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    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.
    6
    MIT
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    Provides workspace-scoped file operations and command execution tools for building Cursor-style agents, along with system prompts and tool definitions for LLM integration.
    5
    MIT
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    Enables integration of Perplexity's AI API with LLMs, delivering advanced chat completion by utilizing specialized prompt templates for tasks like technical documentation, code review, and API documentation.
    1
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    MIT
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    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.
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    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.
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    Enable Claude (or any other LLM) to interactively debug your code (set breakpoints and evaluate expressions in stack frame). It's language-agnostic, assuming debugger console support and valid launch.json for debugging in VSCode.
    53
    514
    MIT
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    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.
    2
    Apache 2.0
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    A lightweight and fast MCP server that enables AI agents to efficiently discover and execute tools through progressive disclosure, minimizing context consumption while supporting safe code execution in external environments.
    12
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    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.
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    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.
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    Enables offline AI agent automation with embedded local LLM (Qwen 2.5), sandboxed file operations through AgentFS, and dynamic skill loading. Exposes capabilities via MCP with tri-state safety guards for private, air-gapped environments without network connectivity or API costs.
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    An advanced MCP server that provides an agentic interface to Google's Gemini 3.1 models via Vertex AI, combining real-time Google Search, URL analysis, and Python code execution to solve complex multi-step research and data tasks.
    1
    MIT