daniel3303

daniel3303 / AgentQL

Public

Reusable .NET library that translates EF Core models into LLM-friendly schema descriptions and provides safe SQL query execution for AI agents.

danielapoliveira.com agentic ai ai-agents ai-tools anthropic
16
1
100% credibility
Found Mar 05, 2026 at 16 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
C#
AI Summary

AgentQL is a .NET library with a demo chat app that allows AI assistants to understand and safely query databases using natural language.

How It Works

1
🕵️ Discover AgentQL

You hear about a handy tool that lets smart assistants chat with your stored information to answer questions naturally.

2
📦 Try the example app

You grab the ready-to-go example travel booking chat and set it up quickly on your computer.

3
💬 Start chatting

Open the friendly chat window and ask simple questions like 'Who has gold loyalty status?' to see magic answers from the data.

4
🔗 Connect your data

Point it to your own collection of info so the assistant knows your specific details like customers or sales.

5
🤖 Link a smart helper

Hook up a thinking service like an AI brain so it understands and pulls the right info safely.

6
⚙️ Tweak safety rules

Set limits like how much info to show at once to keep everything secure and under control.

🎉 Enjoy smart queries

Now anyone can ask everyday questions and get spot-on answers from your data without complicated searches.

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AI-Generated Review

What is AgentQL?

AgentQL is a free C# library for .NET devs using EF Core, turning your DbContext models into clean, LLM-readable schema descriptions complete with tables, relationships, enums, and custom notes. It lets AI agents query your database via safe SQL execution—row limits, timeouts, read-only transactions—with tools plugged into Microsoft.Extensions.AI for providers like OpenAI, Anthropic, or Ollama. Setup is one DI call, and it ships as NuGet packages with a Blazor demo app and Docker support for quick agentql tutorial spins.

Why is it gaining traction?

Unlike agentql alternatives forcing manual schema prompts or risky raw SQL, AgentQL auto-generates precise descriptions from your EF models and wraps queries in safeguards, cutting hallucination risks. The agentql api hooks seamlessly into chat clients for natural "ask your data" flows, with fluent config and attributes to hide sensitive fields. Devs dig the agentql docs clarity and agentql reddit buzz around its minimal boilerplate versus building custom agent login or query layers.

Who should use this?

Backend .NET engineers prototyping AI chatbots over EF Core databases, like internal travel booking tools or customer analytics agents. Teams exploring agentql ai for read-heavy LLM apps, skipping brittle prompt engineering. Avoid if you need production writes or non-EF data sources.

Verdict

Solid for experiments—1.0% credibility score reflects 16 stars and early maturity, but excellent agentql docs, runnable demo, and MIT license make it worth a test over heavier reusable github actions workflows. Pair with github reusable workflow examples for CI if scaling agentql free setups.

(198 words)

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