Showing 4 open source projects for "smtp imap"

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  • 1
    OpenXP 5

    OpenXP 5

    OpenXP 5 - a multi-protocol offline mail and news reader

    OpenXP 5 is a multi-protocol offline mail and news reader for the text console, supporting internet email, Usenet, Fidonet, ZConnect, etc. It is based on OpenXP (https://sourceforge.net/p/openxp, currently inactive) which is based on CrossPoint (XP) by Peter Mandrella. OpenXP 5 is capable of establishing TLS encrypted connections to POP3, IMAP, SMTP and NNTP based servers and supports the new IPv6 protocol. see: http://de.wikipedia.org/wiki/CrossPoint http://svn.code.sf.net/p/openxp5...
    Downloads: 3 This Week
    Last Update:
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  • 2
    This is an open source Email client for Borland Delphi with source code. It uses Indy controls as well as PBears HTML Viewer Component and BSALA EmbeddedWB (updated versions for Delphi 2009 are here). It is IMAP, POP3, MAPI and SMTP compatible.
    Downloads: 14 This Week
    Last Update:
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  • 3
    eemailer is a free email client with IMAP, POP3 and local folder functionality. It has a built-in HTML3.2 compliant webbrowser and integrated SMTP engine. eemailer is completely written in delphi.
    Downloads: 1 This Week
    Last Update:
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  • 4
    Home Mail Server is intended to become a simple SMTP/POP/IMAP mail server which will encapsulate the following features:<br> 1. Ease of use/management<br> 2. DB backend<br> 3. Extended Aliasing<br> 4. Relay protection<br> 5. Virtual domains<br>
    Downloads: 0 This Week
    Last Update:
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  • Cloud data warehouse to power your data-driven innovation Icon
    Cloud data warehouse to power your data-driven innovation

    BigQuery is a serverless and cost-effective enterprise data warehouse that works across clouds and scales with your data.

    BigQuery Studio provides a single, unified interface for all data practitioners of various coding skills to simplify analytics workflows from data ingestion and preparation to data exploration and visualization to ML model creation and use. It also allows you to use simple SQL to access Vertex AI foundational models directly inside BigQuery for text processing tasks, such as sentiment analysis, entity extraction, and many more without having to deal with specialized models.
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