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    Enables structured extraction of methods and reproducibility heuristics from academic papers, allowing AI agents to obtain metadata, full text, structured methods, code repository discovery, and a no-clone reproducibility verdict from a paper URL.
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    35 PyPI
    MIT
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    Recommends study designs for a research question, states the identifying assumptions to verify, and returns runnable R, Python, or Julia code with a formatted citation for every source, drawn from methodological textbooks, an R package, and research articles on causal inference, econometrics, statistics, and machine learning.
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    MIT
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    Enables Claude Cowork on Windows to read, write, edit, list, find, and regex-search files inside a WSL distribution over stdio, accepting Windows and Linux path spellings. Access is confined to server-fixed roots, with secrets files refused, key-shaped strings redacted, and no delete or move operations.
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    MIT
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    Enables an AI assistant to reliably read and chunk PDF/text documents, validate extracted JSON against a schema with full error paths, and save structured output—all confined to a single allowed directory.
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    MIT
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    Enables MCP clients to extract tables and text from digital PDF invoices, bank statements, and bills into CSV, JSON, or Excel, with automatic PII redaction by default.
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    MIT
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    A local stdio MCP server for managing files on XServer via SFTP, enabling secure file operations, backups, and workspace management for XServer hosting.
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    MIT
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    Provides deterministic, schema-driven structured data extraction from PDF documents via regex/heuristic matching, enabling repeatable, inspectable, and cost-free field extraction without LLM API calls.
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    MIT
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    Enables extracting precise data from web pages by parsing the DOM with CSS selectors and returning structured JSON, while also offering tools to inspect page structure, discover candidate selectors, and verify them without loading full pages into context.
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    Extracts any Instagram post, reel, or multi-slide carousel and converts captions, OCR text, and metadata into structured screener filters such as PER, PBV, ROE, RSI, and volume for reusable IG-to-screener workflows.
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    MIT
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    Generates test files locally (images, PDFs, CSVs, corrupted files, etc.) from natural language prompts, with configurable sizes and safety limits.
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    MIT
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    Enables MCP clients to extract validated typed records from unstructured text using named schemas, with schema listing and extraction tools. It returns validated JSON or tool errors, optionally using an offline parser or an OpenAI-compatible model with retries on validation failures.
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    MIT
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    A lightweight MCP server for basic file operations, enabling reading, writing, and listing files securely via the Model Context Protocol.
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    Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.
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    44 PyPI
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    Apache 2.0
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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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    Enables local read-only access to TheRundown Product API data including sports, affiliates, market definitions, events, futures, and open main lines using your own API key.
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