Grafana Loki MCP Server

Overview

The Grafana‑Loki MCP server bridges the gap between AI assistants and Loki log data by exposing a lightweight, FastMCP‑based interface that talks to Grafana’s API. Developers can therefore embed powerful log querying and analysis capabilities directly into conversational agents, enabling real‑time debugging, monitoring, or incident response without leaving the AI workflow.

At its core, the server provides a set of tools that mirror common Loki operations:

• lets an assistant retrieve log streams using a standard Loki query string, time range, and pagination options.
• returns all label names available in the Loki instance, which is useful for building dynamic query builders or auto‑completion features.
• fetches the distinct values for a chosen label, enabling AI‑guided filtering of logs.
• transforms raw query output into human‑readable formats such as plain text, JSON, or markdown, allowing the assistant to present logs in a conversationally appropriate style.

The server supports both stdio and SSE (Server‑Sent Events) transports, giving developers flexibility to choose between synchronous command‑line style interactions or real‑time streaming of log data. This dual transport model is particularly valuable for building AI tools that need to surface live logs during an incident or provide a continuous log feed while the user is troubleshooting.

Typical use cases include:

• Live debugging: An AI assistant can query the latest error logs from a microservice and suggest configuration changes or code fixes.
• Incident triage: During an outage, the assistant pulls relevant logs across multiple applications and aggregates them into a markdown report that can be shared with on‑call engineers.
• Monitoring dashboards: The assistant can surface log trends or alert conditions directly in a chat interface, allowing developers to keep an eye on production health without switching tools.

Because the server communicates purely over HTTP/HTTPS via Grafana’s existing API, it inherits Grafana’s robust authentication and permission model. Developers can secure the MCP endpoint with an API key that scopes only the necessary read access, ensuring that log data remains protected while still being easily accessible to AI workflows.

Overall, the Grafana‑Loki MCP server turns a complex log querying backend into a simple, AI‑friendly API. It empowers developers to build conversational tools that can ask for logs, filter them, and present the results in a format that feels natural within the chat, thereby accelerating debugging cycles and improving operational visibility.