Projects sharing features with Mcp Server Dumplingai

This is a TypeScript-based MCP server that allows searching for New York Times articles from the last 30 days based on a keyword. It demonstrates core MCP concepts by providing:

quant-wiki is a comprehensive knowledge base and structured reference for quantitative finance, financial engineering, and algorithmic trading. It serves as a centralized library of documentation covering mathematical models, financial instruments, and systematic trading strategies. The project integrates AI-driven capabilities through a modular retrieval-augmented generation framework that extracts structured data from research papers and news. It features a multi-agent workflow engine designed to discover and validate predictive alpha factors, alongside tools for local large language model

node-DeepResearch is an autonomous web research engine that uses large language models to iteratively search, read, and reason over web content to answer complex questions. It provides a chat-based interface that displays real-time reasoning steps and final answers, and can be configured to focus exclusively on academic papers by limiting searches to academic repositories. The research engine operates through an agentic search-read-reason loop that repeatedly searches, reads, and reasons until a stopping condition is satisfied. It enforces a token budget to cap total consumption and failed at

Open-deep-research is an automated research platform that utilizes autonomous agents to perform recursive web queries and synthesize information into structured reports. The system functions as an AI-powered research agent, capable of navigating complex topics by iteratively generating follow-up search queries and mapping interconnected findings. The platform distinguishes itself through a recursive orchestration model that allows for deep exploration of subjects beyond initial search results. It provides a unified interface for both cloud-based and local inference engines, enabling users to

This project provides an agentic web interaction engine designed to facilitate autonomous browser automation and large-scale data extraction. It serves as a framework for building and deploying agents that can navigate complex, JavaScript-rendered websites, interact with page elements, and execute multi-step workflows. By providing a structured environment for browser control, the system enables the creation of reusable automation scripts that can be deployed across diverse web platforms. The platform distinguishes itself through a comprehensive suite of security and traffic management tools,

An MCP Tool Implementation for Multi-Source Image Access & Generation

All-in-one platform for search, recommendations, RAG, and analytics offered via API

MCP Server for Hackernews

This project is a Model Context Protocol server that enables Large Language Models to control Playwright browsers for web automation, scraping, and end-to-end testing. It functions as a programmable interface for executing JavaScript, capturing screenshots, and interacting with web elements across multiple browser engines. The server exposes browser automation capabilities as a set of standardized tools that models can discover and invoke. It supports session-based browser isolation to ensure unique contexts for each client connection and provides a transport layer using either standard input

MCP server paired with a browser extension that enables AI agents to control the user's browser.

BioMCP: Biomedical Model Context Protocol

🔎 A MCP server for Unsplash image search.

MCP server for AI search optimization (GEO). Scan websites, generate llms.txt, Schema.org fixes, meta tags. Works with Claude, Cursor, Windsurf.

MCP server for Naver Search API integration. Provides comprehensive search capabilities across Naver services (web, news, blog, shopping, etc) and data trend analysis tools via DataLab API.

The Official Model Context Protocol (MCP) server for Kagi Search & other tools.

mcp server of tavily

MCP Server for Bing Search API

The World's Most Comprehensive, Authoritative, and Structured Open Source Data Source Knowledge Base

The Model Context Protocol is a standardized communication framework designed to connect language models to external data sources, functional tools, and interactive user interfaces. It provides a vendor-neutral interface layer that enables AI hosts to discover and execute capabilities across heterogeneous service environments, using a JSON-RPC based messaging standard to facilitate bidirectional communication between clients and servers. The protocol distinguishes itself through a robust capability-based handshake that negotiates feature sets during session initialization, ensuring compatibil

Reference MCP servers that are no longer maintained