"How to create Grafana dashboards" matching MCP servers:

A server that enables AI assistants to access and query Grafana dashboards, metrics, logs, and configurations through an MCP protocol interface.

Enables teams to manage and automate Grafana operations through natural-language prompts and 100 Portuguese-language tools, including dashboard creation, query validation for PromQL/LogQL/TraceQL/SQL, multi-format reporting, and role-based safe execution across Grafana versions.

A Model Context Protocol (MCP) server for Grafana. This provides access to your Grafana instance and the surrounding ecosystem.

Enables MCP-compatible agents to interact with Grafana instances for searching, creating, and updating dashboards, exploring logs via Loki, querying datasources, managing alerts, incidents, and on-call shifts, and accessing observability data.

A Model Context Protocol server for Grafana data analysis

MCP server that lets agents create, display, and export rich UI widgets (cards, dashboards, charts, forms) inline in conversations, with interactive iframe support in MCP Apps hosts and PNG image fallback for other clients.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Enables AI assistants to convert CSS-animated SVGs into videos (MP4/WebM/MKV/MOV) and animated images (aPNG/GIF) with frame-accurate rendering and transparency support.

Enables AI assistants to convert recipe amounts between volume and weight for specific ingredients using measured densities, scale recipes, and convert oven temperatures, with source citations and alternative published values.

Renders 45+ interactive chart types, dashboards, and KPI widgets directly inside AI conversations. Supports drill-down, live API polling, 20 themes, and one-click export to PNG, PowerPoint, and A4 documents.

A Model Context Protocol server that converts Markdown documents to plain text with flexible options and dual protocol support.

Enables AI assistants to convert raw and cooked weights for meat and poultry by cut and cooking method from USDA data, calculate how much raw meat to buy for cooked servings, and look up cooking yields and sample ranges.

Enables management of Sprite VMs through interactive dashboards and terminal interfaces. It allows users to execute commands, create filesystem snapshots, transfer files, and manage VM lifecycles via natural language.

An MCP server that enables AI agents to retrieve detailed GitHub Pull Request information using git commit hashes, branch names, or PR numbers. It automatically detects repositories and extracts comprehensive PR data including descriptions, labels, and reviews via the GitHub CLI.

One-pass agentic inbox triage as an MCP server: fetch unread Gmail → classify (action_needed/fyi/newsletter/noise) → summarize → extract tasks → draft replies as Gmail DRAFTS (never sends) → flag calendar → write a triage report. Four stdio tools (fetch_emails, save_gmail_draft, append_tasks, write_report); the host is the LLM, so it runs keyless in Claude Code. Gmail scopes: readonly + compose

Converts JSON data to TOON (Token-Oriented Object Notation) format and back, reducing token usage by 30-60% for more efficient LLM applications.

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

An MCP server integration that enables Cursor AI to communicate with Figma, allowing users to read designs and modify them programmatically through natural language commands.

Searches Reddit for answers to questions and saves Q&A sessions to Notion.

Connects Metabase business intelligence platform to AI assistants, enabling users to query data, create dashboards and charts, manage databases, and interact with BI assets using natural language through the Model Context Protocol.

A dynamic service that creates and manages Model Context Protocol (MCP) servers, allowing users to spawn, customize, and control multiple MCP servers as child processes.

Enables AI assistants to interact with Kibana dashboards, visualizations, and Elasticsearch data through read-only resources and executable tools for searching logs, exporting dashboards, and querying data.

Enables two LLMs to play Tic-Tac-Toe against each other autonomously using a shared tool and an SSE relay. The server facilitates agent-to-agent communication by holding tool responses until the opponent makes a move, managing the game state in real-time.

Fetches website content and converts it to Markdown format with AI-powered content cleanup, ad removal, and full OpenAPI/Swagger specification support for easy processing by AI assistants.

Enables AI agents to directly control Figma Desktop via MCP, supporting UI creation, editing, prototyping, and variable management with over 60 tools.

Provides AI assistants with comprehensive access to Grafana's React component library, including TypeScript source code, MDX documentation, Storybook examples, test files, and design system tokens for building Grafana-compatible interfaces.

A tool that creates MCP (Model Context Protocol) servers from OpenAPI/Swagger specifications, enabling AI assistants to interact with your APIs.

An MCP server that converts Markdown to HTML, supporting both stdio and HTTP interfaces for easy integration with Cursor and other MCP clients.

Enables LLM clients to ask natural-language questions about FABRIC Testbed infrastructure metrics, with responses grounded in fixed Grafana/PromQL queries for node, switch, and link metrics.

Enables AI assistants to query PostgreSQL, MySQL, SQL Server, Oracle, and MongoDB databases through MCP with read-only, audited access.