"How to Assess the Security of a Python Application" matching MCP servers:

A Python MCP server for Metabase that enables AI assistants to query databases, manage dashboards, and interact with your Metabase instance.

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 LLM clients to run Python code in a persistent, user-selected interpreter via MCP, with tools for data loading, summaries, regressions, diagnostics, and plotting, while keeping sessions alive between calls and isolating crashes.

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 secure execution of statistical Python code in isolated micro-VM sandboxes, generating charts and analytical summaries.

Enables time series analysis following Box-Jenkins-Treadway methodology, supporting guided or autonomous modes for model identification, estimation, and diagnosis via an LLM.

A local Python MCP server for AI-assisted development of Yandex DataLens dashboards, enabling inspection, planning, validation, and guarded application of changes.

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

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 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.

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.

Zero-dependency charts for Python and AI agents. SVG and PNG, 15 chart types, a one-line MCP server, and a Claude skill.

A demo MCP server that returns an interactive dashboard (bar chart with dataset selector) as an MCP App via the official MCP Apps extension (SEP-1865).

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.

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 converting ASCII and Unicode text diagrams into crisp, animated SVG with 1:1 verification, including repair of misaligned diagrams.

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.