Grafana MCP Server for LangChain 4 tools — connect in under 2 minutes
LangChain is the leading Python framework for composable LLM applications. Connect Grafana through the Vinkius and LangChain agents can call every tool natively — combine them with retrievers, memory, and output parsers for sophisticated AI pipelines.
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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({
"grafana": {
"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 Grafana, 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 Grafana MCP Server
Connect your Grafana instance to any AI agent and take full control of your application observability, dashboard inspections, and alerting workflows through natural conversation.
LangChain's ecosystem of 500+ components combines seamlessly with Grafana through native MCP adapters. Connect 4 tools via the 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
- Dashboard Discovery Orchestration — Search for Grafana dashboards by title or tag to retrieve unique UIDs and metadata natively within your chat
- Panel & Query Inspection — Retrieve the full configuration of any dashboard by UID, extracting precise PromQL, LogQL, or SQL queries and panel layouts flawlessly
- Data Source Auditing — List all configured data sources including Prometheus, Loki, CloudWatch, and SQL databases to verify connectivity boundaries securely
- Alert Monitoring Oversight — Enumerate active alert rules and retrieve current firing states to monitor system health and resolve incidents synchronously
- Observability Navigation — Analyze specific localized variables decoding active monitoring routes and extracting structural constraints from your Grafana environment
- SRE Command Center — Verify dashboard UIDs and retrieve query strings to debug performance regressions or analyze log patterns using natural language
The Grafana MCP Server exposes 4 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 Grafana to LangChain via MCP
Follow these steps to integrate the Grafana 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 4 tools from Grafana via MCP
Why Use LangChain with the Grafana MCP Server
LangChain provides unique advantages when paired with Grafana through the Model Context Protocol.
The largest ecosystem of integrations, chains, and agents — combine Grafana 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 Grafana queries for multi-turn workflows
Grafana + LangChain Use Cases
Practical scenarios where LangChain combined with the Grafana MCP Server delivers measurable value.
RAG with live data: combine Grafana tool results with vector store retrievals for answers grounded in both real-time and historical data
Autonomous research agents: LangChain agents query Grafana, synthesize findings, and generate comprehensive research reports
Multi-tool orchestration: chain Grafana tools with web scrapers, databases, and calculators in a single agent run
Production monitoring: use LangSmith to trace every Grafana tool call, measure latency, and optimize your agent's performance
Grafana MCP Tools for LangChain (4)
These 4 tools become available when you connect Grafana to LangChain via MCP:
firing_alerts
Returns alerting rules that are currently in "firing" state, including their labels and annotations. Get currently firing alerts from Grafana Unified Alerting
get_dashboard
Requires the dashboard UID, which you can get from search_dashboards. Get full dashboard configuration including panels and queries
list_datasources
) are available in this Grafana instance. List all configured data sources in Grafana
search_dashboards
Returns basic info including the UID. To inspect the panels and queries of a dashboard, use get_dashboard with the uid. Search Grafana dashboards by title or tag
Example Prompts for Grafana in LangChain
Ready-to-use prompts you can give your LangChain agent to start working with Grafana immediately.
"Search for dashboards tagged with 'production'"
"Show me the queries for dashboard 'abc-123'"
"Are there any firing alerts right now?"
Troubleshooting Grafana MCP Server with LangChain
Common issues when connecting Grafana to LangChain through the Vinkius, and how to resolve them.
MultiServerMCPClient not found
pip install langchain-mcp-adaptersGrafana + LangChain FAQ
Common questions about integrating Grafana 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 Grafana 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 Grafana to LangChain
Get your token, paste the configuration, and start using 4 tools in under 2 minutes. No API key management needed.