Speakeasy vs Kong MCP gateway: Which layer should govern your agents' tool calls?

Speakeasy’s comparison of its MCP gateway with Kong AI Gateway argues that Kong is strongest for organizations already operating Kong infrastructure, especially those needing self-hosted, on-premises, or private-network deployments, OpenAPI-to-MCP conversion, GitOps-managed policies, and integration with existing API authentication, rate-limiting, and logging systems. Kong identifies callers through local AI Consumers or token claims and applies per-server and per-tool ACLs, while Speakeasy emphasizes directory-synchronized identities, organization-wide role-based permissions, client admission controls, and centralized administrative auditing. Both platforms support granular tool access, upstream credential handling, and detailed activity records, but they differ in policy architecture: Kong relies on gateway configuration and external authorization-server client registration, whereas Speakeasy uses IdP group mappings, per-server client allowlists, Shadow AI controls, and managed per-user OAuth grants. The post notes Kong’s limitations around native MCP guardrails and some session features, while acknowledging Speakeasy cannot be self-hosted, though it offers Tailscale private access and outbound tunnels for private backends. Overall, it recommends Kong for platform teams with established Kong deployments and infrastructure-control requirements, and Speakeasy for security or AI-enablement teams focused on directory-driven governance of users, agents, tools, and approved AI clients.

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