Agno Integrations

Oxylabs is a market leader in web intelligence with enterprise-grade, ethical, and compliant solutions. Its proxy infrastructure spans one of the largest global networks, offering residential, ISP, mobile, datacenter, & dedicated datacenter proxies, along with Web Unblocker – an AI-driven tool that ensures block-free access to even the most protected sites. On the scraping tools side, the Oxylabs Web Scraper API manages every stage of large-scale data extraction. For dynamic, bot-protected websites, the Headless Browser ensures uninterrupted access. Oxylabs also offers AI Studio, which lets users extract data without writing code. The ready-made datasets provide structured data across industries such as e-commerce, real estate, and more – for data projects without custom scraping. In short, Oxylabs offers 177M+ IPs in 195 countries & is trusted by 4000+ clients worldwide, including Fortune 500 companies. Plus, the 24/7 customer service ensures clients get support when needed.

The core of extensible programming is defining functions. Python allows mandatory and optional arguments, keyword arguments, and even arbitrary argument lists. Whether you're new to programming or an experienced developer, it's easy to learn and use Python. Python can be easy to pick up whether you're a first-time programmer or you're experienced with other languages. The following pages are a useful first step to get on your way to writing programs with Python! The community hosts conferences and meetups to collaborate on code, and much more. Python's documentation will help you along the way, and the mailing lists will keep you in touch. The Python Package Index (PyPI) hosts thousands of third-party modules for Python. Both Python's standard library and the community-contributed modules allow for endless possibilities.

xpander.ai is a backend-as-a-service platform tailored for production-grade AI agents, offering developers a robust infrastructure that handles memory, tools, connectors, multi-agent workflows, triggering, state management, observability, and CI/CD pipelines without requiring infrastructure setup. Its visual AI agent workbench enables users to design, configure, simulate, test, and deploy agents interactively, complete with support for multi-agent collaboration, tool integrations, role-based access, and runtime governance. Developers can connect agents to SaaS or enterprise systems via AI-ready connectors, attach tool-compatible workflows, and monitor agent behavior with built-in observability and lifecycle tools. It supports deployment on hosted cloud infrastructure or within private VPCs, ensuring both agility and secure enterprise integration, and accelerates agent development from idea to production.

AG-UI is an open, lightweight, event-based protocol that standardizes how AI agents connect to user-facing applications. Built for simplicity and flexibility, it enables seamless integration between AI agents, real-time user context, and user interfaces. AG-UI is designed for agent-human interaction: during agent executions, backends emit events compatible with standard AG-UI event types, and agent backends can accept simple AG-UI-compatible inputs as arguments. It works with any event transport, including SSE, WebSockets, webhooks, and other streaming systems, while providing a flexible middleware layer that ensures compatibility across diverse environments. AG-UI brings agents into user-facing applications and complements the wider agentic protocol stack: MCP gives agents tools, A2A allows agents to communicate with other agents, and AG-UI connects agents directly to the user interface.

Dock is the AI workspace for you, your team, and every agent you run. It gives humans and AI agents the same shared cloud workspace, where everyone can read and write the same state in real time instead of working across scattered chats, files, and one-off outputs. Dock is built around tables with typed columns, rich-text docs, and agents as first-class identities, each with their own API keys, permissions, and audit trail rather than delegated human tokens. Teams can use Dock to plan, research, decide, and ship with humans and AI on the same surface, with use cases across engineering, go-to-market, research, operations, solo work, and agency workflows. Engineering teams can manage sprint planning, spec docs, and incident response; GTM teams can organize content calendars, sales pipelines, and customer success; research teams can track interviews, themes, and competitive intelligence; and operations teams can manage runbooks, recruiting, compliance, and onboarding.

Hindsight is an agent memory system built to create smarter AI agents that learn over time instead of starting every conversation from zero. Most agent memory systems focus on recalling conversation history, but Hindsight is focused on making agents learn, not just remember. It gives AI agents persistent long-term memory using biomimetic data structures, helping them retain facts, recall relevant context, and reflect on experience as part of reasoning. Hindsight is designed for agents that need to understand who a user is, what has been discussed, what preferences have emerged, what decisions were made, and how behavior should adapt across sessions. It provides three core operations: retain, recall, and reflect. Retain stores new information, recall retrieves the right memories when needed, and reflect helps agents synthesize observations, form mental models, and learn from prior interactions.

Ejentum is a reasoning harness for agentic AI, built as a structured reasoning layer that makes LLM agents more reliable, auditable, and disciplined during long or complex tasks. It works as a tool that an agent can call mid-task, returning the exact cognitive operation matched to the problem in front of it, so the agent can correct reasoning at inference time instead of relying only on static prompts. Ejentum is designed to stop AI agents from drifting, flattering, fabricating, locking into false hypotheses, stopping at shallow answers, or losing important context after several steps. It provides 679 abilities across four cognitive harnesses: reasoning, code, anti-deception, and memory. The reasoning harness channels analytical power across causality, time, space, simulation, abstraction, and metacognition, helping agents avoid surface-level pattern matching.

Gemini Managed Agents provides a visual way to prototype and learn how to build managed agents without having to create and write API calls. Managed agents on the Gemini API give developers a configurable agent harness where a single API call provisions a secure Linux sandbox for the agent to reason, execute code, manage files, and browse the web autonomously. In AI Studio Playground, users can switch to the Agents tab and start from pre-built templates that configure the base Antigravity Agent with tools, environment settings, instructions, and skills. The Antigravity Agent is a general-purpose managed agent powered by Gemini 3.5 Flash, able to run code, manage files, search the web, and be extended with custom instructions, skills, and data. Agent behavior, persona, and capabilities are defined through files in the environment, including AGENTS.md for system instructions and persona, and SKILL.md files for specific capabilities and workflows.