Pepys Mcp

One API for Search, Crawling, and Sitemaps

Zhipu Web Search MCP Server is a search engine specifically designed for large models. It integrates four search engines, allowing users to flexibly compare and switch between them. Building upon the web crawling and ranking capabilities of traditional search engines, it enhances intent recognition capabilities, returning results more suitable for large model processing (such as webpage titles, URLs, summaries, site names, site icons, etc.). This helps AI applications achieve "dynamic knowledge acquisition" and "precise scenario adaptation" capabilities.

A Model Context Protocol server that provides time and timezone conversion capabilities. This server enables LLMs to get current time information and perform timezone conversions using IANA timezone names, with automatic system timezone detection.

高德地图官方 MCP Server

An MCP server implementation that provides a tool for dynamic and reflective problem-solving through a structured thinking process.

A Model Context Protocol (MCP) server for image generation and manipulation using fal.ai's Stable Diffusion model.

A Model Context Protocol (MCP) server that integrates with Jina AI Search Foundation APIs.

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Is this song AI or human? SongCheck detects AI-generated music (Suno, Udio, and more) and media from any AI agent. Point it at an audio file, an image/video, or a whole music folder and it returns a verdict (LIKELY AI-GENERATED / UNCERTAIN / LIKELY HUMAN), an AI-probability score, confidence, and provenance signals (Content Credentials / SynthID watermark, generator hints). Tools: detect_ai_music, detect_ai_media, scan_catalog (audit an entire catalog), and songcheck_health. Free tier is 5 checks/day; a paid key unlocks unlimited catalog scans. Powered by SongCheck (Khaled Media), a self-hosted v9 ensemble detector.

The Milvus MCP server enables AI applications to interact with Milvus vector databases using natural language commands. It allows AI models to perform vector searches, manage collections, and retrieve data without writing custom database queries. This integration facilitates seamless access to vector data, enhancing the capabilities of AI tools like Claude Desktop and Cursor.

Secure file operations with configurable access controls

ContextBridge (CB) is a local-first retrieval layer that sits between your codebase and your AI coding agent. Instead of pasting raw source files into context or letting the AI guess which files matter, CB indexes your codebase's real structure (via Graphify) and returns a compact, ranked result — owner file, related files, key symbols, and dependency chains — grounded in your actual code. A typical response is ~4–8 KB instead of the 100+ KB of raw source an AI would otherwise need to read to answer the same question — roughly a 96% cut in input tokens sent to your cloud AI, with zero hallucinated file paths or method names.

Persistent Adaptive Planning Intelligence - structured loop engineering for AI coding assistants, with memory that persists across sessions, tools, and teammates.