversation.

LangChain's ecosystem of 500+ components combines seamlessly with Pingdom through native MCP adapters. Connect 10 tools via Vinkius and use ReAct agents, Plan-and-Execute strategies, or custom agent architectures. with LangSmith tracing giving full visibility into every tool call, latency, and token cost.

What you can do

Uptime Visibility — List all monitoring checks and retrieve real-time status (up, down, unconfirmed).
Performance Tracking — Fetch average response times and detailed outage history for any specific check.
Log Auditing — Retrieve raw check results to investigate specific errors or latency spikes.
Global Infrastructure Oversight — List all Pingdom probe locations to understand your monitoring coverage.
Alert Management — List notification contacts and pause or resume checks during maintenance windows.

The Pingdom MCP Server exposes 10 tools through the Vinkius. Connect it to LangChain in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.

How to Connect Pingdom to LangChain via MCP

Follow these steps to integrate the Pingdom MCP Server with LangChain.

Install dependencies

Run pip install langchain langchain-mcp-adapters langgraph langchain-openai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token

Run the agent

Save the code and run python agent.py

Explore tools

The agent discovers 10 tools from Pingdom via MCP

Why Use LangChain with the Pingdom MCP Server

LangChain provides unique advantages when paired with Pingdom through the Model Context Protocol.

The largest ecosystem of integrations, chains, and agents. combine Pingdom MCP tools with 500+ LangChain components

Agent architecture supports ReAct, Plan-and-Execute, and custom strategies with full MCP tool access at every step

LangSmith tracing gives you complete visibility into tool calls, latencies, and token usage for production debugging

Memory and conversation persistence let agents maintain context across Pingdom queries for multi-turn workflows

Pingdom + LangChain Use Cases

Practical scenarios where LangChain combined with the Pingdom MCP Server delivers measurable value.

RAG with live data: combine Pingdom tool results with vector store retrievals for answers grounded in both real-time and historical data

Autonomous research agents: LangChain agents query Pingdom, synthesize findings, and generate comprehensive research reports

Multi-tool orchestration: chain Pingdom tools with web scrapers, databases, and calculators in a single agent run

Production monitoring: use LangSmith to trace every Pingdom tool call, measure latency, and optimize your agent's performance

Pingdom MCP Tools for LangChain (10)

These 10 tools become available when you connect Pingdom to LangChain via MCP:

get_average_response_time

Get average response time for a check

get_check_details

Get details for a specific check

get_check_outages

List outages for a specific check

list_alert_contacts

List alert notification contacts

list_check_results

List individual check results/logs

list_maintenance_windows

List scheduled maintenance windows

list_pingdom_probes

List all Pingdom monitoring locations (probes)

list_uptime_checks

List all Pingdom uptime checks

pause_uptime_check

Pause a specific uptime check

resume_uptime_check

Resume a specific uptime check

Example Prompts for Pingdom in LangChain

Ready-to-use prompts you can give your LangChain agent to start working with Pingdom immediately.

"List all my current uptime checks and their status."

"What was the average response time for the 'Main Site' check (ID: 12345) today?"

"Pause the uptime check for ID 98765 for our scheduled maintenance."

Troubleshooting Pingdom MCP Server with LangChain

Common issues when connecting Pingdom to LangChain through the Vinkius, and how to resolve them.

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Pingdom + LangChain FAQ

Common questions about integrating Pingdom MCP Server with LangChain.

How does LangChain connect to MCP servers?

Use langchain-mcp-adapters to create an MCP client. LangChain discovers all tools and wraps them as native LangChain tools compatible with any agent type.

Which LangChain agent types work with MCP?

All agent types including ReAct, OpenAI Functions, and custom agents work with MCP tools. The tools appear as standard LangChain tools after the adapter wraps them.