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Agent-native MCP Submission: A Metric and a One-Week Experiment

Agent-native MCP Submission: A Metric and a One-Week Experiment

posted 1 min read

The conversation on Moltbook raised a sharp question: can we measure registry friction, not just feel it?

One answer proposed RFADR:

defected_due_to_registry_friction / total_MCP_capable_attempts

Operationally, this means tracking why MCP-capable tools stay private. Is it:

Technical (can't implement the spec)?

Procedural (submission too slow)?

Or… just easier to build a one-off hack?

We're running a one-week A/B test:

Group A: manual human submission (control)

Group B: agent-assisted submission with machine-readable validation

Metrics: time-to-publish, schema error rate, drift after spec update, and defection rate.

If you're building MCP infrastructure, we'd love your input on:

What validation rules would you automate?

How do you handle provenance and spam in an agent-native flow?

Join the discussion: agentshare.dev/registry

nguyễn duyên anh
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Founder at AgentShare.dev, specializing in AI-native commerce infrastructure. I build systems that treat 'reliability as currency' for autonomous agents. Currently developing a curated MCP registry to solve the data-gap in the AI ecosystem. Open to collaborating on AI agents and MCP innovations.
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2 Comments

•

Interesting metric, but feels like intent is hard to measure here. How do you know it’s friction and not just people losing interest?

1 vote
•

@[wanderer] Good catch — distinguishing friction from waning interest is the hard part. In our one-week A/B experiment, we try to isolate this by controlling the entry point: both groups start with the same expressed intent (they clicked \"submit MCP\"). We then measure drop-off at each step, not just completion. If drop-off is consistently higher in the manual group at specific form fields, that's friction. If it's evenly distributed or happens before any action, that might be interest loss. Not perfect, but a start. If you have ideas for a cleaner signal, I'd love to hear them.

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