MCP Servers for Grafana

Grafana is an open-source analytics and monitoring platform that allows users to query, visualize, and alert on metrics from various data sources. It provides interactive dashboards for time-series data visualization and is widely used for infrastructure monitoring.

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  • Why this server?

    Provides compatibility with Grafana for monitoring the MCP server through Prometheus clients.

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    An MCP server to interact with a Tinybird Workspace from any MCP client.
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    51
    Python
    Apache 2.0
    • Apple
  • Why this server?

    Provides tools for querying Grafana Loki logs using LogQL, accessing label values and metadata, and analyzing log data with support for different output formats and filtering options.

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    An MCP interface that allows AI assistants to query and analyze Grafana Loki logs using LogQL, with support for authentication and various output formats.
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    3
    83
    TypeScript
    MIT License
    • Linux
    • Apple
  • Why this server?

    Provides access to Grafana dashboards, data sources, and ecosystem tools, enabling search and retrieval of dashboards, querying of data sources (Prometheus, Loki), incident management, alerting capabilities, and OnCall functionality.

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    A Model Context Protocol (MCP) server for Grafana. This provides access to your Grafana instance and the surrounding ecosystem.
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    691
    Go
    Apache 2.0
    • Linux
    • Apple
  • Why this server?

    The project is derived from the MCP Server for Grafana, though it doesn't provide Grafana-specific functionality.

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    MCP Server for Netbird
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    28
    Go
    Apache 2.0
  • Why this server?

    Visualizes AI system metrics and performance data, providing dashboards for monitoring model behavior and operational health.

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    A high-performance FastAPI server supporting Model Context Protocol (MCP) for seamless integration with Large Language Models, featuring REST, GraphQL, and WebSocket APIs, along with real-time monitoring and vector search capabilities.
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    5
    Python
    MIT License
  • Why this server?

    Offers visualization dashboards for monitoring the Sequential Questioning server's performance metrics

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    A specialized server that enables LLMs to gather specific information through sequential questioning, implementing the MCP standard for seamless integration with LLM clients.
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    Python
  • Why this server?

    Provides monitoring dashboards for visualizing MCP server metrics and performance

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    Provides a scalable, containerized infrastructure for deploying and managing Model Context Protocol servers with monitoring, high availability, and secure configurations.
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