"Resources for security testing, penetration testing, and bug bounty programs" matching MCP servers:

Provides coding agents with visibility into test health through tools for flaky test detection, test quality linting, and LLM evaluation harness, enabling them to triage failures, review test quality, and check prompt changes for regressions.

Enables AI agents to interact with Google NotebookLM and Gemini API for document analysis, deep research, and notebook creation with enterprise-grade security including post-quantum encryption and 14 security layers.

Enterprise-grade Azure security assessment toolkit with multi-location scanning, IMDS exploitation, attack path analysis, and compliance reporting. Enables authorized penetration testing and compliance audits across all Azure regions.

MCP server for WeChat Mini Program debugging and automation, enabling agents to perform UI operations, screenshots, and regression testing through natural language commands.

A production-grade TypeScript starter for building Model Context Protocol servers, supporting stdio and Streamable HTTP transports with modular tools, resources, and prompts.

Enables AI coding agents to make evidence-aware design-pattern decisions by analyzing cases, comparing options, detecting misuse, stress-testing assumptions, planning adoption, writing ADRs, and generating evidence plans with transparent scoring.

Integrates HomeMatic smart home devices (via CCU3, RaspberryMatic, or debmatic) as MCP tools, enabling natural language query and control of rooms, devices, programs, and system variables.

An MCP server that lets AI agents build on GenLayer by searching documentation, inspecting contracts and transactions over RPC, and scaffolding, linting, and testing Intelligent Contracts.

Enables AI assistants to automate mobile app testing and development for iOS and Android through natural language interactions. Supports intelligent element identification, session management, automated test generation, and comprehensive device interactions including clicks, swipes, screenshots, and app management.

Provides complete access to Model Context Protocol documentation through an MCP server, allowing LLMs to query specific sections like 'Tools', 'Resources', and 'Authorization' to retrieve comprehensive protocol specifications.

Enables AI assistants to automate WeChat Developer Tools for mini programs, allowing navigation, inspection, and manipulation of pages and components through the miniprogram-automator API.

Habitica MCP server built with Effect v4, currently exposing a hello-world tool, resource, and prompt over stdio for early development and testing.

A production-grade MCP server providing an autonomous AI agent swarm, persistent semantic memory, browser automation, multi-model reasoning, and 78+ tools for AI-first testing and development.

Exposes GOV.UK Frontend components and Design System patterns and styles as MCP resources for use with AI assistants.

MCP server providing token-efficient access to OpenAPI/Swagger specs via MCP Resources for client-side exploration.

A lightweight MCP server that enables AI assistants to execute local development tools and retrieve system status with low latency over stdio or HTTP.

An MCP server that provides AI clients with access to developer documentation via llms.txt files. Exposes tools, resources, and prompts.

A local-first, no-API-key MCP server that enables LLMs to search the web, fetch pages, and read documents using multiple engines and smart fallbacks.

Enables AI assistants to perform Google searches with real, resolvable sources and transparent search terms.

MCP server for overseer.nvim — gives any MCP-capable coding agent running inside Neovim (Claude Code, Codex, Gemini CLI, opencode) the same visibility and control over tasks the user has: list, run, tail, restart, stop. Agent-started dev servers land in the user's own task list instead of becoming invisible orphaned processes.