An MCP server that enables users to retrieve trivia questions and answers across various categories through the API-Ninjas Trivia API. It supports customizable result limits and filtering by categories like science, history, and entertainment.
Enables users to search for and retrieve detailed information about celebrities from the API Ninjas database. Supports filtering results by name, nationality, net worth range, and height.
Enables users to search and retrieve fitness exercise information from the Api Ninjas database. It supports filtering by exercise name, target muscle, type, and difficulty level.
Generates Lorem Ipsum placeholder text with customizable parameters including paragraph count, length, and formatting options through the API Ninjas service.
Automates competitive research for startup ideas by executing a 7-step pipeline including idea understanding, competitor discovery, profile extraction, feature comparison, market gap analysis, innovation scoring, and report generation.
An MCP server that transforms standard LLMs into autonomous investment bankers, enabling live market data retrieval, fundamental ratio calculations, DCF valuations, portfolio diversification assessment, and automated emailing of executive reports.
MCP server that parses web pages into clean markdown via Crawl4AI's HTTP API, exposing parse_page and health-check tools with configurable proxy and timeout.
Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.
Code-mode MCP server (docs_search + execute_code two-tool surface) backed by a unified capability manifest across three sandbox kernels (in-process node:vm, WASM via QuickJS / Pyodide / Wasmtime, and remote microVM via E2B / Cloudflare Sandbox). At N=30 tools the bootstrap-context cost drops to 13.6% of direct tool-use. Apache-2.0.
MCP server that enables cloud models (like Gemini/Claude) to delegate coding tasks to a local llama.cpp server, preserving cloud usage limits through an AI-powered code review loop.
Enables AI assistants to query KumoRFM for predictive analytics on relational data, including graph management, natural language to PQL conversion, and training-free predictions.
Provides CodeQL language intelligence to AI agents via MCP, enabling completions, hover, definitions, references, diagnostics, formatting, and in-memory file updates for QL code.