"MCP (Model Context Protocol) requirements and selection" matching MCP servers:

Provides AI agents with read-only access to live chart context, candles, drawings, indicators, and provider status from the MyLinedChart desktop app, all running locally.

MCP server for rendering Object-Process Methodology (OPM) models from YAML to SVG diagrams and OPL sentences, with validation and generation capabilities.

Options analytics an agent can drive: import a permitted chain, solve implied volatility, build a sixteen-Greek ladder, map dealer gamma walls, rank twenty-three structures, run a GARCH-t simulation with a convergence gate, and backtest with modelled premiums. Twelve stdio tools; every output is a schema-validated JSON file with source, assumptions and a degraded flag. Research only, no orders.

Validates and renders declarative JSON diagram specs to themeable SVG. The format has no coordinates, so a model writes structure and the renderer does the layout; tools: validate, render, kinds.

Embeds live, interactive Tableau dashboards in ChatGPT, pushing mark selections to the model so questions about specific data points are answered with live queried numbers.

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.

Read-only FastMCP server providing machine learning stock selection scores, Alpha158 signals, and SHA-256 checksums from Qlib.

A unified Model Context Protocol server for data engineering and analytics that lets LLM clients query, profile, transform, and visualize data using DuckDB and PySpark, while keeping raw data out of the model's context through read-only, bounded, and audited operations.

Enables LLMs to generate visual summary reports from CSV datasets using MCP Resources, Tools, and Prompts, without exposing raw data to the model.

A Model Context Protocol server that renders Apache ECharts options to SVG, enabling AI agents to generate deterministic charts server-side without a browser.

Enables LLMs to safely execute pandas code for data analysis and generate interactive visualizations through the Model Context Protocol.

A Model Context Protocol server for interacting with Lightdash, enabling AI assistants to discover data, create charts, and manage dashboards programmatically.

A FastMCP server that turns JSON data into Plotly figures, deployable as an isolated service on Modal. Data goes in as JSON; a validated Plotly figure (JSON) or a rendered PNG comes back over the Model Context Protocol.

Enables AI hosts to generate editable online diagrams (flowcharts, mindmaps, UML, and more) from natural language or Mermaid, using a ProcessOn account via the Model Context Protocol.

An MCP (Model Context Protocol) server that lets AI agents manage Power BI workspaces, datasets, and refreshes via natural language.

A Model Context Protocol (MCP) server that exposes tools for exploring and querying SQLite and PostgreSQL databases. It allows Large Language Models (LLMs) to inspect table structures, perform statistical profiling, generate entity-relationship diagrams, and execute queries safely.

A Model Context Protocol server that provides a dynamic map interface with tools to add raster/vector layers, control map view, and modify paint properties.

Enables AI assistants to create, update, publish, and manage Datawrapper charts via the Model Context Protocol.

Enables natural language control of live ArcGIS Pro sessions through the Model Context Protocol, allowing inspection of projects, layers, and attributes, and execution of geoprocessing tasks.