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    <title>PyPI recent updates for entroly</title>
    <link>https://pypi.org/project/entroly/</link>
    <description>Recent updates to the Python Package Index for entroly</description>
    <language>en</language>    <item>
      <title>0.8.5</title>
      <link>https://pypi.org/project/entroly/0.8.5/</link>
      <description>The token saving proxy and context compression engine for AI coding agents. Reduce LLM API costs by 80% while providing full codebase context to Cursor, Claude Code, and Copilot.</description>
<author>fastrunner10090@gmail.com</author>      <pubDate>Thu, 23 Apr 2026 14:30:50 GMT</pubDate>
    </item>    <item>
      <title>0.8.4</title>
      <link>https://pypi.org/project/entroly/0.8.4/</link>
      <description>The token saving proxy and context compression engine for AI coding agents. Reduce LLM API costs by 80% while providing full codebase context to Cursor, Claude Code, and Copilot.</description>
<author>fastrunner10090@gmail.com</author>      <pubDate>Thu, 23 Apr 2026 14:27:02 GMT</pubDate>
    </item>    <item>
      <title>0.8.1</title>
      <link>https://pypi.org/project/entroly/0.8.1/</link>
      <description>The token saving proxy and context compression engine for AI coding agents. Reduce LLM API costs by 80% while providing full codebase context to Cursor, Claude Code, and Copilot.</description>
<author>fastrunner10090@gmail.com</author>      <pubDate>Tue, 14 Apr 2026 02:45:39 GMT</pubDate>
    </item>    <item>
      <title>0.7.0</title>
      <link>https://pypi.org/project/entroly/0.7.0/</link>
      <description>The token saving proxy and context compression engine for AI coding agents. Reduce LLM API costs by 80% while providing full codebase context to Cursor, Claude Code, and Copilot.</description>
<author>fastrunner10090@gmail.com</author>      <pubDate>Sun, 12 Apr 2026 08:00:16 GMT</pubDate>
    </item>    <item>
      <title>0.6.5</title>
      <link>https://pypi.org/project/entroly/0.6.5/</link>
      <description>The token saving proxy and context compression engine for AI coding agents. Reduce LLM API costs by 80% while providing full codebase context to Cursor, Claude Code, and Copilot.</description>
<author>fastrunner10090@gmail.com</author>      <pubDate>Sat, 11 Apr 2026 20:33:55 GMT</pubDate>
    </item>    <item>
      <title>0.6.4</title>
      <link>https://pypi.org/project/entroly/0.6.4/</link>
      <description>Information-theoretic context optimization for AI coding agents. Knapsack-optimal token budgeting, Shannon entropy scoring, SimHash dedup, predictive pre-fetch. MCP server.</description>
<author>fastrunner10090@gmail.com</author>      <pubDate>Sun, 05 Apr 2026 14:55:06 GMT</pubDate>
    </item>    <item>
      <title>0.6.3</title>
      <link>https://pypi.org/project/entroly/0.6.3/</link>
      <description>Information-theoretic context optimization for AI coding agents. Knapsack-optimal token budgeting, Shannon entropy scoring, SimHash dedup, predictive pre-fetch. MCP server.</description>
<author>fastrunner10090@gmail.com</author>      <pubDate>Fri, 03 Apr 2026 05:46:31 GMT</pubDate>
    </item>    <item>
      <title>0.6.2</title>
      <link>https://pypi.org/project/entroly/0.6.2/</link>
      <description>Information-theoretic context optimization for AI coding agents. Knapsack-optimal token budgeting, Shannon entropy scoring, SimHash dedup, predictive pre-fetch. MCP server.</description>
<author>fastrunner10090@gmail.com</author>      <pubDate>Sun, 29 Mar 2026 06:30:57 GMT</pubDate>
    </item>    <item>
      <title>0.6.1</title>
      <link>https://pypi.org/project/entroly/0.6.1/</link>
      <description>Information-theoretic context optimization for AI coding agents. Knapsack-optimal token budgeting, Shannon entropy scoring, SimHash dedup, predictive pre-fetch. MCP server.</description>
<author>fastrunner10090@gmail.com</author>      <pubDate>Sun, 29 Mar 2026 05:40:59 GMT</pubDate>
    </item>    <item>
      <title>0.6.0</title>
      <link>https://pypi.org/project/entroly/0.6.0/</link>
      <description>Information-theoretic context optimization for AI coding agents. Knapsack-optimal token budgeting, Shannon entropy scoring, SimHash dedup, predictive pre-fetch. MCP server.</description>
<author>fastrunner10090@gmail.com</author>      <pubDate>Sun, 29 Mar 2026 02:05:11 GMT</pubDate>
    </item>    <item>
      <title>0.5.4</title>
      <link>https://pypi.org/project/entroly/0.5.4/</link>
      <description>Information-theoretic context optimization for AI coding agents. Knapsack-optimal token budgeting, Shannon entropy scoring, SimHash dedup, predictive pre-fetch. MCP server.</description>
<author>fastrunner10090@gmail.com</author>      <pubDate>Sun, 15 Mar 2026 21:10:48 GMT</pubDate>
    </item>    <item>
      <title>0.5.3</title>
      <link>https://pypi.org/project/entroly/0.5.3/</link>
      <description>Information-theoretic context optimization for AI coding agents. Knapsack-optimal token budgeting, Shannon entropy scoring, SimHash dedup, predictive pre-fetch. MCP server.</description>
<author>fastrunner10090@gmail.com</author>      <pubDate>Sun, 15 Mar 2026 20:58:18 GMT</pubDate>
    </item>    <item>
      <title>0.5.2</title>
      <link>https://pypi.org/project/entroly/0.5.2/</link>
      <description>Information-theoretic context optimization for AI coding agents. Knapsack-optimal token budgeting, Shannon entropy scoring, SimHash dedup, predictive pre-fetch. MCP server.</description>
<author>fastrunner10090@gmail.com</author>      <pubDate>Sun, 15 Mar 2026 20:49:24 GMT</pubDate>
    </item>    <item>
      <title>0.5.1</title>
      <link>https://pypi.org/project/entroly/0.5.1/</link>
      <description>Information-theoretic context optimization for AI coding agents. Knapsack-optimal token budgeting, Shannon entropy scoring, SimHash dedup, predictive pre-fetch. MCP server.</description>
<author>fastrunner10090@gmail.com</author>      <pubDate>Sun, 15 Mar 2026 20:45:44 GMT</pubDate>
    </item>    <item>
      <title>0.5.0</title>
      <link>https://pypi.org/project/entroly/0.5.0/</link>
      <description>Information-theoretic context optimization for AI coding agents. Knapsack-optimal token budgeting, Shannon entropy scoring, SimHash dedup, predictive pre-fetch. MCP server.</description>
<author>fastrunner10090@gmail.com</author>      <pubDate>Sun, 15 Mar 2026 20:43:34 GMT</pubDate>
    </item>    <item>
      <title>0.4.9</title>
      <link>https://pypi.org/project/entroly/0.4.9/</link>
      <description>Information-theoretic context optimization for AI coding agents. Knapsack-optimal token budgeting, Shannon entropy scoring, SimHash dedup, predictive pre-fetch. MCP server.</description>
<author>fastrunner10090@gmail.com</author>      <pubDate>Sun, 15 Mar 2026 20:40:52 GMT</pubDate>
    </item>    <item>
      <title>0.4.8</title>
      <link>https://pypi.org/project/entroly/0.4.8/</link>
      <description>Information-theoretic context optimization for AI coding agents. Knapsack-optimal token budgeting, Shannon entropy scoring, SimHash dedup, predictive pre-fetch. MCP server.</description>
<author>fastrunner10090@gmail.com</author>      <pubDate>Sun, 15 Mar 2026 20:26:44 GMT</pubDate>
    </item>    <item>
      <title>0.4.7</title>
      <link>https://pypi.org/project/entroly/0.4.7/</link>
      <description>Information-theoretic context optimization for AI coding agents. Knapsack-optimal token budgeting, Shannon entropy scoring, SimHash dedup, predictive pre-fetch. MCP server.</description>
<author>fastrunner10090@gmail.com</author>      <pubDate>Sun, 15 Mar 2026 20:19:32 GMT</pubDate>
    </item>    <item>
      <title>0.4.6</title>
      <link>https://pypi.org/project/entroly/0.4.6/</link>
      <description>Information-theoretic context optimization for AI coding agents. Knapsack-optimal token budgeting, Shannon entropy scoring, SimHash dedup, predictive pre-fetch. MCP server.</description>
<author>fastrunner10090@gmail.com</author>      <pubDate>Sun, 15 Mar 2026 10:11:12 GMT</pubDate>
    </item>    <item>
      <title>0.4.5</title>
      <link>https://pypi.org/project/entroly/0.4.5/</link>
      <description>Information-theoretic context optimization for AI coding agents. Knapsack-optimal token budgeting, Shannon entropy scoring, SimHash dedup, predictive pre-fetch. MCP server.</description>
<author>fastrunner10090@gmail.com</author>      <pubDate>Sun, 15 Mar 2026 09:55:17 GMT</pubDate>
    </item>    <item>
      <title>0.4.4</title>
      <link>https://pypi.org/project/entroly/0.4.4/</link>
      <description>Information-theoretic context optimization for AI coding agents. Knapsack-optimal token budgeting, Shannon entropy scoring, SimHash dedup, predictive pre-fetch. MCP server.</description>
<author>fastrunner10090@gmail.com</author>      <pubDate>Sun, 15 Mar 2026 08:59:08 GMT</pubDate>
    </item>    <item>
      <title>0.3.2</title>
      <link>https://pypi.org/project/entroly/0.3.2/</link>
      <description>Information-theoretic context optimization for AI coding agents. Knapsack-optimal token budgeting, Shannon entropy scoring, SimHash dedup, predictive pre-fetch. MCP server.</description>
<author>fastrunner10090@gmail.com</author>      <pubDate>Sun, 15 Mar 2026 08:58:09 GMT</pubDate>
    </item>    <item>
      <title>0.4.3</title>
      <link>https://pypi.org/project/entroly/0.4.3/</link>
      <description>Information-theoretic context optimization for AI coding agents. Knapsack-optimal token budgeting, Shannon entropy scoring, SimHash dedup, predictive pre-fetch. MCP server.</description>
<author>fastrunner10090@gmail.com</author>      <pubDate>Fri, 13 Mar 2026 07:09:53 GMT</pubDate>
    </item>    <item>
      <title>0.4.2</title>
      <link>https://pypi.org/project/entroly/0.4.2/</link>
      <description>Information-theoretic context optimization for AI coding agents. Knapsack-optimal token budgeting, Shannon entropy scoring, SimHash dedup, predictive pre-fetch. MCP server.</description>
<author>fastrunner10090@gmail.com</author>      <pubDate>Fri, 13 Mar 2026 07:04:55 GMT</pubDate>
    </item>    <item>
      <title>0.4.1</title>
      <link>https://pypi.org/project/entroly/0.4.1/</link>
      <description>Information-theoretic context optimization for AI coding agents. Knapsack-optimal token budgeting, Shannon entropy scoring, SimHash dedup, predictive pre-fetch. MCP server.</description>
<author>fastrunner10090@gmail.com</author>      <pubDate>Fri, 13 Mar 2026 06:52:55 GMT</pubDate>
    </item>    <item>
      <title>0.4.0</title>
      <link>https://pypi.org/project/entroly/0.4.0/</link>
      <description>Information-theoretic context optimization for AI coding agents. Knapsack-optimal token budgeting, Shannon entropy scoring, SimHash dedup, predictive pre-fetch. MCP server.</description>
<author>fastrunner10090@gmail.com</author>      <pubDate>Wed, 11 Mar 2026 04:42:12 GMT</pubDate>
    </item>    <item>
      <title>0.3.1</title>
      <link>https://pypi.org/project/entroly/0.3.1/</link>
      <description>Information-theoretic context optimization for AI coding agents. Knapsack-optimal token budgeting, Shannon entropy scoring, SimHash dedup, predictive pre-fetch. MCP server.</description>
<author>fastrunner10090@gmail.com</author>      <pubDate>Sat, 07 Mar 2026 23:42:51 GMT</pubDate>
    </item>    <item>
      <title>0.3.0</title>
      <link>https://pypi.org/project/entroly/0.3.0/</link>
      <description>Information-theoretic context optimization for AI coding agents. Knapsack-optimal token budgeting, Shannon entropy scoring, SimHash dedup, predictive pre-fetch. MCP server.</description>
<author>fastrunner10090@gmail.com</author>      <pubDate>Sat, 07 Mar 2026 22:11:05 GMT</pubDate>
    </item>    <item>
      <title>0.2.1</title>
      <link>https://pypi.org/project/entroly/0.2.1/</link>
      <description>Information-theoretic context optimization for AI coding agents. Knapsack-optimal token budgeting, Shannon entropy scoring, SimHash dedup, predictive pre-fetch. MCP server.</description>
<author>fastrunner10090@gmail.com</author>      <pubDate>Sat, 07 Mar 2026 21:12:07 GMT</pubDate>
    </item>    <item>
      <title>0.2.0</title>
      <link>https://pypi.org/project/entroly/0.2.0/</link>
      <description>Information-theoretic context optimization for AI coding agents. Knapsack-optimal token budgeting, Shannon entropy scoring, SimHash dedup, predictive pre-fetch. MCP server.</description>
<author>fastrunner10090@gmail.com</author>      <pubDate>Sat, 07 Mar 2026 21:04:34 GMT</pubDate>
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