A CLI tool that sets up a Model Control Protocol server and deploys it to Cloudflare Workers, allowing you to quickly create custom tools for your Cursor Agent just by writing TypeScript functions.
A dynamic service that creates and manages Model Context Protocol (MCP) servers, allowing users to spawn, customize, and control multiple MCP servers as child processes.
An enhanced dynamic MCP server management service that creates, runs, and manages Model Context Protocol servers with multi-language support and strict parameter validation.
Enables AI agents to directly manipulate Jupyter Notebook cells and structure through a secure, well-defined API, overcoming Cursor's AI agent mode limitations.
Enables an MCP-compatible AI client to author Blender Python, run Blender, import the resulting asset into Unity with materials and a prefab, place it in the active scene, verify the import, and revise the same asset using stable IDs.
Enables code execution in isolated Docker containers with persistent IPython, Node.js, or R kernels, supporting file import/export and cross-session transfers via MCP tools.
Provides workspace-scoped file operations and command execution tools for building Cursor-style agents, along with system prompts and tool definitions for LLM integration.
The Problem
Modern distributed systems and AI agents require robust operational scaffolding. Simple CRUD apps or mock loops fail when subjected to real-world edge cases, asynchronous boundaries, and security constraints.
The Solution
An isolated execution platform for AI agents. An agent is given a broken service and a bounded toolset inside a disposable sandbox. Every command passes throug
An orchestration platform for deploying parallel swarms of tool-enabled AI agents to perform complex tasks like code generation, system monitoring, and multi-perspective analysis. It features a unique chunked write pattern that enables the creation of large-scale documents and code files by assembling parallel agent outputs.
Enables external AI clients to invoke an autonomous coding agent that plans, fixes, and self-corrects code in an isolated Docker sandbox via run_task and run_tests tools.
Exposes tools over stdio that let an AI agent create disposable Docker sandboxes to run commands and stream output, read and write files, and take snapshots, roll them back, fork them, list, and destroy them. It tells the model to snapshot before risky changes so failed attempts can be undone or explored in parallel on self-hosted infrastructure.
Enables coding agents to start and operate live kernels on local machines, Modal GPUs, or Colab VMs, running code, notebook cells, shell commands, and file transfers while inspecting variables, plots, and errors. It also runs notebooks, scripts, and web UIs end to end as budget-capped plans that verify expectations and report what failed and what changed.
Connects ChatGPT to Roblox Studio's built-in MCP, enabling natural-language reading and writing of game data, including executing Luau code and modifying scripts and instances.
Gives a coding agent its own Docker-hosted Linux desktop with XFCE, Chromium, Blender, LibreOffice, GIMP and a sudo shell, exposing tools for screenshots, mouse and keyboard input, window focus, shell commands, file read/write, opening URLs or GUI apps, and headless Blender renders. The agent can watch and drive that desktop live from a browser while working on the shared project folder.
Enables coding agents and users to share live tmux-based REPL sessions for many languages, allowing agents to execute code in the same interactive workspace via MCP.
Enables AI agents to create, manage, and execute code in isolated Firecracker microVM sandboxes via the MCP protocol, with support for sandbox lifecycle and file operations.
Enables ChatGPT on Windows to securely access codebases, Git, terminals, language servers, debuggers, SQLite, local HTTP services, adaptive project memory, engineering skills, checkpoints, audit logs, and sandboxed command execution through MCP tools.
Enables the creation and deployment of API-based MCP tools for Cursor Agent using Cloudflare Workers, streamlining development and integration of custom functionalities.
MCP server for the Agent Platform API, enabling management of sandbox environments through MCP protocol. Exposes tools to interact with sandbox lifecycle operations such as start, stop, and status checks.
Routes code generation tasks between local models and Claude Cloud, optimizing cost by handling simple tasks locally and reserving cloud thinking for complex tasks.
MCP server that exposes a pool of Claude SDK agents as tools, enabling deterministic agent creation, retrieval, and resumption from a capability corpus.
An MCP server that exposes a sandboxed task runner protocol to any MCP client, enabling evidence-protected task execution, exit protocol reading, and autopsy reports.
Enables ChatGPT web to interact with local Windows/WSL shell and code workspaces via an MCP server, providing file access, shell execution, and snapshot-based workspace management with per-command authorization.
Enables coding assistants to access Perplexity AI for quick fact-checking and in-depth research. Provides two tools: lookup for fast documentation queries and answer for comprehensive research with recommendations.
Enables AI coding agents to run Kubernetes inspection and Terraform plan/apply operations inside ephemeral gVisor-sandboxed jobs with short-lived, narrowly-scoped credentials, while routing destructive changes through a human approval gate.
Enables supervising and orchestrating local coding agents like Muse and AGY through a client-agnostic MCP interface, with isolated Git worktrees, safe execution, and deterministic verification.
Enables secure Windows development automation by providing MCP tools for filesystem access, project builds, restricted PowerShell commands, and approved network fetches.
A multi-agent collaborative development bridge that enables TRAE Work to offload complex tasks to Codex executor, with tools for task submission, status tracking, artifact listing, and permission management.
Bridges Claude Desktop with Claude Code CLI to delegate complex coding tasks like creating React apps, building APIs, and debugging scripts while maintaining interaction through the Desktop interface.
This MCP server gives an AI coding host controlled, client-agnostic access to a local machine's developer capabilities: transactional file edits, shell and PTY execution, Git and project inspection, language-server operations, isolated browser automation, Windows UI automation, VS Code state, durable jobs, and checkpoints, all bounded by filesystem root allowlisting and resource admission controls. It speaks standard MCP over stdio, Streamable HTTP, and legacy HTTP+SSE, and can also run headless as a long-lived job runner without any hosted model vendor.
Enables cost-effective repository analysis, code search, file editing, and task planning by wrapping the cursor-agent CLI through focused tools. Reduces token usage by offloading heavy thinking tasks from Claude to specialized operations with configurable output formats.
Exposes Gemini CLI's built-in tools and external MCP proxies through a unified MCP endpoint while providing an OpenAI-compatible API for Gemini models. It features configurable security modes to safely manage file system operations, web searches, and shell command execution.
MCP server giving agents a persistent IPython workbench and a brokered RLM engine for durable, stateful computation. Offers 30 tools for bounded model calls, artifacts, and receipts with host-owned authority.