"Python context management and dependency solving in ComfyUI" matching MCP servers:

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

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.

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.

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

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 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.

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

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.

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.

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.

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.

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.

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

MCP server for creating interactive Vega-Lite data visualizations that render inline in chat via MCP Apps.

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 querying SQLite databases in plain language through MCP, letting clients like Claude Code inspect schemas and run read-only SQL.

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

An MCP server that lets Claude or ChatGPT read, create, and edit mind maps stored in a GitHub repository, with support for local and HTTP transport.

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.

Official draw.io MCP server: create diagrams from Mermaid, XML or CSV, shown inline in Claude, ChatGPT, VS Code and Cursor or opened in the draw.io editor. Searches 10,000+ shapes.

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.

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.

Turns a CSV — or a public dataset named in plain English — into an animated chart video. Every numeric claim in the generated narration is recomputed from the source rows before export, and a claim that does not reconcile blocks the export rather than shipping.

Data-visualization MCP server for ROOT Workspace. It enables creating and iterating on charts (Vega-Lite, Python plots) with a persistent kernel and vision loop.

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.

Enables AI agents to render interactive user interfaces such as forms, dashboards, charts, tables, and wizards directly in MCP-compatible clients. Supports structured data collection and richer interactions beyond text responses.

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.