"Villager 0.2.1rc1 Framework MCP Auto Penetration Testing" matching MCP servers:

Enables natural language analysis of mechanical test data files (CSV, TDMS, MDF) by providing tools for channel statistics, spectrum analysis, rainflow fatigue counting, thermal state detection, and report generation.

A local MCP server that parses Robot Framework output.xml files, scores and groups failures, and exposes structured triage data to Claude Desktop and Claude Code.

MCP server for generating diagrams, charts, and visualizations using Gemini image generation on Vertex AI. Supports auto-detection of diagram types, multiple style modes, and iterative refinement.

Enables Claude Code to create and edit presentation-grade visualizations such as cloud architecture diagrams, charts, KPI dashboards, and poster infographics, with auto-layout, themes, and export to SVG, PNG, JPG, and PDF.

AI-powered Fantasy Premier League assistant — scored captain picks, transfer suggestions, differentials, fixture outlook, price predictions, live points, and a full manager hub that auto-detects your squad, bank balance, and free transfers.

Enables AI agents to perform reproducible, verifiable statistical analysis through 25 deterministic tools for descriptive statistics, hypothesis testing, regression, clustering, time-series forecasting, and Chinese-labeled plotting.

An MCP server that enables AI assistants to create interactive visualizations, perform statistical analysis, run auto-EDA, and build dashboards using the HoloViz ecosystem with self-contained HTML output.

Generate 25+ types of hand-drawn Excalidraw diagrams - flowcharts, sequence, architecture, mind maps, ER, UML, kanban, bar/line/radar charts - from structured input with Sugiyama auto-layout and CJK support. Reads and modifies .excalidraw files, exports SVG. Python, local, no API keys required.

Enables AI assistants to run verified statistical and analytics computations—including hypothesis tests, A/B testing, descriptive summaries, and sample-size planning—directly on local CSV, TSV, Excel, and Parquet files of any size. Results include effect sizes, confidence intervals, plain-English interpretations, and assumption warnings, with optional independent checks.

Records and visualizes evidence from a coding agent's own testing tools in a private local workspace, with live activity, domain charts, screenshot maps, findings, reproduction steps, human priorities, and persisted testing preferences. Runs 54 bundled CARBON command workflows over local stdio and serves a loopback-only visual workspace with strict evidence and permission gates.

A virtual statistician MCP server that provides real statistical methods—design of experiments, hypothesis testing, regression, SPC, MSA—via tested Python libraries, with plain-language interpretations and plotted outputs.

Enables natural language querying of databases with multi-turn conversations, auto-generated charts, and proactive monitoring via scheduled queries and alerts.

Provides a virtual statistician for AI agents, offering real statistical methods such as design of experiments, hypothesis testing, regression, and process control. It includes an advisor tool to recommend appropriate analyses and generates plain-language interpretations of results.

Enables AI agents to manage and analyze personal investment portfolios, including fund and stock holdings, net value tracking, XIRR calculations, penetration analysis, and backtesting.

Enables AI assistants to turn natural-language descriptions of systems, flows, and data into auto-laid-out, hand-drawn Excalidraw diagrams across 25 diagram types, with architecture-aware styling, natural-language revision, and SVG/PNG export. Runs fully offline with no API keys, and can optionally persist a queryable, version-controlled architecture knowledge graph.

Enables AI coding assistants to generate and iteratively revise auto-laid-out, hand-drawn diagrams across 25 types — architecture, flowcharts, sequence, ER, Gantt, and charts — from natural-language descriptions, with SVG/PNG export. It can also persist a system as a version-controlled, queryable architecture knowledge graph, running fully offline in Cursor, Claude Code, and Windsurf without API keys.

Enables AI coding assistants to turn natural-language architecture and data descriptions into editable, auto-laid-out hand-drawn diagrams across 25 types, with natural-language revisions, SVG/PNG export, and an optional queryable architecture knowledge graph, fully offline without API keys.

Enables AI coding assistants to turn system architecture into auto-laid-out, editable Excalidraw diagrams across 25 diagram types — architecture, sequence, flowcharts, state machines, ER models, swimlanes, Gantt, and charts — with architecture-aware styling, SVG/PNG export, and natural-language revision. It can also persist the system as a version-controlled, queryable knowledge graph, running fully offline without API keys.

Enables AI assistants to turn described architecture and data into 25 types of hand-drawn, auto-laid-out Excalidraw diagrams and editable .excalidraw files, with natural-language revision, SVG/PNG export, and an optional queryable architecture knowledge graph. Runs fully offline in Cursor, Claude Code, and Windsurf without API keys.

Turns structural descriptions of systems, processes, data models, and charts into auto-laid-out, hand-drawn .excalidraw files across 25 diagram types, with natural-language revision and SVG/PNG export. Runs fully offline in Cursor, Claude Code, and Windsurf with no API keys, and can optionally persist an architecture as a version-controlled knowledge graph the AI can query and lint.

Enables AI assistants to generate and revise fully offline, auto-laid-out Excalidraw diagrams across 25 types from natural-language descriptions, including architecture, sequence, state, ER, swimlane, Gantt, and charts, with SVG/PNG export and an optional queryable architecture knowledge graph.

Enables AI coding tools to turn architecture and other structured descriptions into auto-laid-out, hand-drawn Excalidraw diagrams across 25 diagram types, including architecture, flowcharts, sequence, ER, swimlanes, timelines, Gantt, and charts. It also supports natural-language revision, SVG/PNG export, and optionally a queryable knowledge graph of the system.

Enables AI assistants to turn plain-language descriptions of systems, flows, and data into 25 kinds of fully laid-out, hand-drawn Excalidraw diagrams — architecture, sequence, ER, swimlane, Gantt, charts and more — with auto-styling for 50+ technologies and revision in natural language. Runs fully offline, exports to SVG and PNG without a browser or Node.js, and can optionally persist the architecture as a queryable knowledge graph.

Enables AI assistants to generate auto-laid-out, hand-drawn-style Excalidraw diagrams across 25 diagram types from natural-language structure descriptions, with SVG/PNG export and natural-language revision. Runs fully offline without API keys and can persist the described system as a queryable architecture knowledge graph.

Turns natural-language descriptions of systems, workflows, and data into auto-laid-out, hand-drawn-style editable diagram files across 25 diagram types, with optional persistence of the architecture as a queryable, lintable knowledge graph. Runs fully offline inside Cursor, Claude Code, and Windsurf with no API keys, and can export diagrams to SVG and PNG.

Enables AI assistants to generate auto-laid-out, hand-drawn Excalidraw diagrams across 25 types—from architecture and sequence diagrams to Gantt charts and scatter plots—that can be edited and revised in natural language, with SVG/PNG export and optional persistence of a system as a queryable, lintable architecture knowledge graph. Runs fully offline with no API keys.

Enables AI assistants to turn natural-language descriptions of systems, processes, and data into auto-laid-out, hand-drawn editable diagram files across 25 diagram types — architecture, flowcharts, sequence, swimlanes, ER models, Gantt, timelines and charts — with optional natural-language revision and SVG/PNG export. It can also persist an architecture as a version-controlled knowledge graph that the AI can query and lint, running fully offline in Cursor, Claude Code and Windsurf without API keys.

Enables AI coding tools to generate, revise, and export 25 types of auto-laid-out, hand-drawn Excalidraw diagrams from structured specs, with optional persistent architecture knowledge graph querying and linting. It runs fully offline without API keys and produces editable diagrams.

Enables AI assistants to turn architecture descriptions, flows, and data into 25 types of auto-laid-out, hand-drawn .excalidraw diagrams that stay editable, with optional SVG/PNG export and a version-controlled knowledge graph the AI can query and lint. Runs fully offline in Cursor, Claude Code, and Windsurf with no API keys, and diagrams can be revised through natural language.

Enables AI coding assistants to turn architecture and engineering concepts into auto-laid-out, hand-drawn Excalidraw diagrams across 25 types, with natural-language revision and SVG/PNG export. Optionally persists systems as a queryable, version-controlled architecture knowledge graph while running fully offline without API keys.