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35,708 results · Page 132 of 992

Keenious

AI search

Keenious is an AI-assisted tool for academic research that recommends relevant scholarly literature based on the text the user is writing. It works in Microsoft Word, Google Docs, and the browser, helping users find real published research, understand paper content, and grasp the overall landscape of a field. It supports interaction in nearly 100 languages, covers more than 250 million scholarly works, and its database is updated monthly. It provides AI-driven explanations of complex methodologies, statistical concepts, and specialized terminology, and users can highlight text to ask questions. The free version has message and conversation limits, while the Plus version has practically unlimited use. PDF uploads are limited to 20MB, and files and conversations are automatically deleted after 1 day. Institutional licenses are offered for universities and organizations, with support for link resolver integrations such as EBSCO and PRIMO.

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keep-mcp

AI developer platforms

keep-mcp is an MCP (Model Context Protocol) server for Google Keep, developed by feuerdev and open-sourced on GitHub. It connects to Google Keep's unofficial private API through gkeepapi, enabling AI clients that support MCP to query, create, update, and manage Google Keep notes. The main tools include: searching and reading notes (find, get_note), creating and updating notes and lists (create_note, create_list, update_note, add_list_item, etc.), note state management (setting color, pinning, archiving, trashing, restoring, deleting), label and collaborator management, and media attachment listing and downloading. By default, all destructive and modifying operations are limited to notes created by this server (those with the keep-mcp label), and this restriction can be bypassed by setting UNSAFE_MODE to true. Before use, you need to configure the GOOGLE_EMAIL and GOOGLE_MASTER_TOKEN credentials, and obtain the master token through a browser-assisted flow. The project provides a Makefile to support local development, unit testing, and smoke testing with a real account, and automatically publishes to PyPI via GitHub Actions.

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