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If you give an LLM access to your code, you write tools. A tool is a function plus what a model needs to call it: a name, a description, and a schema for the arguments. Then you write the same tools again. The first version uses the AI SDK's tool().
This is a submission for the Sanity Challenge, Path One: Ship an Agent That Queries Real Content What I Built Cybersecurity questions often have answers scattered across standards, vulnerability references, attack patterns, and mitigation guidance.
The associative half is easy to show in a few lines of Python. Store each note with the concepts it is about, count how often two concepts are written together, and let a read follow the strong pairs, so a question about timeouts brings back a note about backoff that never mentions a timeout.
This is a submission for the Sanity Challenge, Path One: Ship an Agent That Queries Real Content What I Built CanonKeeper is an AI-powered Fictional Universe Lore & Canon Resolution Engine.
Short answer: Model Context Protocol documentation is versioned by date, not by number. Each revision has its own specification pages, a schema published beside them, and a changelog recording what moved since the previous revision.
E-commerce platform Shopify has enabled browser-based AI agents to complete purchases on its merchants’ sites, taking the opposite approach to retailers such as Amazon and reportedly Adidas, which are blocking AI agents from buying on users’ behalf.
Join us at AGNTCon + MCPCon NA 2026, the premier event for people building, operating, researching, or supporting agent systems. Where developers, architects, and AI practitioners come together to explore the latest in agentic AI, tool protocols, and production-ready MCP architectures.
Join us at AGNTCon + MCPCon NA 2026, the premier event for people building, operating, researching, or supporting agent systems. Where developers, architects, and AI practitioners come together to explore the latest in agentic AI, tool protocols, and production-ready MCP architectures.
Connect a LangGraph agent to Apify through the official langchain-apify integration or Apify MCP Server, and give it real-time web search, scraping, and social media data.
I connected my Apify Actor to an AI agent over the Apify MCP server. It ran, returned data, and the data was garbage. Nothing was broken: every failure traced back to something my input schema never said. Four description rewrites later, the agent picks the right settings on its own.
Features, pricing, and crawl options side by side, plus a look at Firecrawl's new Alexandria library and when each platform is the better pick.
We define every agent in our software factory as code: orchestration, secrets, MCP servers, automations, runners, scorers, and benchmarks. Here’s a walkthrough of each part of the factory config.
Record a Tabstack Research request, preserve its cited pages, and check the answer against its sources with a Python review sheet.
Shadow AI is no longer just an employee opening ChatGPT without telling IT. Employees are using coding agents with personal API keys. Teams are connecting...
Your AI governance policy is a PDF. The agent that just approved the payment never opened it, and the dashboard that flagged the problem did...
Compare Google Jules and Octomind on async coding, daily caps, cloud VMs, model choice, persistence, integrations, pricing, and routines.
Building an agent is getting easier. More capable models and coding agents are making...
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