The Best MCP Gateway Options for Security Teams and CISOs
AI agents are a new attack surface and most organizations don’t have visibility into it yet. Agents with unfettered tool access (which MCP provides by default) can introduce MCP security risks. After all, MCP enables agents read private data and write to production systems, which can cause data exfiltration, manipulation through prompt injection or other attacks such as rug pulls. i. Security teams need to treat MCP as a threat vector, not just an integration protocol.
An MCP gateway is the security control plane for AI agent activity.
MCP gateways make it easier for organizations to deploy AI in for employees by:
- centralizing authentication
- enforceing access policies
- detecting MCP-specific attack patterns
- producing audit trails that incident response and compliance teams require
This guide covers the best MCP gateway options for security teams and CISOs.
Why Security Teams Need an MCP Gateway
MCP Introduces Attack Vectors Your Security Stack Doesn’t Cover
Prompt injection, tool poisoning, rug pull attacks, and data exfiltration through chained tool calls are threats specific to MCP’s architecture. Your SIEM sees network events. Your API gateway validates HTTP requests. Neither detects an agent being manipulated through a poisoned issue in a public GitHub repo into exposing names of private repositories. A gateway with MCP-aware threat detection fills that gap.
You Can’t Secure What You Can’t See
Without centralized logging of agent-to-tool interactions, security teams have no visibility into which agents accessed which tools, with which parameters, authorized by whom, and what data was returned. A gateway captures that full chain for every tool call — creating the observability layer that makes threat detection and incident response possible.
Least-Privilege Access Must Be Enforced at the Tool Level
Agents often get configured with broader access than they need. A gateway enforces least-privilege at the tool and operation level — ensuring agents can only invoke the specific capabilities they’re authorized for, regardless of what the underlying MCP server exposes.
MCP Manager by Usercentrics
Best MCP Gateway for Security Teams That Need MCP-Specific Threat Protection
MCP Manager was built around the governance and security use case. For CISOs and security teams, that means every feature is oriented toward the questions you’re asking: what’s the attack surface, who has access, what’s happening in real time, and can we prove it to a regulator?
Key security capabilities:
- Runtime guardrails**: Automated defense against prompt injection, tool poisoning, and rug pull attacks — enforced at the gateway layer without requiring changes to individual agent configurations.
- PII and sensitive data detection**: Presidio-powered interception of API keys, credentials, and regulated data before it reaches an LLM.
- RBAC and ABAC**: Access policies at the user, team, agent, tool, and operation level. Attribute-based controls add contextual rules that reflect real-world access governance.
- Immutable audit logs**: Every tool call recorded with agent identity, tool name, parameters, result, and the human authorization chain — the compliance evidence SOC 2, HIPAA, and GDPR auditors expect.
- SIEM integration via OpenTelemetry**: Export telemetry directly to Splunk, Datadog, or your existing SOC tooling.
- Real-time alerts**: Proactive notification when agent behavior deviates from expected patterns.
- Private MCP registry**: Maintain an approved catalog of vetted MCP servers. Unauthorized servers never reach agents.
You can try MCP Manager for free by booking an onboarding call.
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Kong AI Gateway
Best for Security Teams in Organizations Already Running Kong
Many enterprise security teams have already vetted and approved Kong for API governance. Kong’s MCP capabilities — the MCP Proxy plugin, OAuth 2.1 via a dedicated MCP OAuth2 plugin, MCP-specific Prometheus metrics, and the MCP Registry in Kong Konnect — extend that approved infrastructure to cover MCP traffic.
For security teams, the value is risk reduction through familiarity. Kong’s plugin ecosystem (OIDC, mTLS, rate limiting, OpenTelemetry) applies to MCP traffic using the same policies and monitoring pipelines your team already operates. No new infrastructure to vet, no new operational patterns to learn.
The tradeoff: Kong’s MCP features extend an API gateway, not a purpose-built MCP security platform. MCP-specific threat detection — prompt injection defense, tool poisoning prevention, PII scanning at the tool-call level — isn’t Kong’s core competency. And the pricing, which can exceed $50,000 annually for enterprise deployments, reflects the breadth of the full API management platform.
IBM ContextForge
Best for Security Teams in Complex, Multi-Domain Environments
Large organizations with separate security domains — different business units, geographies, or regulatory jurisdictions — need MCP governance that can federate across those boundaries. ContextForge is IBM’s open-source AI gateway, designed for exactly that complexity.
Multi-cluster federation via Redis allows independent ContextForge instances to interoperate across organizational boundaries while maintaining separate governance. The platform supports SSO through GitHub, Google, Microsoft Entra, Okta, Keycloak, IBM Security Verify, and generic OIDC — covering the identity infrastructure most security-conscious enterprises already operate. RBAC/ABAC with multi-tenancy enables private, team, and global catalogs that mirror real-world access hierarchies.
ContextForge also provides an admin UI with airgapped deployment support — critical for security teams operating in environments without external network access. OpenTelemetry observability integrates with Phoenix, Jaeger, Zipkin, and other OTLP backends for distributed tracing.
Multi-architecture container support includes linux/s390x for IBM Z/LinuxONE mainframes — relevant for financial institutions and government organizations running mainframe infrastructure.
The tradeoffs: ContextForge is in beta (1.0.0-BETA), has no commercial support, and your team owns the full operational lifecycle. Security teams that require vendor-backed SLAs or production support agreements should factor that operational risk into their evaluation.
Obot
Best for Security Teams That Require Complete Data Perimeter Control
For organizations where security policy mandates that no AI agent traffic leaves the corporate network, Obot provides a fully self-hosted MCP platform deployable on your own Kubernetes infrastructure. No data flows to third-party services. All logging, credential management, and traffic inspection happen within your perimeter.
The shim architecture is particularly relevant for security teams: credentials and secrets live in the shim alongside each server and are never exposed to the MCP server process itself. This limits the blast radius if a server is compromised — the attacker gains access to the tool’s capabilities but not to the credentials or to other servers.
The curated catalog of vetted MCP servers gives security teams a starting point for approved tools, with the ability to add or remove servers through the admin UI or GitOps workflows. The open-source edition supports GitHub and Google for identity; the Enterprise Edition adds Okta and Microsoft Entra.
Obot is backed by $35 million in seed funding and offers an Enterprise Edition with dedicated support. The tradeoff is self-hosting responsibility: your security team owns deployment, patching, and monitoring.
Amazon Bedrock AgentCore Gateway
Best for Security Teams in AWS-First Organizations
For security teams that have already built their security operations around AWS tooling, AgentCore Gateway provides MCP governance through the same infrastructure: IAM for authorization, CloudWatch for monitoring, CloudTrail for audit logging.
The strongest security feature for CISOs is AgentCore Policy — a deterministic policy enforcement layer that intercepts every tool call through the gateway and evaluates it against Cedar policies before allowing execution. Unlike probabilistic LLM-based guardrails, Cedar enforcement is deterministic: if a policy says deny, the call is denied. No reasoning, no exceptions, no hallucinated approvals.
Policies can be authored in natural language and automatically converted to Cedar, making policy creation accessible to security teams without Cedar expertise. Every enforcement decision is logged through CloudWatch, creating an auditable record of every allow/deny decision.
The tradeoff is AWS lock-in. Security teams managing multi-cloud environments or MCP governance across non-AWS tools will find AgentCore Gateway’s scope limited to the AWS boundary.
Choosing the Right MCP Gateway for Your Security Team
MCP-specific threat protection is the primary requirement: MCP Manager. Runtime guardrails, PII detection, SIEM integration, and immutable audit logs — purpose-built for the MCP threat model. You can learn more about MCP Manager and book a free trial.
Already operating Kong with approved security policies: Extend Kong to MCP. Same infrastructure, same monitoring, same team.
Federated security across multiple domains or geographies: IBM ContextForge. Multi-cluster federation, airgapped deployment, and multi-protocol support for complex security architectures.
Zero data egress, full perimeter control: Obot. Self-hosted on your infrastructure with credential isolation at the shim layer.
AWS-native security operations: AgentCore Gateway. Deterministic Cedar policy enforcement with IAM, CloudWatch, and CloudTrail integration.
The MCP attack surface is real and growing. Every agent with tool access is a potential vector. The gateway you choose determines whether your security team has the visibility, controls, and audit trail to manage that risk — or whether you’re discovering problems after the damage is done.
