How to evaluate an AI Gateway

Evaluating an AI gateway should balance technical fit, security approval, and vendor reliability, beginning with a customer-defined, testable capability matrix rather than vendor-led demos. The text emphasizes that MCP deployments require particular scrutiny because credential and tool governance, especially for servers dependent on static API keys, may not be covered by conventional AI policy reviews; it cites survey findings that 45% of software companies already use MCP in production while 64% identify security as the primary barrier to wider adoption. It recommends comparing two or three vendors, aligning security questionnaires with contractual data terms, separating pricing discussions from technical selection, and planning onboarding, sandbox testing, and incident support before signing. Thorough evaluations typically take four to eight weeks, and vendor responsiveness during diligence is presented as an indicator of post-sale support quality. The piece concludes by positioning Barndoor as a provider designed around individual MCP credential and tool-call governance, rapid evaluation support, and usage-based commercial terms.

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