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"Understanding Sequential Thinking and Its Applications" matching MCP servers:

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    Enables document conversion between PDF, DOCX, and Markdown formats to facilitate reading and editing complex files in AI tools like Claude Desktop or Cursor. It utilizes marker-pdf and pandoc to provide structured text versions of documents, helping to manage context and support unsupported file types.
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    TheWeave is a markdown-native memory architecture for Claude and any MCP-aware agent. Your agent's memory lives as plain .md files you own: a 5-verb MCP core over the vault, query-driven PageRank retrieval, bi-temporal facts (valid_from / valid_until), and a persona-as-vault model. No database and no embeddings server. The files are the memory, inspectable in your editor and versionable in git.
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    Apache 2.0
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    A minimal server that provides Claude AI with secure file system access and sequential thinking capabilities, allowing Claude to navigate directories, read files, and break down complex problems into structured thinking steps.
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    Local MCP server that registers restricted Python filters and runs them against local JSON, YAML, and TXT files, enabling safe data filtering and file conversion.
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    MIT
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    Enables AI agents to deploy applications and manage servers over SSH using natural language commands, with built-in tools for Python bots, Docker Compose, and SSL setup.
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    MIT
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    MCP server that exposes agent-memory-daemon to any MCP-compatible client — Kiro (CLI & IDE), Claude Desktop, Cursor, and others. The daemon does the thinking (consolidation + extraction); this server is a thin filesystem bridge so agents can read, append, and search memory through the Model Context Protocol.
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    MIT
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    Enables AI assistants to parse and convert PDFs and images to structured text formats using the Doc2x v2 API. Supports asynchronous document processing, format conversion, and file downloads with configurable polling and timeout settings.
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    Parses PDF receipts to extract grocery and shopping expenses, automatically categorizes items using smart rules and LLM fallback, and stores them in a local SQLite database for querying purchase history and spending patterns.
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    A Model Context Protocol server that provides secure and intelligent interaction with files and filesystems, offering smart context management and token-efficient operations for working with large files and complex directory structures.
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    MIT
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    Enables LLM interaction with the Macau University of Science and Technology (M.U.S.T.) campus system, including automated login to Wemust and Moodle, retrieving class schedules, checking assignments and deadlines, downloading course materials, and managing course content.
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    MIT
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    MCP server that gives AI agents full vision and control over Android devices via ADB and scrcpy. Supports screenshots, input, apps, UI automation, shell, files, and clipboard.
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    MIT