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                        <id>https://phptoptens.com/authors/tom-herrmann/feed</id>
                                <link href="https://phptoptens.com/authors/tom-herrmann/feed" rel="self"></link>
                                <title><![CDATA[Artisan Weekly — Author Feed]]></title>
                    
                                <subtitle>Featured links for a given author across Artisan Weekly editions.</subtitle>
                                                    <updated>2026-09-17T14:38:48+01:00</updated>
                        <entry>
            <title><![CDATA[Building an MCP Server for Archivist AI with Laravel]]></title>
            <link rel="alternate" href="https://gummibeer.dev/blog/2026/building-myarchivist-mcp" />
            <id>https://gummibeer.dev/blog/2026/building-myarchivist-mcp</id>
            <author>
                <name><![CDATA[Tom Herrmann]]></name>
                <email><![CDATA[hello@example.com]]></email>

            </author>
            <summary type="html">
                <![CDATA[Tom Herrmann explores the technical implementation of building a Model Context Protocol (MCP) server for Archivist AI using Laravel, covering the evolution from a simple read-only API wrapper to a secure OAuth-authenticated system that integrates campaign data with AI tools like Cursor and ChatGPT.]]>
            </summary>
                                    <updated>2026-09-17T14:38:48+01:00</updated>
        </entry>
            <entry>
            <title><![CDATA[Logarithmic auto-scaling for Laravel Horizon]]></title>
            <link rel="alternate" href="https://gummibeer.dev/blog/2026/logarithmic-auto-scaling-laravel-horizon" />
            <id>https://gummibeer.dev/blog/2026/logarithmic-auto-scaling-laravel-horizon</id>
            <author>
                <name><![CDATA[Tom Herrmann]]></name>
                <email><![CDATA[hello@example.com]]></email>

            </author>
            <summary type="html">
                <![CDATA[Explore a sophisticated approach to optimising Laravel Horizon's worker allocation using logarithmic scaling, which intelligently balances queue workloads with vastly different arrival patterns and sizes to prevent worker starvation on high-throughput queues.]]>
            </summary>
                                    <updated>2026-09-17T14:28:28+01:00</updated>
        </entry>
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