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    Sandboxed Python execution with automatic dependency management. Executes Python scripts in isolated environments (bubblewrap or Docker) with PEP 723 inline dependencies, preventing host pollution.
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    53 PyPI
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    MIT
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    Provides CodeQL language intelligence to AI agents via MCP, enabling completions, hover, definitions, references, diagnostics, formatting, and in-memory file updates for QL code.
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    MIT
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    An MCP-powered AI agent that audits your Gmail for recurring subscriptions, detects silent price increases, and flags unused services.
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    MIT
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    Code-mode MCP server (docs_search + execute_code two-tool surface) backed by a unified capability manifest across three sandbox kernels (in-process node:vm, WASM via QuickJS / Pyodide / Wasmtime, and remote microVM via E2B / Cloudflare Sandbox). At N=30 tools the bootstrap-context cost drops to 13.6% of direct tool-use. Apache-2.0.
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    Apache 2.0
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    An MCP server that reads a clinical note and returns ranked ICD-10-CM diagnosis code candidates with clinical reasoning, validated against official CMS coding constraints.
    2
    31 npm
    MIT
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    An MCP server that enables LLMs to execute Python code on GPU-accelerated compute nodes within SLURM-managed HPC environments. It bridges local clients to remote clusters by launching JupyterLab sessions via SLURM jobs to facilitate high-performance notebook-based computation.
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    A Python MCP server that enables AI assistants to manage Todoist tasks and projects through the Model Context Protocol. It supports full CRUD operations for tasks and projects, including support for nested projects and Todoist's advanced filter syntax.
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    MIT
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    A Python MCP server that provides language models full read/write access to a Node-RED instance through its Admin HTTP API, enabling flow management with structured Pydantic responses and incremental patching.
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    Automates competitive research for startup ideas by executing a 7-step pipeline including idea understanding, competitor discovery, profile extraction, feature comparison, market gap analysis, innovation scoring, and report generation.
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    MIT
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    A Model Context Protocol server framework featuring dynamic tool loading and automatic tool discovery from a dedicated directory. It leverages FastMCP to provide a robust environment for building, configuring, and testing individual Python-based tools.
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    A Model Context Protocol server built with FastMCP that enables dynamic tool loading and configuration from individual Python files. It provides a flexible framework for automatically discovering, testing, and running tools via Stdio or HTTP transport modes.
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