"Proof-of-concept examples for Multi-Component Processes (MCPs)" matching MCP servers:

A collection of Model Context Protocol implementations ranging from a minimal hello-world to an autonomous AI agent for software development.

Enables LLMs to interact with Kibana through composable toolboxes for building dashboards, managing data, and handling alerts, among other operations.

A safety-gated Python MCP server for Metabase that lets MCP clients and agents inspect Metabase, run governed queries, and create or maintain dashboards, cards/questions, collections, snippets, permissions, and other Metabase assets through the Metabase REST API.

Provides aerodynamic analysis tools through MCP, enabling geometry generation, meshing, CFD solving, and visualization for 2D airfoils.

A production-grade MCP server that provides tools to fetch historical stock data, company information, and technical indicators (SMA, EMA, RSI, MACD, Bollinger Bands) via yfinance, and includes a Flask web dashboard for visual analysis.

Generate annotated post-trade candlestick review-chart PNGs from broker or exchange fills. Includes capability checks, no-charge preflight validation, and chart rendering; no signals or order execution.

Enables your own ChatGPT to build and manage a collaborative work board—dashboards, categories, datasets, monitors, and policies—through typed WebMCP tools, with human approval, audit trails, and guardrails enforced on every action.

MCP server for MetricUI — a React dashboard component library. Provides AI coding tools with full API references, working examples, format suggestions, prop validation, and complete dashboard scaffolding for building analytics UIs.

MCP server for Microsoft Power BI and Fabric, enabling Claude to discover workspaces, semantic models, generate and execute DAX queries, and retrieve report metadata via device-code authentication.

Enables AI assistants to drive a live TradingView chart in Chrome, turning natural-language trading ideas into compiled Pine Script indicators, adding them to charts, and reading back results. It also supports chart navigation, indicator management, screenshots, and strategy tester backtest results.

MCP server providing data analytics tools for AI agents to load, clean, analyze data, generate charts and dashboards.

Enables AI assistants to control a logged-in TradingView chart in Chrome, including writing and compiling Pine Script indicators, adding them to charts, changing symbols and timeframes, capturing screenshots, and retrieving strategy tester results.

Enables turning data into map images of countries, states, provinces, counties, continents, and the world, including choropleths, category maps, and pinned locations.

Enables rendering, validation, formatting, and inspection of D2 diagrams via the Model Context Protocol, using WASM for rendering without requiring the d2 binary.

A Model Context Protocol server that gives an LLM a structured visual layer to describe what exists and get back a clean, precise SVG diagram instead of ASCII art.

Enables natural language querying of brain volumes (NIfTI) with a fixed set of tools, returning visualizations and reproducible nilearn code.

Enables reading and analysis of vector spatial data through Claude Desktop, supporting formats like FileGDB, Shapefile, GeoJSON, and GeoPackage with tools for layer listing, schema inspection, field statistics, feature extraction, and interactive map rendering.

MCP server that lets agents create and update persistent concept maps via the NodeLand API, returning shareable URLs for humans to view, embed, and keep editing.

MCP server for generating diagrams, charts, and visualizations using Gemini image generation on Vertex AI. Supports auto-detection of diagram types, multiple style modes, and iterative refinement.

Universal MCP server for generating word clouds using ShapeWords, enabling creation of SVG, JSON, or PNG word clouds from text with extensive customization options.