"YAPI API Documentation Integration Guide" matching MCP servers:

An MCP server that enables users to manage Google's Jules AI coding agent sessions directly from MCP-compatible clients. It supports creating sessions, approving execution plans, and interacting with session activity to streamline autonomous coding workflows.

MCP server that automates the generation of production-grade async FastAPI services following Clean Architecture, with self-healing pytest-based verification and OpenAPI spec ingestion for rapid CRUD API development.

Brings all SuperClaude features to Gemini CLI, enabling advanced coding assistance, persona switching, and token optimization.

A multi-agent system for code rules management using MCP, supporting search, generation, and architectural validation through specialized agents.

Production-ready MCP server starter templates in TypeScript and Python. Includes tool, resource, and prompt patterns with Claude Desktop integration configs.

Enables AI tools to interact with browsers for enhanced frontend development, providing context to LLMs through tools like API call analysis, screenshots, element selection, and documentation ingestion.

An MCP (Model Context Protocol) server that enables integration with the Simplifier Low Code Platform. This server provides tools and capabilities for creating and managing Simplifier Connectors and BusinessObjects through the platform's REST API.

MCP server that provides AI coding agents automatic access to AGENTS.md documentation from GitHub repositories, enabling understanding of codebase conventions and patterns.

This MCP server enables remote control and management of Claude Code agents, allowing you to execute missions, configure agent personalities, and integrate with other MCP tools.

Provides access to the Superpowers skills library - expert-crafted workflows and best practices that guide AI assistants through proven techniques for coding tasks. Supports both community skills and custom personal skills.

Enables orchestration of multiple Jules AI workers for tasks like code generation, bug fixing, and review using the Google Jules API. It features git integration, a shared memory system, and real-time activity monitoring for complex, multi-agent development workflows.

An MCP server that implements a structured workflow for LLM-based coding, guiding development through feature clarification, documentation generation, phased implementation, and progress tracking.

A FastMCP integration with Hyperskill that allows AI agents to explain programming topics and search for programming resources using Hyperskill's learning materials.

A server component of the Model Context Protocol that provides intelligent analysis of codebases using vector search and machine learning to understand code patterns, architectural decisions, and documentation.

Provides AI coding agents with access to CleanSlice architecture documentation, rules, and conventions. It enables users to search documentation and retrieve essential patterns to help AI build applications correctly.

Connects AI coding assistants to the Jules API for autonomous coding sessions. Enables creating and managing coding sessions, GitHub integration, plan approval workflows, and real-time activity tracking directly from your IDE.

Multi-Agent Development Agentic Network that enables AI-driven software development through specialized agents, interactive wizards, and structured debate, with MCP integration for IDE tools like workflow execution, impact analysis, and ecosystem search.

A local AI agent system that gives any LLM real access to the filesystem, terminal, and codebase via MCP, usable as a standalone terminal agent or Continue.dev integration in VS Code.

Integrates with Dispersl to provide multi-agent orchestration for AI-driven software development, enabling code generation, testing, documentation, git operations, and chat.

Indexes GitHub repositories and provides living documentation context to coding agents, enabling them to ground work in actual repository conventions and propose doc updates.