关键词 "pull request summaries" 的搜索结果， 共 18 条, 只显示前 480 条
This project provides an HTTP server for image generation using Stable Diffusion, along with a Model Context Protocol (MCP) server that enables AI agents to request image generation.
An MCP Server for Canvas / Instructure to help pull Assignment details and deadlines
A lightweight TypeScript middleware for MCP SDK servers that delivers analytics. Captures request metrics, performance data, and usage patterns with minimal overhead. Features real-time monitoring, co
Statsource is a standalone MCP server designed to simplify data analysis. Whether you're pulling data from a PostgreSQL database or a CSV file, Statsource delivers actionable insights with ease
An MCP server for interfacing with the Youtube Translate API. Create transcripts, translations, subtitles, summaries for any Youtube video (or any other platform). Search video transcripts for keyword
This project is a Model Context Protocol (MCP) Server built using Node.js + Express.js that interacts with the OpenWeather API. It allows users to fetch air pollution data based on latitude & longitud
A FastAPI-MCP server that fetches Wikipedia summaries for AI assistants, deployed using Google Colab and Ngrok.
An MCP server to give Claude easy access to pulling docs
An MCP (Model Context Protocol) server for data transformation and BI charts will allow AI assistants to connect to your data sources, transform data, and generate high-quality visualizations through
Pull pagespeed data using this MCP server.
This project implements a Python-based MCP (Model Context Protocol) server that acts as an interface between Large Language Models (LLMs) and the Google Calendar API. It enables LLMs to perform calend
It consistently responds with "Ranger!" to any MCP tool request it receives via standard input/output.
Exposes MinIO data through Resources. The server can access and provide: Text files (automatically detected based on file extension) Binary files (handled as application/octet-stream)
🚀🤖 Crawl4AI：开源 LLM 友好型网络爬虫和抓取工具。 Crawl4AI 是 GitHub 上排名第一的热门代码库，由充满活力的社区积极维护。它提供速度超快、AI 就绪的 Web 爬取功能，专为 LLM、AI 代理和数据管道量身定制。Crawl4AI 开源、灵活，专为实时性能而构建，为开发者提供无与伦比的速度、精度和部署便捷性。 ✨ 查看最新更新 v0.6.0 🎉 0.6.
企业 IM、在线客服、企业知识库 / 帮助文档、客户之声、工单系统、AI 对话、工作流、项目管理。 Docker 快速开始 方法一：克隆项目并启动docker compose容器，需要另行安装ollama，默认使用 qwen3:0.6b 模型 git clone https://gitee.com/270580156/weiyu.git && cd weiyu/deplo
Summarize YouTube videos in one click for free online with SlideBomb - get AI generated summaries instantly
MiniMax-M1是MiniMax团队最新推出的开源推理模型，基于混合专家架构（MoE）与闪电注意力机制（lightning attention）相结合，总参数量达 4560 亿，每个token激活 459 亿参数。模型超过国内的闭源模型，接近海外的最领先模型，具有业内最高的性价比。MiniMax-M1原生支持 100 万token的上下文长度，提供40 和80K两种推理预算版本，适合处理长输入
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