#multi-agent

Core MCP Server with React Frontend and Multi-Agent Support

Claude 3.7 Swarm with Field Coherence: A Model Context Protocol (MCP) server that orchestrates multiple specialized Claude 3.7 Sonnet instances in a quantum-inspired swarm. It creates a field coherence effect across pattern recognition, information theory, and reasoning specialists to produce optimally coherent responses from ensemble intelligence.

This is a revolutionary AI MCP plugin with excellent pluggable and encapsulated features. With just a few lines of configuration, it can easily integrate into your Spring boot web program and give it MCP capabilities,inheriting the powerful engineering capabilities of the Spring series framework

The open-source multi-agent chat interface that lets you manage multiple agents in one dynamic conversation and add MCP servers for deep research

This project is a proof of concept for running a local-first multi-agent system using: 🤖 Local LLMs via Ollama 🧩 Simple function/tool-call detection using <tool_call>... 🔍 Brave Search API or optional Brave MCP plugin server 🧠 Two collaborating agents: Searcher and Synthesizer

MCP Server generated by mcp.ag2.ai

The llm_to_mcp_integration_engine is a communication layer designed to enhance the reliability of interactions between LLMs and tools (like MCP servers or functions).

This is a revolutionary AI MCP plugin with excellent pluggable and encapsulated features. With just a few lines of configuration, it can easily integrate into your Spring boot web program and give it MCP capabilities,inheriting the powerful engineering capabilities of the Spring series framework

A powerful MCP tool for forging and managing AI agent personalities with customizable expert traits and behaviors. 一个可以由大模型控制并定制Agent的MCP工具，supervisor架构，低成本复刻类似于CO-STORM的multi-agent research。

This is a revolutionary AI MCP plugin with excellent pluggable and encapsulated features. With just a few lines of configuration, it can easily integrate into your Spring boot web program and give it MCP capabilities,inheriting the powerful engineering capabilities of the Spring series framework

MCPOmni Connect is an agent execution runtime that connects to multiple MCP servers via stdio, SSE, or streamable HTTP. It supports chat, autonomous agents, and planner-based orchestration treating each MCP server as a tool agent to enable dynamic multi-agent workflows across LLM systems, and can be embedded in FastAPI or backend systems.

A Model Context Protocol server that provides task orchestration capabilities for AI assistants

This is a Multi agent that utilizes MCP server to communicate and also Uses Azure Cloud Service

A Model Context Protocol (MCP) compliant server designed for comprehensive web research. It uses Tavily's Search and Crawl APIs to gather detailed information on a given topic, then structures this data in a format perfect for LLMs to create high-quality markdown documents.

一个强大的、可扩展的多智能体工作流引擎，支持Multi-Agent系统、auto-workflow、MCP-SERVER接入等功能，支持多种工具和资源，提供智能代理和自动化服务执行。

A modular AGI agent framework based on MCP (Multi-Context Processing), inspired by Manus, with ChatGPT-style LLM integration and task control.

This MCP server provides documentation about Strands Agents to your GenAI tools, so you can use your favorite AI coding assistant to vibe-code Strands Agents.

Claude 3.7 Swarm with Field Coherence: A Model Context Protocol (MCP) server that orchestrates multiple specialized Claude 3.7 Sonnet instances in a quantum-inspired swarm. It creates a field coherence effect across pattern recognition, information theory, and reasoning specialists to produce optimally coherent responses from ensemble intelligence.

Seamlessly integrating APIs, advanced AI, and intelligent automation with Github & X, this state-of-the-art MCP framework revolutionizes server & client-side functionality. 🚀 With features like AI-powered Intelligent Notifications, it predicts critical updates and delivers custom alerts via email, ensuring smarter workflows.

**SlashMCP** is a production-grade AI workspace that connects LLMs to real-world data and tools through an intuitive chat interface. Built on the Model Context Protocol (MCP), it enables seamless interaction with multiple AI providers (OpenAI, Claude, Gemini) while providing powerful capabilities for document analysis, financial data queries, web scraping, and multi-agent workflow orchestration. ### Key Features: - **Multi-LLM Support**: Switch between GPT-4, Claude, and Gemini at runtime—no restart needed - **Smart Command Autocomplete**: Type `/` to discover and execute MCP server commands instantly - **Document Intelligence**: Drag-and-drop documents with automatic OCR extraction and vision analysis - **Financial Data Integration**: Real-time stock quotes, charts, and prediction market data via Alpha Vantage and Polymarket - **Browser Automation**: Web scraping and navigation using Playwright MCP - **Multi-Agent Orchestration**: Intelligent routing with specialized agents for command discovery, tool execution, and response synthesis - **Dynamic MCP Registry**: Add and use any MCP server on the fly without code changes - **Voice Interaction**: Browser-based transcription and text-to-speech support ### Use Cases: - Research and analysis workflows - Document processing and extraction - Financial market monitoring - Web data collection and comparison - Multi-step task automation **Live Demo:** [ slashmcp.vercel.app ]( https://slashmcp.vercel.app ) **GitHub:** [ github.com/mcpmessenger/slashmcp ]( https://github.com/mcpmessenger/slashmcp ) **Website:** [ slashmcp.com](https://slashmcp.com )