"How to Test Kubernetes Network Policies" matching MCP servers:

An MCP server that integrates AI agents with Figma, enabling reading and programmatic modification of designs.

Enables AI agents to directly control Figma Desktop via MCP, supporting UI creation, editing, prototyping, and variable management with over 60 tools.

Enables LLM clients to generate standardized test cases, perform quality control with lint scoring, convert to Xray/Jira format, and compose test suites (Smoke/Regression/E2E) with coverage analysis.

Enables AI agents to retrieve real-time data on wallet DeFi positions, token balances, and NFT holdings across multiple blockchains. It supports hundreds of protocols and provides specialized tools for chain-specific or protocol-specific portfolio analysis.

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.

A simple MCP server that provides a basic greeting tool and serves as a starter template for AWS Lambda deployment. Demonstrates how to build and deploy MCP servers with both local development and cloud deployment capabilities.

Enables AI agents to interact with the Moltbook social network, including posting, reading feeds, commenting, voting, and semantic search.

Enables AI assistants to read and modify Figma designs programmatically through the Model Context Protocol.

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.

Enables AI models to access and search offline Wikipedia and other knowledge bases stored in ZIM format files. Provides intelligent content retrieval, structured browsing, advanced search capabilities, and metadata extraction for comprehensive offline knowledge access.

Provides unofficial access to Philippine Stock Exchange data including quotes, price history, disclosures, financial reports, and market data via MCP.

Provides AI assistants with direct access to Jamf official documentation, enabling them to answer Jamf-related questions by searching, retrieving articles, and browsing product documentation.

Local MCP server for generating image assets with Google Gemini (Nano Banana 2 / Pro). Supports transparent PNG/WebP output, exact resizing/cropping, up to 14 reference images, and Google Search grounding.

An offline MCP server for SAP ABAP that provides static analysis, ABAP Cloud readiness checks, and RAP scaffolding using abaplint, enabling AI agents to analyze and generate ABAP code without a live SAP system.

Enables LLMs to interact with the AT Protocol ecosystem, including Bluesky, through natural language. Supports public data access without authentication and full write operations with authentication.

Enables AI assistants to read, search, and traverse your entire reMarkable library, including handwritten notes via OCR.

A TypeScript-based server that enables programmatic management of pseudo-terminal sessions. It allows users to spawn, control, and interact with terminal processes in real-time through the Model Context Protocol.