Already have a useful Python package on PyPI? This step-by-step guide walks you through converting it into a portable, verified agent skill using the ANP format — unlocking discovery, cross-framework compatibility, and monetization.
Step-by-step guide to importing your existing LangChain tools to AgentNode. Gain verification, discovery, and monetization for your tools without rewriting them. Includes code examples, testing workflow, and before/after comparison.
Learn how to write tests that maximize your AgentNode verification score. Covers test structure, unit vs integration tests, mock strategies, and tips for reaching Gold tier.
Your MCP server works locally but nobody can find it. This step-by-step guide takes you from local MCP tool to globally discoverable, verified agent skill — with code examples, manifest templates, and tips for maximizing your trust score.
By the end of this tutorial, you'll have a working MCP server — tested, verified, and discoverable by every Claude and Cursor user.
Your verification score determines how much agents trust your package. Learn how to write tests that push your score into Gold tier.
Complete reference for the ANP manifest.yaml format. Every field explained with examples, including multi-tool packages, permissions, and runtime configuration.
Everything you need to know about publishing an ANP package to AgentNode — from project structure and manifest writing to verification and scoring.
Already have tools built with LangChain, MCP, OpenAI, or CrewAI? The AgentNode Import tool converts them into portable ANP packages in seconds.
Use the AgentNode Builder to describe what your AI tool does and get a complete, publishable ANP package in minutes — no boilerplate required.