"A tool to access websites and extract coding documentation" matching MCP servers:

Enables discovery of Fabric/Power BI workspaces and semantic models, execution of DAX queries, and generation of executive HTML reports with visualizations.

Enables an agent to turn a paper's draft into editable Figma frames for publication-ready figures, checking every number against the paper and verifying the exported PDF.

Enables MCP-compatible clients to query advertising data, analyze spend, conversions, and audiences, compare campaigns, generate dashboards, and manage campaigns with optional read-only safeguards.

Enables users to create, validate, view, and export system stock-and-flow maps from a versioned JSON model through MCP-capable hosts over local stdio or hosted Streamable HTTP. Supports causal-loop and nested-level mapping while keeping submitted model content with the caller and requiring no LLM provider key.

Enables generating Power BI .pbit dashboards from CSV files or live SQL databases using plain-English prompts and optional reference-image layouts, with local-only processing and MCP tools for Claude Desktop.

Enables Codex to control a Gephi 3D network view through natural language, including network generation, 3D layout, node focus and neighbor highlighting, layered views, and PNG/PDF export.

A local, fully vectorized computational engine for stock market analysis that enables AI to perform factor calculation, strategy backtesting, IC analysis, and GPU-based multi-dimensional visualization using local DuckDB data.

Enables LLMs to safely execute pandas code for data analysis and generate interactive visualizations through MCP protocol.

An HTTP MCP server for exploring CSV files that masks PII before any code execution, enabling safe data analysis with local or cloud LLMs.

Enables AI clients to discover datasets and author dashboards in Dashboard Builder through natural language, while preserving per-user permissions and audit trails via a secure API-key gated gateway.

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.

Enables creating and editing PowerPoint .pptx files without corruption, with native editable SVG shapes, glued connectors, table surgery, threaded comments, live editing, and a comprehensive 138-tool MCP server surface.

Renders word-sized charts — sparklines, bars, bullets and 100+ more types — to self-contained SVG with generated alt text, small enough to sit inline in a model's reply or a table cell. Three tools: find the right chart for a question, get its wiring, and render it.

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.

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.

Converts DataFusion physical execution plans into editable Excalidraw diagrams or PNG images via a single visualize tool.

Renders OHLCV data as candlestick chart PNGs and returns inline images. It is a pure renderer with no network access, allowing models to view charts generated from provided data.

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 users to create, inspect, analyze, format, and chart Excel workbooks by having the client LLM write Python that runs in a fresh, network-restricted Docker container. Exposes a single execute_python tool with access to openpyxl, pandas, numpy, and matplotlib, persisting files between calls.

Geneva MCP brings production-grade forecasting directly into AI assistants and coding agents. Connect any MCP-compatible client to the Geneva Forecasting Engine and run rigorous time series forecasts through natural conversation.

MCP server that provides a live, terminal-native layered dependency map for AI coding assistants, with tools to track and visualize development progress in real time.

Computes biorhythm values (physical, emotional, intellectual) and generates a PNG chart showing sine curves based on birth date and optional target date.

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

Wraps a climate data-processing pipeline so agents can inspect the config schema and available sample CSVs, validate an inline JSON config, and run the pipeline to return a monthly summary table plus a rendered plot, with file access sandboxed to the data and outputs directories.

A graph layout server that computes node coordinates and edge paths from structure using elkjs, enabling agents to offload layout calculations without rendering.

Provides live weather radar and text-based radar maps for any location via the get_weather tool, returning structured data and character grid visualizations readable by both humans and LLM agents.

A comprehensive MCP server that provides intelligent access to the HoloViz ecosystem, enabling AI assistants to help you build interactive dashboards and data visualizations with Panel, hvPlot, Lumen, Datashader, and your favorite Python libraries.

Exposes a time series forecasting model as an MCP tool with built-in audit logging for every call, enabling trustworthy autonomous forecasting.

Gives terminal coding agents a local browser canvas for rendering charts, tables, metrics, markdown, live widgets and sandboxed MCP App UIs that would otherwise reach them as raw JSON. Lets agents pose blocking visual multiple-choice questions and read back the user's clicks, selections and an animated architecture map of file activity.

Visualizes conversations as structured hierarchical mind maps by injecting a prompt that instructs the LLM to generate a JSON mind map — no external APIs required.