Better Stack MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Better Stack through Vinkius and LangChain agents can call every tool natively. combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
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({
"better-stack-1": {
"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 Better Stack, show me what tools are available.",
}]
})
print(response["messages"][-1].content)
asyncio.run(main())
* 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 Better Stack MCP Server
Connect your Better Stack (Better Uptime) account to any AI agent and empower it to act as your Level 1 Site Reliability Engineer (SRE). Let your AI diagnose incidents, manage escalations, and audit monitoring configs securely via conversation.
LangChain's ecosystem of 500+ components combines seamlessly with Better Stack 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
- Incident Response — Rapidly list firing incidents, inspect technical downtime payloads, acknowledge alerts, and force resolve states inline
- Uptime Monitors — Fetch exact definitions of active HTTP endpoint pings, DNS probes, and latency constraints across your fleet
- Cron Heartbeats — Investigate passive tracking endpoints validating background workers and server limits
- On-Call Management — Expose active shifts and team schedules to determine explicitly who is getting paged in real-time
- Status Pages — Read configured public dashboards tracking your global infrastructure
The Better Stack 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 Better Stack to LangChain via MCP
Follow these steps to integrate the Better Stack 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 Better Stack via MCP
Why Use LangChain with the Better Stack MCP Server
LangChain provides unique advantages when paired with Better Stack through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Better Stack 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 Better Stack queries for multi-turn workflows
Better Stack + LangChain Use Cases
Practical scenarios where LangChain combined with the Better Stack MCP Server delivers measurable value.
RAG with live data: combine Better Stack tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Better Stack, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Better Stack tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Better Stack tool call, measure latency, and optimize your agent's performance
Better Stack MCP Tools for LangChain (10)
These 10 tools become available when you connect Better Stack to LangChain via MCP:
acknowledge_incident
Acknowledge an ongoing explicit incident halting paging
get_heartbeat
Get explicit details of a passive heartbeat node
get_incident
Retrieve the native timeline payload of an explicit incident
get_monitor
Get full details of a specific Better Stack monitor
list_heartbeats
List all configured cron heartbeats securely
list_incidents
List all explicit incidents on Better Stack
list_monitors
List all monitors on Better Stack (Better Uptime)
list_on_call
List exact On-Call routing calendars
list_status_pages
List all explicit Status Pages
resolve_incident
Force resolve a specific incident
Example Prompts for Better Stack in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Better Stack immediately.
"List any active unresolved incidents going on right now."
"Who is currently on-call for the main engineering shift?"
"Check the detailed root cause of passed Incident #8012."
Troubleshooting Better Stack MCP Server with LangChain
Common issues when connecting Better Stack to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersBetter Stack + LangChain FAQ
Common questions about integrating Better Stack MCP Server with LangChain.
How does LangChain connect to MCP servers?
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?
Can I trace MCP tool calls in LangSmith?
Connect Better Stack with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Better Stack to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.