Can my agent search for specific dashboards in my Grafana instance?

Yes. Use the 'search_dashboards' tool. You can provide an optional query string to match titles or tags. The agent will return basic info including the unique UID required for deeper inspection.

How do I extract the PromQL or SQL queries from a dashboard panel via chat?

Use the 'get_dashboard' tool with the dashboard UID. Your agent will retrieve the full JSON configuration, including all panels and their underlying data queries, enabling you to review the exact metrics logic natively.

Can I see firing alerts through the agent?

Absolutely. Use the 'list_alerts' tool. The agent retrieves all configured alert rules and their current statuses, allowing you to identify which monitors are currently in a firing state synchronousy.

Grafana MCP Server for CrewAI 4 tools — connect in under 2 minutes

Name: Grafana
Availability: InStock
Author: Vinkius

docs.crewai.com/mcp/overview

Built by Vinkius GDPR 4 Tools Framework

Connect your CrewAI agents to Grafana through the Vinkius — pass the Edge URL in the `mcps` parameter and every Grafana tool is auto-discovered at runtime. No credentials to manage, no infrastructure to maintain.

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

from crewai import Agent, Task, Crew

agent = Agent(
    role="Grafana Specialist",
    goal="Help users interact with Grafana effectively",
    backstory=(
        "You are an expert at leveraging Grafana tools "
        "for automation and data analysis."
    ),
    # Your Vinkius token — get it at cloud.vinkius.com
    mcps=["https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"],
)

task = Task(
    description=(
        "Explore all available tools in Grafana "
        "and summarize their capabilities."
    ),
    agent=agent,
    expected_output=(
        "A detailed summary of 4 available tools "
        "and what they can do."
    ),
)

crew = Crew(agents=[agent], tasks=[task])
result = crew.kickoff()
print(result)

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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 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.

When paired with CrewAI, Grafana becomes a first-class tool in your multi-agent workflows. Each agent in the crew can call Grafana tools autonomously — one agent queries data, another analyzes results, a third compiles reports — all orchestrated through the Vinkius with zero configuration overhead.

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 CrewAI 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 CrewAI via MCP

Follow these steps to integrate the Grafana MCP Server with CrewAI.

Install CrewAI

Run pip install crewai

Replace the token

Replace [YOUR_TOKEN_HERE] with your Vinkius token from cloud.vinkius.com

Customize the agent

Adjust the role, goal, and backstory to fit your use case

Run the crew

Run python crew.py — CrewAI auto-discovers 4 tools from Grafana

Why Use CrewAI with the Grafana MCP Server

CrewAI Multi-Agent Orchestration Framework provides unique advantages when paired with Grafana through the Model Context Protocol.

Multi-agent collaboration lets you decompose complex workflows into specialized roles — one agent researches, another analyzes, a third generates reports — each with access to MCP tools

CrewAI's native MCP integration requires zero adapter code: pass the Vinkius Edge URL directly in the `mcps` parameter and agents auto-discover every available tool at runtime

Built-in task delegation and shared memory mean agents can pass context between steps without manual state management, enabling multi-hop reasoning across tool calls

Sequential and hierarchical crew patterns map naturally to real-world workflows: enumerate subdomains → analyze DNS history → check WHOIS records → compile findings into actionable reports

Grafana + CrewAI Use Cases

Practical scenarios where CrewAI combined with the Grafana MCP Server delivers measurable value.

Automated multi-step research: a reconnaissance agent queries Grafana for raw data, then a second analyst agent cross-references findings and flags anomalies — all without human handoff

Scheduled intelligence reports: set up a crew that periodically queries Grafana, analyzes trends over time, and generates executive briefings in markdown or PDF format

Multi-source enrichment pipelines: chain Grafana tools with other MCP servers in the same crew, letting agents correlate data across multiple providers in a single workflow

Compliance and audit automation: a compliance agent queries Grafana against predefined policy rules, generates deviation reports, and routes findings to the appropriate team

Grafana MCP Tools for CrewAI (4)

These 4 tools become available when you connect Grafana to CrewAI 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 CrewAI

Ready-to-use prompts you can give your CrewAI 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 CrewAI

Common issues when connecting Grafana to CrewAI through the Vinkius, and how to resolve them.

MCP tools not discovered

Ensure the Edge URL is correct. CrewAI connects lazily when the crew starts — check console output.

Agent not using tools

Make the task description specific. Instead of "do something", say "Use the available tools to list contacts".

Timeout errors

CrewAI has a 10s connection timeout by default. Ensure your network can reach the Edge URL.

Rate limiting or 429 errors

The Vinkius enforces per-token rate limits. Check your subscription tier and request quota in the dashboard. Upgrade if you need higher throughput.

Grafana + CrewAI FAQ

Common questions about integrating Grafana MCP Server with CrewAI.

How does CrewAI discover and connect to MCP tools?

CrewAI connects to MCP servers lazily — when the crew starts, each agent resolves its MCP URLs and fetches the tool catalog via the standard tools/list method. This means tools are always fresh and reflect the server's current capabilities. No tool schemas need to be hardcoded.

Can different agents in the same crew use different MCP servers?

Yes. Each agent has its own mcps list, so you can assign specific servers to specific roles. For example, a reconnaissance agent might use a domain intelligence server while an analysis agent uses a vulnerability database server.

What happens when an MCP tool call fails during a crew run?

CrewAI wraps tool failures as context for the agent. The LLM receives the error message and can decide to retry with different parameters, fall back to a different tool, or mark the task as partially complete. This resilience is critical for production workflows.

Can CrewAI agents call multiple MCP tools in parallel?

CrewAI agents execute tool calls sequentially within a single reasoning step. However, you can run multiple agents in parallel using process=Process.parallel, each calling different MCP tools concurrently. This is ideal for workflows where separate data sources need to be queried simultaneously.

Can I run CrewAI crews on a schedule (cron)?

Yes. CrewAI crews are standard Python scripts, so you can invoke them via cron, Airflow, Celery, or any task scheduler. The crew.kickoff() method runs synchronously by default, making it straightforward to integrate into existing pipelines.