What are the best Kong MCP gateway alternatives in 2026?

With Kong MCP gateway, Model Context Protocol (MCP) runs as a plugin within the AI gateway from Kong's, turning REST APIs into MCP options governed by the same system that fronts API calls. The picks covered by this roundup have matching features, each with their strengths and weaknesses. Some are full control layers with sign-in, risk checks, and records as the service, some are basic gateways with no API control stack below, and some go beyond gateway flows into new coding tools and hardware.

Below, you’ll learn about Kong MCP gateway basics, why it loses evaluations, and how these options stack up, including Speakeasy, MintMCP, Runlayer, LiteLLM plus Bifrost.

What is the Kong MCP gateway?

Kong ships MCP support as the AI MCP Proxy plugin on its AI gateway, available in the AI Gateway Enterprise offering on gateway version 3.12 or higher. The plugin converts existing REST APIs into MCP tools with no custom server code, the openapi2mcp tool generates that configuration from an OpenAPI 3.x document, and Kong's plugin ecosystem (OpenID Connect, key auth, rate limiting, logging) applies to MCP endpoints the way it applies to API routes. From version 3.13, per-tool ACLs on Consumers and Consumer Groups add access control with an audit log of allowed and denied attempts, and the Kong MCP Registry pairs a server catalog with the gateway, in Tech Preview inside Konnect Labs.

Why do teams look for Kong MCP gateway alternatives?

A business already standardized on Kong should use it to run API, LLM, and MCP requests together. Evaluations proceed for 4 causes:

• A deeper governance focus. The principal on every MCP call is a Kong Consumer rather than a person or agent in Okta or Entra, there is no documented concept of an agent identity, Kong's own scope-of-support table lists AI Guardrails as not supported on MCP traffic through the plugin, and there is no threat detection or session-level analysis on tool calls.
• A different architecture. The AI MCP Proxy plugin sits in the AI Gateway Enterprise offering and requires gateway 3.12 or higher, and the MCP Registry is a tech preview whose GA timeline Kong's own FAQ declines to commit to. Teams not already standardized on Kong would be adopting an API management platform, its licensing, and its operational model to get MCP governance.
• A lighter LLM gateway. Kong's model routing rides the same platform. Teams that want an open-source, self-hosted gateway for model and tool traffic without API management underneath look at LiteLLM or Bifrost.
• An agent-agnostic solution with reach beyond the gateway. Kong governs MCP traffic that routes through the gateway, with no agent hooks in coding agents, no endpoint or device presence, and no session-level monitoring, so traffic that skips the gateway is invisible to it. Teams want governance any MCP client inherits, with agent identity that resolves in the identity provider whatever runtime the agent uses.

Which Kong MCP gateway alternative should you choose?

Each alternative fits one of the three architectures mapped in which MCP gateway architecture do I need: infrastructure, governance, or a hybrid that also supplies the servers.

Speakeasy: the AI Control Plane with directory-native identity

Speakeasy is the alternative when the evaluation widens from "put MCP traffic through the gateway we run" to "govern every AI surface and supply the tools our agents need." Agents reach internal data through it: internal APIs, databases, and SaaS come under governed MCP servers, with outbound-only tunnels into your VPC for the systems behind your firewall. The MCP gateway is one part of an AI Control Plane that connects AI clients to tools, secures every interaction, controls who reaches what, and observes usage and cost across the organization. Identity resolves to the directory: people sync from Okta or Entra through directory sync, Agent Identity, in early access, syncs from providers such as Entra Agent ID or is created in Speakeasy, and one permission model covers both, so "who is this principal" always answers to the identity provider rather than to a Kong Consumer record.

The safeguards go beyond routing. Risk policies run a prompt injection heuristic with an opt-in LLM judge, and the detector catalog covers secrets, financial data, PII, government identifiers across the US, UK, EU, and APAC, and healthcare identifiers across prompts, assistant messages, tool calls, and tool responses, where Kong excludes AI Guardrails from MCP traffic. Natural-language guardrails replay against recent live sessions to produce a scorecard before they enforce, and custom detection rules in CEL are tested against a real session. Enforcement reaches any MCP client through standard OAuth 2.1 authorization at the gateway, agent hooks in Claude Code, Claude Cowork, Cursor, Codex, and OpenCode, and a device agent on macOS, Windows, and Linux, none of which a network gateway can see. Under the same rules, systems tying tools to company information are run and cataloged, not kept in gateway configuration; Speakeasy has SOC 2 Type 2 plus ISO 27001.

MintMCP: a dedicated managed governance gateway

MintMCP is what a purpose-built version of the layer Kong bolts on looks like: an enterprise MCP gateway paired with an endpoint product called Agent Monitor. Managed hosted connectors remove connector operations, employees reach a self-serve MCP store after SSO, Agent Monitor hooks coding agents on laptops including GitHub Copilot CLI, and its trust center lists SOC 2 Type 2, HIPAA, and CASA Tier 2. Two things carry over from the Kong evaluation rather than resolving it: agent identities are native to MintMCP with no matching record in Okta or Entra, much as Kong's principals are Kong Consumers, and custom servers are written and hosted by hand as STDIO configurations, Docker images, or CLI deployments, where Kong at least generates tools from an OpenAPI document. For the whole breakdown, check MintMCP vs Speakeasy.

Runlayer: the security-first governance gateway

Groups where the security unit runs the review can choose Runlayer to fill what gateway-only systems miss. Every MCP request passes through a single-tenant AWS gateway that authenticates, authorizes, scans, and logs it. ToolGuard scans tool definitions and outputs with findings mapped to MITRE ATLAS, AgentGuard analyzes whole sessions for reasoning pivots and task drift, and Shadow AI reaches laptops through MDM tools like Jamf, Intune, and Kandji. The trade-offs: agents authenticate as Runlayer-native Agent Accounts, custom servers are packaged as containers and deployed to Runlayer-managed infrastructure with no path from an API contract to a generated server, which Kong does offer, and deployment is single-tenant AWS only. See Speakeasy vs Runlayer for the full comparison.

LiteLLM: the open-source LLM proxy with an MCP gateway

LiteLLM shares Kong’s consolidation instinct: a single gateway handling AI calls and agent links, minus the API layer below. It is an open-source proxy exposing an OpenAI-compatible API across more than 100 providers, with retries, fallbacks, virtual keys, and per-key and per-team budgets, and its MCP gateway extends the proxy to tool traffic: servers added in the UI or in config.yaml, OAuth 2.0 to upstream servers, access controlled by key, team, and organization, and spend tracked per MCP server. On the model path, a guardrails framework runs providers such as Presidio, Lakera, Bedrock, and Azure Content Safety, which contrasts with Kong's exclusion of AI Guardrails from MCP traffic, and a Generic Guardrail API accepts a control plane of your choosing, the hook the Speakeasy LiteLLM integration uses. It self-hosts in any environment, even air-gapped, with SSO, SCIM, and logs on the premium plan. It mirrors Kong's: each call is tied to a LiteLLM token, not a directory user, with no endpoint or agent-side component.

Bifrost: the performance-first AI gateway with a built-in MCP gateway

Bifrost is the open-source AI gateway from Maxim AI, written in Go under the Apache 2.0 license, and it earns a seat on a Kong shortlist as the self-hosted consolidation play: one OpenAI-compatible API routing model traffic across 20+ providers with automatic failover, load balancing, and semantic caching, and a built-in MCP gateway in the same process that aggregates tools at a single endpoint with per-virtual-key allow-lists and OAuth to upstream servers. Its benchmarks show only microseconds in overhead per call, but those figures come from Maxim's, not us. Governance runs through virtual keys, hierarchical budgets, and rate limits, with OIDC SSO, SCIM, RBAC, and signed audit logs in the licensed Enterprise tier, and it self-hosts from a single command to air-gapped Kubernetes. The downside for Kong is this: you lose REST-to-MCP support and its plugin ecosystem, while each request uses one Bifrost user, not any directory user. Check the Bifrost and Speakeasy post for a line-by-line look.

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