Ship MCP servers with confidence.
Deterministic quality testing for Model Context Protocol servers — from contract discovery and fingerprinting to functional checks, bounded security, official conformance normalization, and CI quality gates.
Deterministic workflow
Inspect → Fingerprint → Test → Secure → Conformance → Gate
MCP Quality v0.1 keeps protocol, functional, and security results distinct and does not require a model call to make a quality determination.
Inspect
Discover server identity, capabilities, tools, resources, and prompts.
Fingerprint
Normalize the contract and produce a stable SHA-256 identity.
Test
Run deterministic functional contract checks without inventing destructive tool inputs.
Secure
Evaluate the bounded deterministic MCP security baseline and redacted evidence.
Conformance
Invoke the official MCP conformance runner through NAT and preserve upstream result IDs.
Gate
Use machine-readable JSON artifacts and explicit exit codes in CI.
Stable contract identity
Know when the MCP contract actually changed.
NAT normalizes discovered MCP contracts before fingerprinting, excludes volatile capture metadata, and deterministically orders tools, resources, and prompts. An unchanged deterministic contract should produce the same fingerprint every time.
CI contract
Quality failures and broken test runs are not the same thing.
Every public MCP command supports JSON output. Preserve the artifacts with the build and use NAT's documented exit semantics to distinguish target quality failures from an environment where a valid determination could not be made.
Security & redaction
Bounded, deterministic trust checks.
v0.1 checks deterministic issues such as duplicate normalized tool names, obvious credential material in descriptions, invalid resource URIs, sensitive local file exposure, and breaking drift. NAT applies recursive redaction before inspection and NAT-native result serialization.
Security & redaction docs →Explicit v0.1 boundary
No model-in-the-loop security claims.
MCP Quality v0.1 does not claim semantic prompt-injection detection, model-driven tool-poisoning analysis, LLM-as-judge evaluation, chaos testing, MCP SaaS execution, centralized MCP run history, or MCP-specific pricing.
Design-partner empirical validation
Develop or maintain an MCP server?
NAT MCP Quality v0.1 is being validated with a small cohort of real MCP engineering teams. The goal is to find where deterministic results are useful, wrong, confusing, or difficult to integrate — not to collect endorsements.
Discuss design-partner validation