#framework

The fast, idiomatic way to build MCP servers in Go. Struct-tag auto schema, middleware chain, tool groups, auth, adapters for Gin/OpenAPI/gRPC, async tasks, Inspector UI, and more.

Agent-native travel search. 5 second flights & hotels $50 cheaper. Free forever for the first 1000 Stargazers.

A control plane for AI agents and human supervisors. Persistent task registry with scoped permissions, inter-agent delegation, and full provenance - all accessible via MCP. Deploy on Supabase free tier in 3 commands.

AI-powered website crawling, analysis, and export via MCP. 38 tools for crawl control, browser enrichment capture, WARC/ZIP/single-HTML export, observation timeline, and evidence-backed findings. 4 resources, 4 prompts. Dual-mode: full (38 tools) or code (6 tools). Install: npx crawlio-mcp

Please run `uv pip install pptagent` first

Tool to Prevent AI tunnel-vision in critical workflows. Vibe Check MCP v2.5 introduces Chain-Pattern Interrupts (CPI) to enhance your infrastructure stack. mitigates over-engineering, scope creep, and misalignment by injecting Socratic checkpoints into agent reasoning. - Supports Gemini API, OpenRouter and OpenAI models. - Logs errors for continuous improvement. - Trusted by 11k+ developers. - Strong CI and Security testing protocol built in. Integrate this metacognitive guardrail into your blockchain, data pipelines, or agent-development stacks for robust AI safety and alignment. Visit https://pruthvibhat.com/work/vibecheck-mcp/ for more details. Links: https://murst.org/ https://pruthvibhat.com/ Author: Pruthvi Bhat Tags: metacognition, CPI, AI-safety, agent-frameworks, infrastructure-tools,

QuerySculptor is a GraphQL query builder designed for AI agents that provides 26 structured tools via the Model Context Protocol (MCP). Instead of generating complex GraphQL queries from scratch, AI agents can build queries step-by-step with real-time validation, schema introspection, and error prevention. It works with Claude, Cursor, and other MCP clients, using Redis for session management and featuring a live demo with the Pokemon API. The tool transforms the traditional error-prone approach of raw GraphQL generation into a guided, conversational workflow perfect for AI assistants and chatbots.

Model–Context–Protocol (MCP) Server A modular, extensible Rust-based server providing short-term, long-term, and latent memory services, a chat endpoint backed by a BaseAgent + Sentience DSL, and seamless integration with ChromaDB and LLM services.

MCP API server example : where customers can order from a fun dummy restaurant menu, track order status (success/failed), and view order history. Fully RESTful, plug-and-play, and perfect for testing MCP integrations.

Google Chat MCP server that lets AI assistants like Claude and Cursor participate directly in team conversations - search messages, help teammates, share files, and coordinate across chat platforms.

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

Production-Ready MCP Server Framework • Build, deploy & scale secure AI agent infrastructure • Includes Auth, Observability, Debugger, Telemetry & Runtime • Run real-world MCPs powering AI Agents

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

AI Agents & MCPs & AI Workflow Automation • (280+ MCP servers for AI agents) • AI Automation / AI Agent with MCPs • AI Workflows & AI Agents • MCPs for AI Agents

Flock MCP Servers and Tools

MCP server template based on the Yokai Go framework.

A Model Context Protocol (MCP) server for debugging pytest failures using systematic debugging principles. 🛠 Tools Available register_pytest_failure - Register a new test failure list_failures - List all registered failures get_failure_info - Get detailed information about a specific failure debug_with_principle - Apply debugging principles systematically analyze_failures - Analyze patterns in test failures generate_debug_prompt - Generate LLM prompts for debugging pytest_docs_guide - Get pytest documentation guidance example_tool - Example tool for testing

Elemental is a multi-agent framework designed with a focus on the modularity of agent workflow stages. It enables the creation and management of single-agent or multi-agent systems with ease. The core functionality revolves around dynamically planning how to solve assigned tasks and executing those plans with the help of an agent team. Elemental supports the programmatic creation of flexible and custom workflows and includes a no-code interface for easy management of agents and tasks. Elemental fully supports MCP Tools with easy configuration of MCP servers and selection of individual tools or complete set.

A GitHub API integration server using the MCP (Message Control Protocol) framework

MCP server template based on the Yokai Go framework.

Simple, modular, and observable Go framework for backend applications.

Qilin MCP Framework

This repository provides an empty Playwright test framework that was designed to test AI and Playwright MCP (Model Context Protocol) in course

simply a TypeScript framework for building MCP servers

TypeScript framework for building MCP servers

Production-ready Model Context Protocol (MCP) servers in Python, Go, and Rust for VS Code integration. Enables AI systems to interact with tools via standardized interfaces.

Repository creates or uses various MCP Servers to integrate with Agentic Frameworks and Microsoft Copilot Studio

⛓️RuleGo is a lightweight, high-performance, embedded, next-generation component orchestration rule engine framework for Go.

MCP Agent Graph (MAG) is an agent development framework for rapidly building agent systems. This project is based on graphs, nodes, and MCP to quickly construct complex Agent systems.

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

Digimon Engine — Multi-Agent, Multi-Player Framework for AI-Native Games and Agentic Metaverse

A security scanner for your LLM agentic workflows

🔥 Java enterprise application development framework for full scenario: Restrained, Efficient, Open, Ecologicalll!!! 700% higher concurrency 50% memory savings Startup is 10 times faster. Packing 90% smaller; Compatible with java8 ~ java24. (Replaceable spring)

Adversary simulation and Red teaming platform with AI

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

An extensible AI agents framework

This project demonstrates a decoupled real-time agent architecture that connects LangGraph agents to remote tools served by custom MCP (Modular Command Protocol) servers. The architecture enables a flexible and scalable multi-agent system where each tool can be hosted independently (via SSE or STDIO), offering modularity and cloud-deployable execut

Fair-code workflow automation platform with native AI capabilities. Combine visual building with custom code, self-host or cloud, 400+ integrations.

MCPAgent for Grupa.AI Multi-agent Collaboration Network (MACNET) with Model Context Protocol (MCP) capabilities baked in

MCPAgent for Multi-agent Collaboration Network (MACNET) with Model Context Protocol (MCP) capabilities baked in

How to turn any robot framework library to a mcp server

Developed an MCP-based AI infrastructure enabling real-time tool execution, structured knowledge retrieval, and dynamic agentic interactions for AI clients like Claude and Cursor.

A framework helps you quickly build AI Native IDE products. MCP Client, supports Model Context Protocol (MCP) tools via MCP server.

Pokedex web app

Python framework for creating AI agents that use MCP servers as tools. Compatible with any MCP server and model provider.

mcp test

A simplified implementation of the Model Context Protocol (MCP) server using Elixir's Phoenix Framework.

Easy-to-use MCP server framework specialized for SSE.

MCP Server for Anchor framework.

Automatable GenAI Scripting

MCP-Server tool use project concept for Claude and compatible AI.

Easy MCP (Model Context Protocol) servers and AI agents, defined as YAML.