"OWASP Dependency-Check" matching MCP servers:

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

A fully offline MCP server for generating 15 types of SVG charts, including line, bar, pie, and more, without any network dependency.

Enables AI assistants to read and audit Tableau .twbx workbooks locally, providing tools for dependency tracing, field listing, SQL queries, filters, and semantic diffs.

MCP server for rendering Mermaid diagrams and generating source-code diagrams, with tools to render text/files and produce dependency/class diagrams.

Enables AI agents to parse and query VCD/FSDB simulation waveforms, search signals, analyze AXI transactions, render ASCII timing diagrams, and check protocol compliance through structured MCP tools.

A design studio where AI draws, charts and animates: agents create fully editable hand-drawn visuals, build charts from data, and their edits become stop-motion GIF and video animations. Free, offline, zero-dependency, MIT.

A minimal, dependency-free MCP server that renders interactive widgets (like bar charts) inline in Claude, ChatGPT, and Grok from a custom connector.

Enables users to visualize and interact with Claude's chain-of-thought reasoning from extended thinking traces, turning them into interactive reasoning maps with typed moves, dependency graphs, timelines, and replay mode.

Enables AI agents to synthesize heterogeneous search results into interactive comparison layouts (Genspark Sparkpages) through the Model Context Protocol, with deterministic, zero-dependency execution.

Enables agents to create, customize, analyze and export relationship diagrams — theorem dependencies, paper maps, task RACI, org charts, conversation graphs — through 25 MCP tools, with cycle detection, centrality bottleneck reports, dependency closure and Mermaid/DOT/Markdown/JSON interop. Graphs stay local-first in a diff-friendly JSON source of truth and can be refined on a visual canvas.

Enables AI agents to perform deterministic search synthesis and compile Sparkpage layouts into comparison matrices and ready-to-render HTML interfaces through a zero-dependency Python MCP server. Plugs into Claude Desktop, Cursor, and other MCP clients for structured, low-latency output with execution telemetry.

Enables autonomous agents to synthesize heterogeneous search results into interactive comparison layouts (Genspark Sparkpages) via MCP, with deterministic JSON schema validation and zero-dependency execution.