AI-Chain

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Explore the Latest Trends and Practical Tips in AI Applications

Hands-On with GitHub MCP Server: Connecting AI Agents to Repositories, Issues, and Pull Requests with a Minimal Toolset

Hands-On with GitHub MCP Server: Connecting AI Agents to Repositories, Issues, and Pull Requests with a Minimal Toolset

How does GitHub’s official github-mcp-server expose repository, issue, pull request, and CI/CD capabilities to AI agents through MCP? Starting with remote and local deployment, minimal toolsets, read-only access, and lockdown mode, this article outlines a practical engineering workflow that prioritizes clear permission boundaries.
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D3.js Is More Than Charts: Building Interactive Visualizations with Data Binding

D3.js Is More Than Charts: Building Interactive Visualizations with Data Binding

D3.js is not a component library that drops data into fixed chart templates; it is a low-level set of visualization tools built on web standards. Drawing on the d3/d3 module structure and official examples, this article explains how data binding, scales, shape generation, and interaction updates fit together, with a runnable SVG example to show where D3.js is a good fit—and when a higher-level charting solution is preferable.
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Stop Choosing Models by Feel: Turn LLM Evaluation, Red Teaming, and CI into a Repeatable Workflow with Promptfoo

Stop Choosing Models by Feel: Turn LLM Evaluation, Red Teaming, and CI into a Repeatable Workflow with Promptfoo

The hardest part of maintaining an LLM application is often not connecting a model, but knowing why answer quality changed. Promptfoo brings prompts, models, test cases, assertions, and red-team scans into one CLI and library workflow, so model comparisons, regression tests, and security checks can run locally and in CI/CD. This article builds a practical evaluation process and explains where Promptfoo fits, how to adopt it, and what limitations still require engineering judgment.
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