Can I trigger an API check manually through the agent?

Yes! Use the `trigger_check_run` tool with the unique check ID. The agent will instruct Checkly to run the test immediately from its global network.

How do I see the performance metrics for my homepage check?

Use the `get_check_performance_metrics` tool with the check ID. Your agent will fetch detailed analytics including success rates and response time percentiles.

Where do I find my Checkly API Key and Account ID?

Log in to your Checkly account and navigate to **User Settings -> API Keys** for the key. The **Account ID** can be found in the **Account Settings** section.

Checkly MCP Server for LangChain 8 tools — connect in under 2 minutes

Name: Checkly
Availability: InStock
Author: Vinkius

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

Built by Vinkius GDPR 8 Tools Framework

LangChain is the leading Python framework for composable LLM applications. Connect Checkly 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({
        "checkly": {
            "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 Checkly, show me what tools are available.",
            }]
        })
        print(response["messages"][-1].content)

asyncio.run(main())

Fully ManagedVinkius Servers

60%Token savings

High SecurityEnterprise-grade

IAMAccess control

EU AI ActCompliant

DLPData protection

V8 IsolateSandboxed

Ed25519Audit chain

<40msKill switch

Stream every event to Splunk, Datadog, or your own webhook in real-time

* 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 Checkly MCP Server

Connect your Checkly account to any AI agent and take full control of your application monitoring and synthetic testing through natural conversation. Streamline how you ensure the uptime and performance of your APIs and web apps.

LangChain's ecosystem of 500+ components combines seamlessly with Checkly through native MCP adapters. Connect 8 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

Check Oversight — List and retrieve details for all API and Browser monitors natively
Live Execution — Manually trigger check runs to verify system health on-demand flawlessly
Performance Intelligence — Access detailed performance metrics and response times for any monitor securely
Alert Management — List and audit all configured alert channels (Slack, Email, PagerDuty) flawlessly
Reliability Tracking — Monitor heartbeat and cron jobs to ensure your background tasks are running flawlessly
System Metadata — Retrieve core account information and organizational structures directly within your workspace

The Checkly MCP Server exposes 8 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 Checkly to LangChain via MCP

Follow these steps to integrate the Checkly 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 8 tools from Checkly via MCP

Why Use LangChain with the Checkly MCP Server

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

The largest ecosystem of integrations, chains, and agents. combine Checkly 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 Checkly queries for multi-turn workflows

Checkly + LangChain Use Cases

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

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

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

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

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

Checkly MCP Tools for LangChain (8)

These 8 tools become available when you connect Checkly to LangChain via MCP:

get_check_details

Get detailed information for a specific check

get_check_performance_metrics

Retrieve performance metrics for a specific check

get_checkly_account_info

Retrieve core account and organization metadata

list_check_groups

List groups of checks

list_checkly_alert_channels

List all configured alert channels (Slack, Email, PagerDuty, etc)

list_checkly_checks

List all API and Browser checks

list_checkly_heartbeats

List all heartbeat (cron) monitors

trigger_check_run

Manually trigger a check to run immediately

Example Prompts for Checkly in LangChain

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

"List all my monitors in Checkly and their last status."

"Show me the response time graph for the 'Checkout Flow' check."

"Check the status of my heartbeat monitors."

Troubleshooting Checkly MCP Server with LangChain

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

MultiServerMCPClient not found

Install: pip install langchain-mcp-adapters

Checkly + LangChain FAQ

Common questions about integrating Checkly 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.