Incident.io MCP Server for LangChain 10 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Incident.io 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({
"incidentio": {
"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 Incident.io, 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 Incident.io MCP Server
Empower your AI agents to manage your incident response lifecycle with Incident.io. This MCP server allows you to list and retrieve incidents, manage roles and types, track custom fields, and view on-call schedules directly through the Incident.io API. Ideal for automating SRE workflows and incident coordination.
LangChain's ecosystem of 500+ components combines seamlessly with Incident.io 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.
The Incident.io 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 Incident.io to LangChain via MCP
Follow these steps to integrate the Incident.io 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 Incident.io via MCP
Why Use LangChain with the Incident.io MCP Server
LangChain provides unique advantages when paired with Incident.io through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents. combine Incident.io 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 Incident.io queries for multi-turn workflows
Incident.io + LangChain Use Cases
Practical scenarios where LangChain combined with the Incident.io MCP Server delivers measurable value.
RAG with live data: combine Incident.io tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Incident.io, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Incident.io tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Incident.io tool call, measure latency, and optimize your agent's performance
Incident.io MCP Tools for LangChain (10)
These 10 tools become available when you connect Incident.io to LangChain via MCP:
get_incident
Retrieves details for a specific incident
list_catalog_types
Lists all defined catalog types
list_custom_fields
Lists all defined custom fields
list_incident_roles
Lists all defined incident roles
list_incident_types
Lists all defined incident types
list_incidents
Lists all incidents
list_schedules
Lists all on-call schedules
list_severities
Lists all defined incident severities
list_teams
Lists all teams
list_users
Lists all users
Example Prompts for Incident.io in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Incident.io immediately.
"List all ongoing incidents in Incident.io."
"Show me the on-call schedules for this week."
"Check the details for incident ID 'abc-123'."
Troubleshooting Incident.io MCP Server with LangChain
Common issues when connecting Incident.io to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersIncident.io + LangChain FAQ
Common questions about integrating Incident.io 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 Incident.io 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 Incident.io to LangChain
Get your token, paste the configuration, and start using 10 tools in under 2 minutes. No API key management needed.