grafana-mcp-observability
Enables AI agents to query Grafana dashboards, alerts, and datasources for observability insights and incident investigation.
README
grafana-mcp-observability
MCP server for Grafana — query dashboards, alerts, and datasources via AI agents.
What is this?
grafana-mcp-observability is an MCP (Model Context Protocol) server that exposes Grafana's observability stack to AI agents. It enables AI-driven incident investigation, alert triage, and dashboard querying — without requiring manual Grafana access.
Built for platform engineers who run Grafana with Prometheus, Loki, or Tempo as their observability backend.
Available Tools
| Tool | Description |
|---|---|
list_dashboards |
List all Grafana dashboards by folder |
get_dashboard |
Fetch a dashboard's panel definitions and queries |
query_datasource |
Run a PromQL or LogQL query against a datasource |
list_alerts |
List active and pending alert rules |
get_alert_details |
Get labels, annotations, and state for a specific alert |
list_datasources |
List configured datasources (Prometheus, Loki, Tempo, etc.) |
get_annotations |
Fetch deployment or event annotations from dashboards |
Quick Start
Prerequisites
- Python 3.11+
- Grafana instance with API access
- Grafana Service Account token with
Viewerrole
Installation
git clone https://github.com/akkireddy-challa/grafana-mcp-observability
cd grafana-mcp-observability
pip install -r requirements.txt
Configuration
export GRAFANA_URL=https://grafana.example.com
export GRAFANA_TOKEN=<service-account-token>
Run
python server.py
MCP Client Config (Claude Desktop)
{
"mcpServers": {
"grafana": {
"command": "python",
"args": ["/path/to/grafana-mcp-observability/server.py"],
"env": {
"GRAFANA_URL": "https://grafana.example.com",
"GRAFANA_TOKEN": "<your-token>"
}
}
}
}
Security Model
- Uses Grafana Service Account tokens — not user credentials
- Token requires
Viewerrole only — no write access needed - No dashboard modifications or alert rule changes are possible
- All queries are read-only
- Token stored in environment variables, never in code
Use Cases at Telia
This pattern is used to allow AI agents to:
- Investigate active alerts by querying Prometheus metrics in context
- Correlate Loki log spikes with Grafana annotation events (deployments)
- Summarize dashboard panel state for on-call briefings
- Detect anomalous query patterns across multi-tenant Grafana orgs
Roadmap
- [ ]
get_traces— query Tempo distributed traces - [ ]
create_annotation— mark AI-driven investigation events - [ ]
silence_alert— create Alertmanager silences via MCP - [ ] Multi-org Grafana support
- [ ] GitHub Actions workflow for CI validation
Related Projects
| Repo | Purpose |
|---|---|
| k8s-mcp-server | Kubernetes cluster diagnostics via MCP |
| azure-mcp-platform | Azure resource management via MCP |
| phoenix-mcp-eval | LLM tracing and evaluation via MCP |
License
MIT License. See LICENSE for details.
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