Top 9 MCP Gateway for Developers to Build AI Agents

TL;DR:

• Most "best MCP gateway" rankings are misleading because they rank on feature count when the real question is which architecture fits your constraints. The term "MCP gateway" actually covers six different product types that each started as something else:
• Identity layers (Scalekit), model the agent as a specific user acting on someone's behalf
• Integration platforms (Scalekit, Composio), breadth of prebuilt connectors
• Unified AI+MCP gateways (TrueFoundry, Bifrost), govern model and tool calls in one plane
• Network/infra proxies (Solo agentgateway), Kubernetes/Envoy heritage
• Governance control planes (MintMCP, Obot), RBAC, audit, compliance
• Security scanners (Lasso), inspect tool traffic for threats

Most gateway rankings mislead. Search for the best MCP gateway and you get leaderboards: ten products, a feature grid, a latency number, a winner. For a weekend project that is fine. For a team putting agents in front of customer data, it is the wrong instrument, because it answers "which has the most features" when the real question is "which architecture fits my constraints."

The term MCP gateway is overloaded: it covers at least six different kinds of products that happen to speak the same protocol. Once you see the categories, the choice around choosing an MCP gateway as part of your agent architecture gets much clearer. So rather than rank, this guide classifies by architecture, names the axes that actually decide fit, and then profiles the contenders honestly within those categories.

What an MCP gateway actually is, and is not

An MCP gateway sits between your agents and the tools they call, and centralizes the things you do not want scattered across every agent: authentication, authorization, routing, observability, and policy.

"Add a tool once, rotate a credential once, enforce a rule once."

That consolidation is the core value, and it is why teams that skip it in prototyping almost always add one before they ship.

Why an API gateway is not a drop-in

A reasonable question is whether your existing API gateway already does this. It mostly does not, because the traffic shape is different.

Traditional API traffic is stateless request-response, while MCP traffic is stateful, multi-turn, and action-oriented, with a discovery-then-call cycle the gateway should understand at the protocol level rather than just the HTTP level.

Gateway patterns are now on the MCP roadmap itself, which is a signal that this layer is becoming formal infrastructure rather than an add-on.

Six categories hiding under the tag 'MCP'

Most products in this space did not start as MCP gateways. They started as something else and added MCP support later, and that heritage still shapes what they are good at. Six categories cover the field:

• Integration platforms that speak MCP, optimized for breadth of prebuilt connectors.
• Unified AI-and-MCP gateways, governing model calls and tool calls in one control plane.
• Network and infrastructure proxies, with data-plane and Kubernetes heritage.
• Governance control planes, built for catalogs, RBAC, and compliance.
• Security scanners, built to inspect tool traffic for threats.
• Identity layers, built around who the agent is and whose authority it carries.

No category is best in the abstract. Each is the right answer to a different question, so the practical method is to find the category that matches your dominant constraint, then choose the strongest MCP Gateway within it. The next two sections give you the axes and the lens to do that.

The architectural axes that decide fit

Feature lists blur these together, so it helps to separate the axes that change an architecture decision:

• Identity model: shared service credential, client-token passthrough, or per-user credential resolution.
• Access-control depth: enforcement at the server, the tool, or the parameter level.
• Deployment: managed SaaS, self-hosted, or bring-your-own-cloud.
• Transport and protocol posture: Streamable HTTP, and readiness for the stateful-to-stateless shift.
• Multi-tenancy and isolation: whether one tenant can ever reach another's data or credentials.
• Audit and compliance: immutable logs and a delegation chain, which the EU AI Act's high-risk rules make a hard requirement from 2 August 2026.

The axes teams underweight

Two more axes rarely make the feature grid but cause real incidents—

• The first is token and context efficiency, since connecting five or more servers can flood the model's context with tool definitions and degrade tool selection.
• The second is MCP-specific threat handling, covering tool poisoning, rug-pull tool redefinition, cross-server shadowing, and the confused-deputy risk of forwarding a client token straight to a downstream API.

Performance overhead matters too, but for most product teams it is a tiebreaker, not the deciding axis.

The identity axis, up close

Many gateways treat the agent as a routing client: they hold a credential, often a shared service account or a passed-through client token, and forward calls. That centralizes secrets, which is genuinely better than scattering them, but it leaves a gap. The agent can usually do far more than the human who triggered it.

Why the gap matters

A human with read-and-update access to a CRM does not accidentally export fifty thousand records; an agent with the same token can. When the credential is shared or broadly scoped, an identity layer cannot tell one user's action from another's, and the audit trail cannot answer what the agent did on whose behalf.

Treating the agent as an identity actor closes that gap: the agent acts as a specific user, with that user's scoped credential, isolated per tenant, and every action attributable.

A note on security scanners

Security-first products sit alongside this axis rather than on it. Tools such as Lasso Security inspect traffic for prompt injection, tool poisoning, and data exposure, and they are valuable, but they are usually layered onto a governance or identity gateway rather than replacing one.

Best MCP Gateway for Developers to build AI Agents

We evaluate 9 best MCP Gateway based on their core architectural bet, identity and auth flow, deployment, control depth, best fit, and where it is the wrong choice.

Note: Latency and certification figures are vendor-published or widely reported, and worth re-verifying against your own workload.

1. Scalekit: the Identity-first Gateway, with a Large Pre-built Connector Catalog

Scalekit approaches the problem from the identity layer rather than the network layer. When a user authorizes a connector, Scalekit creates a per-user connected account, and every tool call then runs under that specific user's credential, scoped to what they approved and isolated per tenant. The agent is modeled as a real identity acting on someone's behalf, across delegated-user, service, and token-exchange flows. Credentials sit in a per-tenant AES-256 vault that your code and the model never touch, and every action lands in a delegation chain you can export to a SIEM.

• Identity and auth: per-user connected accounts where the agent acts as the authorizing user, with human and agent auth unified alongside SSO and SCIM.
• Two surfaces: MCP Auth, a drop-in OAuth 2.1 authorization server with DCR, CIMD, and PKCE; and Agent Auth, a token vault plus scoped tool-calling over 100-plus connectors.
• Deployment and posture: managed or in your own VPC, US or EU, and SOC 2 Type II, ISO 27001, and GDPR aligned.
• Best fit: multi-tenant products where per-user authority, isolation, and an auditable delegation chain are non-negotiable.
• Where it is not the pick: when you want a microsecond-latency routing proxy.

Worth exploring:

• Agent Connector Catalog
• Virtual MCP Server
• Scalekit's offerings for Agent Builders
• Pricing (designed for Agents)

2. Composio: the integration platform that speaks MCP

Source: Composio

Composio is an agentic integration platform whose strength is breadth. It maintains 900-plus connectors, operating the OAuth flows, token refresh, and schema drift so your team does not. Its Tool Router exposes a single MCP endpoint with dynamic discovery and routes intelligently so a model is not flooded past the roughly thirty-tool comfort zone. Architecturally it behaves more like a managed integration platform that speaks MCP than a control or identity plane, which is the right trade when wiring many tools quickly matters more than owning the layer.

• Identity and auth: unified OAuth, API key, and JWT; framework-agnostic SDKs for OpenAI, Anthropic, LangChain, and others; MCP API key enforcement on by default since March 2026.
• Control and posture: action-level RBAC, a zero-data-retention stance, sandboxed execution, SOC 2 Type II and ISO certification, and a published latency overhead under 5 milliseconds.
• Deployment: managed-first, with self-hosted or VPC options at the enterprise tier; some reviewers describe it as effectively managed-only.
• Best fit: when time-to-integration across many SaaS tools is the binding constraint.
• Where it is not the pick: when you need to govern arbitrary internal or community servers, customize closed-source connectors, or keep all tool-call data in your own cloud.

The May 2026 security incident

In May 2026 Composio disclosed a security incident. Composio reported roughly 5,241 API keys and 5,001 GitHub OAuth tokens as likely exposed, characterized as about 0.3 percent of active connections, and rotated and revoked credentials in response. It belongs in a gateway comparison for an architectural reason: it maps onto where credentials live and the blast radius when a boundary fails, and any gateway that stores tokens in a central cache inherits those questions.

• The decisive failure was egress rather than execution, covered in securing the exit and in what encryption at rest does not cover.
• For Composio teams reassessing: our migration guide states the real constraints, including that OAuth tokens cannot transfer and each user must re-consent once.

3. TrueFoundry: the performance-focused unified gateway

Source: TrueFoundry

TrueFoundry is an MLOps and agentic-AI platform whose MCP gateway is one module beside model serving, fine-tuning, and LLM routing. Its calling card is performance: it handles authentication and rate limiting in memory rather than through database lookups, publishing sub-3-millisecond latency under load and figures like 350 requests per second on a single vCPU. For a team that wants one vendor across the whole AI lifecycle, the integration story is tight, since model traffic and tool traffic share one control plane, governance, and observability.

• Identity and auth: OAuth 2.0 and 2.1 with dynamic discovery, federated identity via Okta, Azure AD, or Google Workspace, and on-behalf-of token propagation.
• Control: RBAC at the MCP server level, a virtual-MCP feature for composite endpoints, and observability sliced by team, user, tool, and cost center.
• Deployment and posture: VPC and on-premises on the Pro tier; SOC 2 Type 2 and HIPAA aligned.
• Best fit: teams already standardizing model traffic on TrueFoundry that want tool governance in the same plane.
• Where it is not the pick: teams that only need MCP tooling, since adopting it pulls in a much larger platform, with no built-in server registry.

4. Bifrost by Maxim AI: LLM and MCP in one binary

Source: Bifrost

Bifrost is an open-source gateway that runs an LLM gateway and an MCP gateway as a single binary, governed by one virtual-key system, one audit log, and one observability pipeline. The architectural argument is genuine: a single agent turn interleaves model calls and tool calls, so routing them through two systems doubles the operational surface, splits cost data, and fragments traces.

A notable security property is stateless, explicit tool execution, where the model's tool calls are treated as suggestions and execution requires a separate authenticated call from the application.

• Identity and auth: virtual keys with IdP integration, and vault-backed credential storage with immutable logs.
• Control: RBAC, per-tool allow lists, and budget controls spanning both model and tool calls.
• Deployment: open-source, self-operated as a single binary.
• Best fit: teams that want model and tool governance unified in one plane and are comfortable running it themselves.
• Where it is not the pick: teams that want a fully managed service, or an identity-centric or connector-centric layer.

5. Solo agentgateway: the Kubernetes-native data plane

Source: Solo

Solo's agentgateway brings Envoy and CEL heritage to MCP and is configured the way platform teams already work, through Kubernetes custom resources attached to an MCP route. Its data-plane primitives are mature: per-tool rate limiting expressed with CEL descriptors that inspect the JSON-RPC body to separate tool calls from other operations, plus layered gateway-level and route-level policies where the tighter route policy wins.

For an organization already running Envoy and the Gateway API, it inherits that maturity rather than introducing a new runtime.

• Identity and auth: plugs into the identity and policy stack you already run in the mesh, rather than shipping a connector catalog.
• Control and policy: policy-as-code for agent traffic, with both local in-process limiting per replica and global limiting through a shared service.
• Deployment: Kubernetes-native, open core with an enterprise tier.
• Best fit: platform teams already operating Kubernetes and Envoy who want infrastructure-grade routing and policy.
• Where it is not the pick: product teams without that footprint, or teams whose primary need is identity or a connector catalog.

6. Docker MCP Gateway: the container-first option

The Docker MCP Gateway runs each MCP server in an isolated container with restricted privileges, network, and resources, and manages the full lifecycle, spinning servers up on demand. It is open-source, ships inside Docker Desktop's MCP Toolkit, and runs standalone via the docker mcp CLI.

Its catalog offers 300-plus verified, containerized servers with versioning, provenance, SBOMs, and supply-chain checks, and profiles scope which servers a given client can see. Security at the supply-chain and isolation layer is its strongest dimension.

• Identity and auth: OAuth 2.0 and SAML for downstream services, with Docker Hub-integrated credential management.
• Security and secrets: secrets are injected into the target container at runtime rather than into config, and interceptors can verify image signatures, log calls, and block payloads that look like secrets.
• Deployment: local-first on a laptop, Compose to scale out; the broader governance bundle is invite-only.
• Best fit: local development and container-first teams that value image provenance and isolation.
• Where it is not the pick: regulated multi-tenant production, given cold-start latency and a lighter identity story; several reviewers call it a developer tool, not an enterprise platform.

7. MintMCP: the governance and compliance control plane

Source: MintMCP

MintMCP is built governance-first and aimed squarely at regulated environments. It is SOC 2 Type II and HIPAA aligned, with SCIM-driven RBAC, enterprise SSO through SAML and OIDC, granular audit logs, and high availability with automatic failover.

Its one-click deployment turns a local STDIO server into a production endpoint with authentication, logging, and access control configured by default, and it brokers OAuth so individual agents never hold raw credentials. Virtual MCP bundles and hosted connectors round out a data-permissions-first posture.

• Control: SCIM-driven RBAC, OAuth brokering, real-time monitoring dashboards, and a data-permissions-first model.
• Deployment: managed, with one-click promotion of local servers to governed endpoints.
• Best fit: regulated enterprises where compliance certification is a prerequisite for shipping MCP to production.
• Where it is not the pick: teams whose main need is a broad prebuilt connector catalog or a server registry.

Honest constraint: it is a gateway and deployment tool, not a full lifecycle platform; there is no server registry or catalog, and pricing is sales-only.

8. Obot: the open-source all-in-one

Source: Obot

Obot bundles a gateway, a curated catalog, server hosting, and a chat client into one open-source deployment under the MIT license, running on Kubernetes or Docker, or consumed as a managed service.

Its built-in catalog is a searchable directory of approved servers with live documentation, capabilities, and IT-verified trust levels, which directly addresses the shadow-MCP problem of developers pasting unvetted URLs into clients. It is close to what a platform team would build for itself given many months.

• Identity and control: centralized identity, multi-role RBAC, per-user OAuth passthrough, and policy-as-code.
• Threat handling: explicit attention to MCP-specific risks like rug-pull tool redefinition and cross-server shadowing.
• Deployment: self-hostable on Kubernetes or Docker, or run as a managed service, under the MIT license.
• Best fit: platform teams wanting an open-source or managed control plane with a catalog built in.
• Where it is not the pick: small teams that do not want to operate a broad, multi-component platform.

9. Lasso Security: the security-first scanner

Source: Lasso

Lasso Security takes a security-first posture, using an open-source, plugin-based architecture to inspect MCP traffic in real time. It detects and mitigates prompt injection, command injection, and sensitive-data exposure, masks and redacts PII in both requests and responses, validates tool-call parameters, and filters network destinations, blocking malicious payloads before they reach the agent or the tool.

That depth of inspection is its whole point, and it is positioned to complement rather than replace a governance gateway.

• Control: real-time threat detection, tool-call parameter validation, and PII masking on both requests and responses.
• Performance: reported latency in the 100-to-250-millisecond range depending on inspection depth, an order of magnitude above routing-focused gateways.
• Deployment: open-source core with an enterprise offering.
• Best fit: security-sensitive deployments that need active threat detection on tool traffic.
• Where it is not the pick: as a sole gateway, since most teams layer it onto a governance or identity plane rather than replacing one.

A decision framework, not a winner

The honest output of this guide is not a single name. It is a mapping from your binding constraint to the category you should look at first:

Note: The categories overlap at the edges, and several products reach into more than one. Use the table to choose where to start your evaluation, then test the two or three axes you cannot compromise on against a real workload, not a feature page.

Conclusion: pick the axis you cannot compromise on first

There is no universally best MCP gateway, because the products are answers to different questions. The fastest way to a good decision is to name the one axis you cannot give up, identity, breadth, unified control, infrastructure fit, compliance, or threat detection, and let that select your category before you compare anything else.

We think identity is the axis most teams underweight until it causes an incident, which is why we build Scalekit around the agent as an identity actor rather than a routing client. If that is your binding constraint, start with the MCP Auth quickstart and a connector example. If it is not, one of the alternatives above is genuinely the better fit, and choosing it deliberately is the whole point of this guide.