关键词 "fastapi" 的搜索结果, 共 24 条, 只显示前 480 条
A simple MCP ODBC server using FastAPI, ODBC and SQLAlchemy.
A Model Context Protocol server implementation with FastAPI
FastAPI MCP Server は、FastAPI を用いた MCP (Model Context Protocol) サーバーです。 このプロジェクトは、各種ツールやデータソースへのアクセスを統一的に実現することを目指します。
everyday series assignment
A working example to create a FastAPI server with SSE-based MCP support
Expose your FastAPI endpoints as Model Context Protocol (MCP) tools, with Auth!
A test repository created using the GitHub MCP server
High-performance FastAPI server implementing Model Context Protocol (MCP) for seamless integration with Large Language Models (LLMs). Built with modern stack: FastAPI, Elasticsearch, Redis, Prometheus
This is our final project , in this we have utlized langgraph coupled with various mcp server mounted of fastapi using fastmcp to create mutlifaceted application for healthcare vendor to make them und
MCP server for EAIM Technologies API integration with FastAPI and Socket.IO
A Telegram bot that fetches and summarizes cryptocurrency news using CryptoPanic API, xAI (Grok), and an MCP FastAPI server. Includes robust logging and error handling.
Real-time stock API with Python, MCP server example, yfinance stock analysis dashboard
A FastAPI-based MCP server tool that fetches and summarizes top Reddit posts using Azure OpenAI. It generates a daily PDF digest and uploads it to Slack, with support for topic-based subreddits and sc
The best way to deploy mcp server. A high-performance WebSocket/SSE transport layer & gateway for Anthropic's MCP (Model Context Protocol) — powered by Nginx, Nchan, and FastAPI.
A FastAPI-MCP server that fetches Wikipedia summaries for AI assistants, deployed using Google Colab and Ngrok.
基于 FastAPI 和 MCP(模型上下文协议),实现 AI 模型与开发环境 之间的标准化上下文交互,提升 AI 应用的可扩展性和可维护性。
Nutanix Prism Central と連携してクラスタ・仮想マシン情報を取得する MCP (Model Context Protocol) サーバーの FastAPI 実装
FastAPI server implementing MCP protocol Browser automation via browser-use library.
一款开源的实时AI语音聊天助手:RealtimeVoiceChat,语音听起来相对自然,支持打断 双向语音交互,延迟低,可以实时看到语音转录,以及AI的回复内容 用来构建客服、教育或陪伴等等场景的AI语音助手比较实用 为低延迟交互而构建的复杂客户端-服务器系统: 🎙️捕获:您的声音被您的浏览器捕获。 ➡️流:音频块通过 WebSockets 传输到 Python 后端。 ✍️转
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