"Oracle Fusion Cloud API Documentation and Resources" matching MCP servers:

Enables AI assistants and other MCP clients to launch and steer Cursor Cloud Agents on repositories or as repo-less research tasks, including model selection, mid-run follow-ups, cancellation, result retrieval, and run listing. Also exposes authentication checks and per-agent or per-run token usage and cost reporting.

Enables AI assistants and MCP clients to launch and manage Cursor Cloud Agents on repositories or without one, select models, follow up mid-run, retrieve or cancel results, and check usage and cost.

Enables Claude or any MCP client to drive the GitHub Copilot cloud agent via its REST API, allowing it to research, edit, and open pull requests on repositories without manual intervention.

Enables AI assistants to create and manage Cursor Cloud Agents that autonomously work on GitHub repositories, including creating tasks, monitoring progress, and automatically generating pull requests.

Enables programmatic control of Cursor's cloud-based AI agents for automated code generation and repository management via standardized MCP tools.

A hosted AI software engineer that writes code, opens PRs, reviews code, generates tests, runs security scans, and answers codebase questions. Connect from any MCP client (Claude Code, Cursor, Windsurf, or your own agents) and delegate engineering tasks.

A paid remote MCP server for OpenAI Codex harness, offering structured JSON tools for coding task planning, safe command suggestions, test verdict recording, and run history.

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.

Instant secure Full Stack Apps and AI Agents

An AI-agent-first framework for building MCP servers that deliver interactive React widgets directly within AI chat interfaces like ChatGPT and Claude. It includes automated visual testing and a zero-config local development environment designed for autonomous agent workflows.

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

Enables IDE integration with a multi-agent AI pipeline for solving, reviewing, and optimizing code through adversarial peer review and security filtering.

Provides MCP tools to create, run commands in, checkpoint, and delete durable cloud environments, giving coding agents persistent state between calls.

An MCP server that lets AI coding assistants delegate work to Capy's cloud agents and wait for results, all within the editor.

MCP server that enables cloud models (like Gemini/Claude) to delegate coding tasks to a local llama.cpp server, preserving cloud usage limits through an AI-powered code review loop.

Exposes 31 high-assurance agentic coding skills as MCP tools and resources, enabling AI agents to invoke structured workflows across DISCIPLINE, TECHNIQUE, KNOWLEDGE LAYER, and REFERENCE registers.

Provides AI coding agents with five intelligence layers (dependency graph, git history, documentation, architectural decisions, code health) via nine MCP tools, enabling deep codebase understanding and reducing exploration cost.

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.

Enables delegating coding tasks to Cursor Cloud Agents from Claude Code, Codex, or Grok, with scoped repository access, progress monitoring, follow-ups, and result reporting.

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.

Enables developers to delegate asynchronous coding tasks to a cloud-based autonomous agent, creating tasks, reviewing and approving execution plans, sending feedback, monitoring sessions, and retrieving diffs and Pull Requests directly from an MCP-compatible IDE. It also supports configurable mock mode for local testing without consuming API credits.

Enables dispatching and managing Google Jules coding tasks across multiple accounts, including parallel cloud chores, local patch reconciliation, preflight conflict checks, and automated GitHub PR workflows.

An MCP server that enables AI-powered IDEs to implement a structured development workflow from requirements gathering to code implementation, guiding users through goal collection, requirements specification, design documentation, task planning, and execution.

A fully local, privacy-first MCP server that gives AI coding assistants deep repository intelligence with file-and-line-cited answers, persistent semantic memory, and agentic abilities like task planning and code review—all without any cloud API calls.

Connects AI coding agents to Autodesk Fusion 360 for CAD automation, enabling natural language control over sketching, 3D modeling, and CAM operations. It uses a Python-based bridge and a custom add-in to execute over 80 tools ranging from simple geometry creation to complex assembly and parameter management.

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

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

Enables AI coding agents to set budgets per task, check costs before expensive operations, and halt when budget is exhausted, with support for calibration and cloud sync.