How to Register and Publish an AI Agent: A Step-by-Step Guide

Why Registration Matters

An unregistered agent is invisible. No matter how good your agent is, if it's not listed on at least one registry, developers won't find it. Registration gives you discoverability, trust signals, and a permanent reference (like an ARD ID) that users can cite in documentation and integrations. This guide covers publishing to the three most impactful registries and getting indexed by AgentResourceDB.

Prerequisites

• A working AI agent with a defined API or interface.
• At least one protocol implementation: MCP (recommended), A2A, or ACP.
• Documentation: API reference, usage examples, and parameter descriptions.
• A hosting endpoint: cloud (AWS, Vercel, Hugging Face) or self-hosted with a public URL.
• Versioning: semantic version tags (v1.0.0) for your agent releases.

Step 1: Choose Your Protocol

Before registering, implement at least one communication protocol. MCP is the recommended starting point — it's supported by 10 of 15 registries and covers the most common use case (tool integration). If your agent collaborates with other agents, add A2A. If your team prefers REST, consider ACP.

Step 2: Publish to LangChain Hub

LangChain Hub is the fastest registry to publish to — no review process, community-driven, and supports both MCP and A2A. It's the best first stop for any agent.

• Create a LangChain Hub account at hub.langchain.com.
• Click 'Publish Agent' and select your framework (LangChain, CrewAI, AutoGen, or custom).
• Upload your agent definition file (Python or JSON configuration).
• Add metadata: name, description, category, supported protocols, and documentation URL.
• Add tags for discoverability (e.g., 'coding', 'mcp', 'code-review').
• Publish — your agent is immediately live and searchable.

Step 3: Publish to OpenAI GPT Store

The GPT Store has the largest audience (25,000+ agents) but requires OpenAI review. Your agent must use OpenAI models and pass content policy checks.

• Build your agent using the OpenAI Assistants API or GPT Builder.
• Navigate to chat.openai.com and open the GPT Builder.
• Configure your agent's instructions, capabilities, and MCP tool connections.
• Test thoroughly — OpenAI rejects agents that produce policy-violating outputs.
• Submit for review. Approval typically takes 3-7 days.
• Once approved, your agent appears in the GPT Store with OpenAI's verification badge.

Step 4: Publish to AWS Bedrock (Enterprise)

AWS Bedrock is the best registry for enterprise agents. It requires AWS certification but provides SOC 2 compliance and native AWS integration.

• Package your agent as an AWS Bedrock Agent using the Bedrock SDK.
• Define your agent's IAM roles, action groups, and knowledge bases.
• Implement MCP tool connections via AWS Lambda functions.
• Submit for AWS certification — this includes security scanning and compliance review.
• Certification takes 2-4 weeks but results in the highest trust signals.
• Once certified, your agent is available to all AWS Bedrock customers.

Step 5: Get Indexed by AgentResourceDB

AgentResourceDB automatically crawls all 15 registries, so your agent will be indexed within 24-48 hours of publishing to any connected registry. However, you can speed this up and ensure accurate metadata by submitting directly.

• Publish to at least one source registry (LangChain Hub, OpenAI, or AWS Bedrock).
• Ensure your agent's metadata (name, description, protocols, category) is complete and accurate.
• AgentResourceDB will crawl and index your agent automatically.
• Once indexed, your agent gets an ARD ID (e.g., ARD-10427) and a profile page with trust score.
• Monitor your agent's profile to track trust score factors and fix any issues.

Step 6: Maintain Your Agent

Registration isn't a one-time event. AgentResourceDB continuously monitors liveness and recalculates trust scores. To maintain a high score:

• Keep your agent online — uptime below 95% tanks your trust score.
• Update documentation when you change your API.
• Follow semantic versioning — breaking changes without version bumps hurt your versioning score.
• Respond to protocol updates — MCP and A2A specs evolve, and compliance tests check for the latest version.
• Monitor your agent's profile page on AgentResourceDB for trust score changes.

Common Registration Mistakes

• Incomplete metadata: Missing descriptions, categories, or protocol tags make your agent invisible in filtered searches.
• No documentation: Agents without docs score below 50 on documentation quality and get deprioritized in search results.
• Claiming protocol support you don't implement: AgentResourceDB's compliance tests will catch this, and your trust score will drop.
• Publishing to only one registry: Limits discoverability. Aim for at least 2-3 registries.
• Ignoring versioning: Without semantic versions, users can't pin stable versions and your versioning score suffers.

Once your agent is registered and indexed, browse the registry to see how it ranks against similar agents. Check your trust score breakdown and address any weak factors to climb the rankings.