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    An MCP-powered AI agent that audits your Gmail for recurring subscriptions, detects silent price increases, and flags unused services.
    6
    MIT
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    A Model Context Protocol server built with FastMCP that provides tools for retrieving the current local date and time. It allows LLMs to access precise temporal information directly from the host environment.
    9
    MIT
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    Bridges a local AI agent to a Colab session in the browser, enabling code execution and file operations through the Model Context Protocol.
    9
    Apache 2.0
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    Turns any MCP host into a finance & tax copilot for Indian taxpayers, using live keyless data and deterministic advisory.
    16
    MIT
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    Enables AI assistants to perform defensive security tasks such as vulnerability detection, CVE lookup, phishing/link safety checks, and security report generation via MCP tools.
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    An MCP server that fetches web pages and extracts clean, AI-friendly Markdown content using Mozilla Readability. It provides secure web access for LLMs with built-in SSRF protection and automated content cleaning for improved context retrieval and summarization.
    1
    70 npm
    MIT
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    An MCP server that provides deterministic unit conversions backed by Pint, enabling exact unit conversions, compatibility checks, and parsing of quantities for LLMs.
    5
    MIT
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    Production-ready MCP server that provides LLMs with essential random generation abilities, including random integers, floats, choices, shuffling, and cryptographically secure tokens.
    7
    57 PyPI
    51
    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 starter template for building calculator-focused MCP servers using NitroStack, including tools, resources, and prompts.
    6
    47 npm
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    Enables users to connect their own YNAB account via OAuth and work with their budgets through natural language — reviewing plans, months, accounts, categories, payees, transactions, scheduled transactions, and money movements, plus writing changes such as creating, approving, recategorizing, or deleting transactions, assigning funds to categories, and moving money between them. It also adds read-only summaries for catching unapproved transactions and overspending, analyzing spending, tracking goal funding, and forecasting cash flow.
    35
    MIT