MCP Health Check

Your MCP Server Is Live.
Is It Actually Agent-Ready?

Submit your MCP server and we'll tell you exactly where you stand.

Evaluate My MCP Server →
MCP Evaluation — acme-payments-apiBazantic / Baz AI
Discoverability
Registry presence, tool descriptions
NEEDS WORK
Tool Structure & Intent Routing
Intent coverage, routing clarity
GAP FOUND
Authentication
Non-human call patterns, token auth
PASS
Response Quality
Structure, token overhead, determinism
NEEDS WORK
Error Handling & Recovery
Actionable errors, recovery paths
GAP FOUND
Protocol & Cross-Model Compliance
MCP, A2A, UCP · Claude, GPT, Gemini
PASS
Framework

The Four Layers of an Agent-Ready MCP

LAYER 001

Built for Deterministic Outcomes

Agents need the same input to return the same output, every time. Loose typing, ambiguous tool names, and responses that vary force an agent to guess — and guessing is where it fails. Deterministic structure is the foundation everything else sits on.

01
02

LAYER 002

Optimized for Token Consumption

Every token an agent spends parsing your responses is a token it can't spend reasoning. Bloated payloads, verbose errors, and redundant fields drive up cost and latency — and push agents toward leaner alternatives. Lean, purpose-built responses keep you in the loop.

LAYER 003

Works Across Multiple LLMs

Claude, GPT, and Gemini don't behave the same way — a server tuned for one can misfire on another. Agent-ready means consistent behavior across every major model, so your API performs no matter which LLM is driving the agent.

03
04

LAYER 004

Maintained at Scale

Protocols evolve. Agents arrive in bursts. A server that runs fine in development can buckle under real agentic concurrency — and every failure is a silent defection. Uptime and throughput are UX concerns now.

Evaluation Criteria

What We Evaluate

Can agents find your server, understand what it does, and determine when to use it?

Are your tools defined around agent intent, or around your API's internal logic?

Does your auth flow work for non-human, programmatic call patterns without introducing friction?

Are responses structured for agent consumption — deterministic, low-overhead, unambiguous?

Do error responses give agents something actionable, or do they dead-end the interaction?

Does your server hold up across Claude, GPT, and Gemini, and against current MCP, A2A, and UCP standards?

Are responses lean and purpose-built, or do bloated payloads and verbose errors burn tokens an agent could spend reasoning?

Get Your MCP Evaluated

We review your MCP server against the seven criteria above and send findings directly to your email. No commitment required.

Reviews are conducted manually by the Bazantic team.
We'll follow up at your email within a few business days.

FAQ
Do I need to be a Bazantic customer to request an evaluation?

No. The evaluation is open to anyone who has built or is building an MCP server. There's no obligation to use Bazantic after receiving your findings.

Is this free?

Yes, for now. We're offering evaluations at no cost during our launch period.

What do I get back?

A structured assessment of your MCP server across the six evaluation criteria — with specific gaps identified and recommendations for each. Not a score. Actual findings.

What if my MCP server has significant gaps?

That's exactly why the evaluation exists. The findings will tell you what to prioritize. If the gaps are ones Bazantic can address, we'll tell you that too — but there's no pressure to act on it.

Does submitting mean I'm applying to become a Bazantic provider?

No. This is a separate track. If you want to explore becoming a provider after your evaluation, you can — but the two are independent.