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One MCP connection. Full Grafana context. No more tab-switching — just ask.
Stop hunting through dashboards and panel configurations. Ask your AI agent for metric values, alert states, dashboard summaries, and anomaly explanations — across all your Grafana data sources at once.
Your AI agent reads harmonized data across 500+ platforms. "Cost" in Google Ads and "spend" in Meta Ads resolve to the same field automatically.
Create dashboards, configure alert rules, update panel queries, and manage annotations — through natural language. Skip the JSON editor and panel configuration UI.
250+ governance rules enforce naming conventions, budget limits, and KPI thresholds. SOC 2 Type II certified.
Go beyond static alert thresholds. Let your AI agent correlate metrics across dashboards, detect multi-signal anomalies, and explain what a spike actually means in context — before it becomes an incident.
Automated weekly reports, anomaly flagging, and budget alerts — all from a single conversation. No more morning check-ins across 5 dashboards.
Create dashboards, configure alert rules, update panel queries, and manage annotations — through natural language. Skip the JSON editor and panel configuration UI.
Every phase runs through the same MCP connection. One protocol, all platforms, full governance. No switching between tools.
When something goes wrong, Grafana fires dozens of correlated alerts simultaneously. The on-call engineer receives a wall of notifications, all pointing at symptoms rather than root cause. Identifying which single failure is causing the cascade requires manually opening 8 dashboards and correlating timelines.
Your AI agent correlates all firing alerts in a single query, identifies the earliest anomaly in the causal chain, and proposes the root cause — presenting a prioritized triage summary instead of a list of symptoms.
Engineering teams create dashboards organically over time. A mature Grafana instance has hundreds of dashboards, many with overlapping metrics, inconsistent naming, and abandoned panels. Finding the one dashboard that shows the specific metric you need — and trusting it's current — can take longer than the investigation itself.
Ask your AI agent to search across all Grafana dashboards for panels matching a metric name, service, or label. It surfaces the relevant panel with its current value and data source, regardless of which dashboard it lives in or how it was named.
After an incident, the post-mortem requires reconstructing exactly what happened and when — which metric spiked, which alert fired, which deploy preceded the anomaly. This means scrubbing through multiple dashboards with time range selectors, exporting data points, and stitching together a narrative manually.
Your AI agent pulls metric data, alert history, and deployment annotations from across Grafana into a single chronological timeline. Ask for an incident reconstruction and receive a ready-to-paste narrative with timestamps and metric values.
Same MCP connection, different workflows for every team member. Agency CEOs get portfolio health. Media Strategists get campaign QA. Analysts get cross-platform reports. Account Managers get auto-generated QBR decks. Creative Directors get performance-based briefs.
Each role asks in natural language. The MCP server handles the complexity — rate limits, auth, schema normalization, governance — behind the scenes.
Grafana MCP is a Model Context Protocol server that gives AI agents like Claude, ChatGPT, and Gemini direct access to your Grafana dashboards, metrics, alerts, and data source queries. You can query infrastructure metrics, investigate anomalies, configure alerts, and create dashboards — all in natural language.
Dashboards and panel configurations, live metric data from any connected data source (Prometheus, InfluxDB, Loki, Tempo, and others), alert rules and current alert states, annotations, data source metadata, and folder structures. The AI agent can execute metric queries, read alert history, and surface any data that Grafana itself can display.
Yes. Write operations include creating and updating dashboards, adding or modifying panels, changing alert thresholds, creating annotations, and updating data source configurations. All changes are versioned in Grafana's history and can be rolled back.
Both. Point the MCP server at your Grafana instance URL during setup. Works with Grafana OSS, Grafana Enterprise, and Grafana Cloud. Any Grafana version supporting the HTTP API (v6+) is compatible.
Yes. The MCP server can execute queries against any data source connected to your Grafana instance — Prometheus, Loki, InfluxDB, Elasticsearch, and others — using the same query language each data source supports. You do not need to configure separate connections for each data source.
Yes. Improvado stores all service account tokens in an encrypted vault (SOC 2 Type II certified). Your AI agent never has direct access to credentials — requests go through Improvado's secure proxy. Access is scoped to the permissions granted to the service account you configure during setup.
Connect your data to an AI agent in under 60 seconds. The closed loop starts with one conversation.
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