This skill bridges Google A2A and OADP to make A2A agents discoverable and interoperable across open hubs.
- Trust
- Needs review
- Install
- MCP ready
- Top risk
- Medium risk · Important install, trust, or metadata evidence is still thin.
Find, trial, compare, and govern AI agents before hiring
Filter the market by role, protocol, source, trust, and evidence readiness. Open each profile before copying install payloads, running trials, or promoting a candidate.
This skill bridges Google A2A and OADP to make A2A agents discoverable and interoperable across open hubs.
This skill helps you interact with the MoltBot A2A Hub to register agents, search the registry, and relay messages.
This skill enables inter-agent communication by discovering agents, sending messages, managing tasks, streaming updates, and handling authenticated requests.
This skill enables autonomous AI agents to participate in A2H Market by negotiating, creating orders, and handling payments with human alignment.
This skill enables cryptographic identity for AI agents by generating keys, signing messages, and verifying signatures across agent communications.
This skill helps you explore and price AI agent services, find agents by skill, and template offerings to accelerate collaboration.
This skill helps you discover, hire, and receive payments from AI agents using the Agentic Money protocol on Ethereum.
Complete reference for running Agentica SDK with a local Claude proxy. This enables Python agents to use Claude CLI as their inference backend.
This skill helps you design and orchestrate autonomous AI agents with robust memory, planning, tool use, and multi-agent coordination for reliable outcomes.
This skill helps you build persistent, memory-enabled AI agents with the Letta API across Python and TypeScript, including multi-user and tool patterns.
This skill guides you in building and deploying AI agents with AWS Strands Agents SDK and Bedrock AgentCore, including architecture, observability, and
Cerebras API integration for building AI-powered applications with ultra-fast LLM inference. Use when working with Cerebras's Chat Completions API, Python SDK (cerebras_cloud_sdk), TypeScript SDK (@cerebras/cerebras_cloud_sdk), tool use/function calling, structured outputs with JSON schemas, reasoning models with thinking tokens, streaming responses, or any...
Candidate cards stay compact; complete records and profile resources stay linked here.
Use the links and review path below for filtered inventory records, review context, and finalist profile resources before action.
Crawlable resources that verify this page for AI answer engines and search crawlers.