mcp-asset-gen

An MCP service designed for deploying HTML content to EdgeOne Pages and obtaining an accessible public URL.

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

MCP server for ArcGIS Portal and ArcGIS Online. Lets AI assistants search content, query feature layers, manage features, handle content operations, and administer users and groups. Built on the Model Context Protocol for integration with Claude Desktop, Cursor, VS Code Copilot, and other MCP clients. Disclaimer: This is an independent open-source project. It is not affiliated with, endorsed by, or sponsored by Esri Inc. "ArcGIS" is a registered trademark of Esri.

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

GitLab API, enabling project management

Playwright MCP server

MCP server to provide Figma layout information to AI coding agents like Cursor

Official Firecrawl MCP Server - Adds powerful web scraping to Cursor, Claude and any other LLM clients.

One API for Search, Crawling, and Sitemaps

百度地图核心API现已全面兼容MCP协议，是国内首家兼容MCP协议的地图服务商。

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.

A Model Context Protocol Server connector for Perplexity API, to enable web search without leaving the MCP ecosystem.

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

基于七牛云产品构建的 Model Context Protocol (MCP) Server，支持用户在 AI 大模型客户端的上下文中通过该 MCP Server 来访问七牛云存储资源、利用 Dora 服务进行图片操作等。 如果有什么需求欢迎在下方评论，您也可以在 github 仓库中提 issue。

Language models generate; Concordance verifies. The verify tool checks a claim deterministically (no model in the loop) and returns HOLDS / BROKEN / INCOMPLETE with the worked reasoning and a sealed receipt (content_hash + cite_url) that re-fetches byte-identical or not at all. Also: ranked search over an ~11k-record library, seal_fetch to re-verify any receipt, redact to strip PII before text travels, and a sealed connection graph. Runs sovereign/offline too (stdlib-first Python). A public false-positive benchmark covers every domain: the engine has never sealed a falsehood. 38 tools live; remote endpoint at https://narrowhighway.com/mcp.

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.

Location services, directions, and place details