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Show HN: Dexto – Connect your AI Agents with real-world tools and data

The prompt

Hi HN, we’re the team at Truffle AI (YC W25), and we’ve been working on Dexto ( a runtime and orchestration layer for AI Agents that lets you turn any app, service or tool into an AI assistant that can reason, think and act. Here's a video walkthrough - We started working on Dexto after helping clients setup agents for everyday marketing tasks like posting on LinkedIn, running Reddit searches, generating ad creatives, etc. We realized that the LLMs weren’t the issue. The real drag was the repetitive orchestration around them: - wiring LLMs to tools - managing context and persistence - adding memory and approval flows - tailoring behavior per client/use case Each small project quietly ballooned into weeks of plumbing where each customer had mostly the same, but slightly custom requirement. So instead of another framework where you write orchestration logic yourself, we built Dexto as a top-level orchestration layer where you declare an agent’s capabilities and behavior: - which tools or MCPs the agent can use - which LLM powers it - how it should behave (system prompt, tone, approval rules) Once configured, the agent runs as an event-driven loop - reasoning through steps, invoking tools, handling retries, and maintaining its own state and memory. Your app doesn’t manage orchestration, it just triggers and subscribes to the agent’s events and decides how to render or approve outcomes. Agents can run locally, in the cloud, or hybrid. Dexto ships with a CLI, a web UI, and a few sample agents to get started. To show its flexibility, we wrapped some OpenCV functions into an MCP server and connected it to Dexto ( Now, a non-technical user could detect faces in images or create custom photo collages by talking to the agent. The same approach works for coding agents, browser agents, multi-speaker podcast agents, and marketing assistants tuned to your data.

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