Current focus
Podcast 01
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AgentsOnly
Building the trust layer for the agentic economy
AgentsOnly is a structured reputation layer for AI agents, designed to solve trust, discovery, and reliability challenges as autonomous systems begin transacting across APIs, services, and human marketplaces in the emerging agentic economy.
Challenge
Agents lack reliable ways to evaluate services, forcing them to depend on human designed interfaces that introduce ambiguity, friction, and frequent execution failures.
Outcome
AgentsOnly enables agents to query trusted services programmatically, improving reliability, reducing failed workflows, and establishing a shared standard for agent ready infrastructure.
01
Discovery
Observing rapid growth of OpenClaw revealed agents could act, but lacked trust signals, creating fragmentation and inconsistent outcomes across services.
02
Build
Defined a machine readable registry, certification tiers, and API first architecture so agents can discover, evaluate, and select services without relying on human interfaces.
03
Launch
Released a public API and MCP endpoint, enabling agents to query services directly and validate capabilities through standardized schemas and certification signals.
Notes
The emergence of agentic systems is shifting how software interacts with the internet. Agents are no longer passive tools. They initiate actions, coordinate workflows, and increasingly transact with external services. This shift exposes a structural weakness in the current ecosystem.
Most of the internet is still designed for humans.
"Agents can act, but without trust, they cannot operate reliably."
Services rely on landing pages, dashboards, and authentication flows that assume a human decision maker. Even when APIs exist, they are often inconsistently documented, lack standard schemas, and provide no clear signal of reliability. For an agent, this creates uncertainty at every step of execution.
The problem becomes more visible as agent frameworks like OpenClaw accelerate adoption. Agents can orchestrate complex workflows, but they cannot determine which services are trustworthy. Discovery becomes guesswork. Execution becomes fragile. Failure rates increase.
This is not a tooling problem. It is an infrastructure gap.
Agents require a different model of discovery. They need structured, machine readable information that describes what a service does, how it can be used, and whether it can be trusted. Without this layer, agents operate in an environment that was never designed for them.
AgentsOnly addresses this by introducing a reputation layer built specifically for agents. Instead of browsing, agents query. Instead of interpreting marketing content, they consume structured data. Each service in the registry is described using a standardized schema that includes capabilities, endpoints, and readiness signals.
The certification system provides an additional layer of clarity. Services are evaluated and categorized based on their ability to support autonomous workflows. This transforms trust from an implicit assumption into an explicit signal that agents can use in decision making.
The system is intentionally API first. Agents interact with the registry through a public endpoint or MCP connection, retrieving a consistent representation of available services. There are no barriers to read access, no need for scraping, and no reliance on undocumented behavior.
This approach shifts discovery from a human centered experience to a machine optimized process. Agents can compare services, select appropriate tools, and execute workflows with greater confidence.
The broader implication is that trust becomes a foundational layer of the agentic economy. As more services adapt to agent driven interaction, the need for standardized evaluation will increase. Platforms that provide this layer may become essential infrastructure.
AgentsOnly is an early step in defining that standard. Whether it becomes widely adopted or fragmented across ecosystems remains uncertain. The challenge is not only technical but also behavioral, requiring services to design for agents as first class users.
The gap, however, is clear. Agents can act, but without trust, they cannot operate reliably.
Q&A
What is AgentsOnly?
AgentsOnly is a structured reputation and discovery layer for AI agents, designed to help them find, evaluate, and trust services in the agentic economy.
What problem does it solve?
It solves the trust gap agents face when interacting with services that were designed for humans, where discovery is unclear, APIs are inconsistent, and reliability signals are missing.
Why can't agents just use existing websites and APIs?
Most services assume a human user and expose information through interfaces, docs, and workflows that agents cannot reliably interpret or validate. Even available APIs often lack standardized schemas and trust metadata.
How does AgentsOnly work?
Agents query a registry of services described through standardized, machine-readable schemas that include capabilities, endpoints, and certification signals, either through a public API or an MCP endpoint.
What are the certification tiers for?
They turn trust into an explicit signal by categorizing how well a service supports autonomous workflows, making it easier for agents to compare options and select reliable tools.
Why does this matter for the agentic economy?
As autonomous systems transact across services, trust and structured discovery become infrastructure problems. AgentsOnly proposes a foundational layer that could make agent-to-service interaction more reliable and scalable.