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    attendance-engine-mcp is a Model Context Protocol server that gives AI agents deterministic, fixture-backed tools for workforce attendance and wage-and-hour compliance. Built on @attendance-engine/core — a pure-function, zero-deps, 100%-covered TypeScript engine — it lets Claude, Cursor, Windsurf, or any MCP host correctly answer the questions HR/payroll teams actually ask: did this person clock i
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    Enables MCP clients to turn Make blueprints and Zapier exports into n8n workflow files, with a per-step report of what converted, what to review, and what must be finished by hand. Also lists zaps, explains how individual steps are handled, checks workflow files for broken links or placeholders, and can upload the result to an n8n instance as an inactive workflow.
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    MIT
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    Deterministic Markdown-to-Word (.docx) publishing compiler with native OMML equations, three-line tables, CSL citations, and quality gates for AI agents.
    1,607 PyPI
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    MIT
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    A local MCP server that uses Word COM automation to perform tasks python-docx cannot, such as computing field/TOC values, counting real pages, rendering high-fidelity PDFs, converting/repairing legacy formats, producing redline comparisons, and running native mail merge.
    MIT
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    Enables AI agents to convert GitHub Flavored Markdown into formatted Word (.docx) files, including headings, lists, tables, links, code and images, with an optional Chinese official document (公文) font preset. Conversion runs locally, so no content is uploaded.
    271 npm
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    Enables converting a direct HTTPS document link into an editable slide deck while keeping charts, images, and shapes as background visuals, with job tracking and file download.
    AGPL 3.0
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    Enables Claude to create, read, update and delete Microsoft To Do lists, tasks and checklist items, and Microsoft Planner plans, buckets and tasks, through Microsoft Graph as the signed-in user. Lists, plans and buckets can be referenced by ID or exact name, with destructive deletes requiring confirmation.
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    MIT
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    Lets Claude and other AI clients read and modify Microsoft To Do through natural language, adding, completing, searching, updating, and deleting tasks and sub-steps by title and list name instead of ids. Personal Microsoft accounts need no Azure app registration — a single device-code sign-in grants access, with optional read-only and no-delete modes available.
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    MIT
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    Enables AI agents to read Figma designs and modify them programmatically, including creating and styling elements, editing text, managing layout and components, exporting images, and working with annotations and prototype connections.
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    Enables users to manage a personal to-do list backed by SQLite, adding single or multiple tasks, listing incomplete tasks, renaming or updating task status, and marking tasks complete. All state persists in a local database created automatically on first run.
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    What is PandaDoc MCP? PandaDoc MCP (Model Context Protocol) server connects AI agents directly to PandaDoc's document workflow — creating, sending, and tracking contracts and agreements without leaving your AI client. How to use PandaDoc MCP? To use PandaDoc MCP, connect your PandaDoc account, provide the required API credentials, and configure the appropriate MCP client.
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    MIT
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    Enables agents to break high-level business objectives into dependency-ordered sub-task graphs and then directly generate the finished deliverables, such as financial spreadsheets, executive presentations, and analytical reports. It runs as a zero-dependency Python MCP server over JSON-RPC stdio, adding deterministic authorization, role-boundary validation, and telemetry.
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    MIT