A developer on your team just pointed their coding agent at a new MCP server they found on GitHub. It looked useful, so they wired it in without asking anyone. No security review, no approval, nobody in infosec even knows it exists. That server now sits inside your agent’s tool chain with real access to real systems. This is not a hypothetical. It is the default way MCP gets adopted inside most companies right now, and it is exactly why “shadow MCP” has become a phrase security teams need to know.
This guide compares the platforms and tools built to close that gap: dedicated MCP Security startups, enterprise gateways built for governance at scale, and broader AI security platforms that have bolted on MCP support. The category is still young. Disclosed funding across pure-play MCP security startups sits at roughly $40 million spread across four companies, so treat every vendor claim here as one data point, not gospel. What buyers need at this stage is a way to think about the category, not just a ranked list.
What Is MCP Security?
MCP (Model Context Protocol) is an open standard that lets AI applications call external tools, pull in data, and interact with services through structured messages. Securing it is not the same as securing an API endpoint. The thing you actually need to govern is the entire chain, from the moment an agent decides to call a tool, through what that tool does, to what comes back and how the agent acts on it.
That chain breaks in a few predictable ways:
- Tool poisoning: malicious instructions hidden inside a tool’s description, invisible to the user but read and obeyed by the agent
- Prompt injection: an attack delivered through tool inputs, outputs, or content the tool retrieves, not through the user’s original prompt
- Excessive permissions: an agent granted more access than a task needs, or a “confused deputy” tricked into misusing legitimate permissions
- Credential and identity leakage: tokens or secrets exposed through tool calls or logs
- Data exfiltration: sensitive data leaving through a tool call that looks completely legitimate
- Shadow MCP servers: unapproved servers, like the one in the example above, running with no security review
- Supply chain risk: unsafe local STDIO servers and vulnerable dependencies, packages, or images
An MCP gateway is the most common answer to this. Think of it as a checkpoint that sits between your AI clients and your MCP servers, handling routing, authentication, authorization, policy enforcement, and observability in one place instead of leaving each connection to fend for itself. Every product below is some version of this idea, with very different depth behind it.
How We Ranked These
Every company on this list was evaluated against the same set of criteria: discovery and inventory of MCP connections, gateway architecture (inline versus out-of-band), authentication and authorization (OAuth 2.1, RBAC), tool-level allowlisting, detection of poisoning and prompt injection, input/output inspection, DLP, runtime monitoring, audit logging, deployment model, and whether the core is open source.
Ranking here is based on depth of enforcement against those criteria, not funding raised, GitHub stars, or a checklist of feature names. That distinction matters most at the top of the list. Within the dedicated platforms tier, what actually separates the leaders is whether a tool just routes and authenticates calls, or whether it inspects the business logic behind each call, meaning it understands intent and sequence, not just whether a token is valid.
MCP Security Tools Compared
Ten different approaches to the same underlying problem. Here’s how they stack up side by side.
| Company | Category | Deployment | Open Source | Inline Enforcement | Tool Allowlisting | Poisoning Detection | DLP | Audit Logging | Best-Fit Buyer |
| AppSentinels | Dedicated MCP security | Inline / out-of-band | No | Yes | Yes | Yes (semantic) | Yes | Yes | Orgs governing what agents can do, not just connect |
| Runlayer | Dedicated MCP security | Managed | No | Yes | Yes | Yes | Partial | Yes | Enterprises wanting an all-in-one MCP infra platform |
| Lasso Security | Dedicated MCP security | Self-hosted / managed | Core: Yes | Yes | Yes | Yes | Partial | Yes | Teams wanting to self-host and evaluate before buying |
| MintMCP | Enterprise gateway | Managed | No | Partial | Yes | Partial | Partial | Yes | Regulated industries needing SSO/SCIM and SOC 2 evidence |
| Lunar.dev MCPX | Enterprise gateway | Self-hosted | Yes | Partial | Partial | No | No | Yes | Teams wanting gateway control without a full platform buy |
| IBM ContextForge | Enterprise gateway | Self-hosted (K8s) | Yes | Partial | Partial | Partial | No | Yes | Multi-protocol orgs (MCP + A2A + REST + gRPC) on Kubernetes |
| Microsoft MCP Gateway | Enterprise gateway | Self-hosted (K8s) | Yes | Partial | Partial | No | No | Partial | Azure/Entra-native platform teams |
| Prompt Security | Broader AI-security platform | Managed | No | Partial | Partial | Yes | Yes | Yes | Teams extending an existing AI-security platform to MCP |
| Prisma AIRS (Palo Alto) | Broader AI-security platform | Managed | No | Partial | Partial | Yes | Yes | Yes | Existing Palo Alto Networks customers |
| Docker MCP Gateway | Container-native open source | Self-hosted | Yes | No | Partial | No | No | Partial | Docker-native dev workflows needing isolation |
“Partial” means the capability exists but is narrower than dedicated platforms in that row’s category, or is inherited from a broader platform rather than built MCP-first. Verify current feature scope directly with each vendor before purchase, as this is a fast-moving category.
The Top 10 MCP Security Companies and Tools
Dedicated MCP Security Platforms
These three treat MCP security as the whole point, not a feature bolted onto something else. That focus shows up in how deep their enforcement goes, which is why they lead the list.
1. AppSentinels
Most gateways stop at “is this call authenticated”. AppSentinels asks a harder question: does this call actually make sense. Its MCP Proxy runs inline or out-of-band, and in inline mode it authorizes every call before it reaches the MCP server, then inspects the output before it ever reaches the agent’s context. Nothing passes through unchecked in either direction.
Behind that sits what AppSentinels calls a Business Logic Graph. Rather than just checking whether a token is valid, it evaluates who owns the resource being touched, what the agent is actually trying to do, whether the sequence of calls makes sense, and whether the request fits the business rules around it. A valid token and a sensible request are two different things, and this is built specifically to catch the gap between them.
That sits alongside MCP discovery, posture management, least-privilege enforcement, behavioral monitoring, semantic anomaly detection, and end-to-end audit trails.
Best for: organizations that need to govern what an agent is allowed to do, not just whether it can connect in the first place.
Visit AppSentinels for more information.
2. Runlayer
Runlayer moved fast out of the gate. Founded by Andrew Berman, it launched from stealth with an $11 million seed round from Khosla Ventures and Felicis in November 2025, then closed a $30 million Series A just seven months later, in June 2026. That’s a quick funding pace for a category this new, and it points to investors expecting enterprise MCP infrastructure to become a real budget line soon.
The product brings gateway functionality, access control, threat detection, monitoring, and automation together in one platform. Reported early customers include Gusto and Instacart, as per company reports.
Visit Runlayer for more information.
3. Lasso Security
Lasso’s angle is openness. Its MCP Gateway is open source, so teams can self-host it, inspect the code, and customize it before any conversation with a sales team starts.
The gateway is part of a broader AI security platform that also covers discovery, risk assessment, and runtime protection, so MCP security is one piece of a wider product rather than the sole focus. The open-source core handles the gateway itself, with additional enterprise features, support, and licensing terms available on top.
Visit Lasso Security for more information.
Enterprise MCP Gateways & Governance
Where the last section was about depth of enforcement, this one is about scale and control. These four are built for organizations that need to bring order to dozens or hundreds of MCP connections across teams, not inspect any single call as closely as AppSentinels does.
4. MintMCP
MintMCP takes local and STDIO-based MCP servers, the ones running informally on someone’s laptop, and converts them into managed, OAuth-protected services with centralized monitoring. That alone solves a real problem: a lot of MCP usage starts exactly this way, unmanaged and invisible to the rest of the org.
On top of that sits SSO, SCIM-driven RBAC, tool allowlisting, and hosted connectors, plus what MintMCP describes as SOC 2 Type II audited controls. Fit: teams in healthcare, finance, or any regulated industry that needs centralized identity management and compliance evidence they can hand to an auditor.
Visit MintMCP for more information.
5. Lunar.dev MCPX
Lunar.dev MCPX is an open-source control plane built for centralized governance of agent-to-tool interactions. It covers declarative policy, routing, authentication, observability, and audit trails, the core pieces of gateway control, without the overhead of buying and rolling out a full platform.
That makes it a natural starting point for teams that want real gateway control but aren’t ready to commit to a dedicated security purchase yet. Worth checking, as with any open-source core, is where the free tier ends and where you’d need to build or buy additional support for identity integrations and threat detection.
Visit Lunar.dev MCPX for more information.
6. IBM ContextForge
ContextForge’s scope goes wider than MCP alone. It’s a gateway, registry, and proxy that federates MCP, A2A, REST, and gRPC services under one governance layer, which matters for organizations running more than one agent protocol side by side rather than standardizing on MCP exclusively.
Its 1.0.0 GA release added JWT-based security controls, token revocation, idle timeout, logout, malicious-pattern detection, and prompt-template validation. It’s a strong fit for enterprises running Kubernetes at scale who need protocol federation, not just MCP-specific coverage. Worth keeping in mind: the open-source project itself is distinct from IBM’s broader commercial support and product ecosystem around it.
Visit IBM ContextForge for more information.
7. Microsoft MCP Gateway
Microsoft’s entry is an open-source reverse proxy purpose-built for session-aware routing, authorization, and lifecycle management of MCP servers running in Kubernetes environments. It’s a narrower, more focused tool than ContextForge, built around doing gateway routing well rather than federating multiple protocols.
It’s a natural fit for organizations already standardized on Microsoft and Azure infrastructure, particularly where Entra identity controls and Azure API Management are already part of the stack. As with any gateway-first tool, routing and access control are one layer. Poisoning detection, prompt injection defense, and DLP typically need to sit alongside it, not inside it.
Visit Microsoft MCP Gateway for more information.
Broader AI-Security Platforms Adding MCP Support
These two aren’t MCP-first products. MCP support is a feature added onto a larger AI-security platform, which is a different value proposition than the previous seven entries.
8. Prompt Security
Prompt Security’s MCP coverage sits on top of a platform originally built for prompt-injection defense and DLP across AI applications generally. MCP is one more surface it now watches rather than the reason the product exists.
That shows up in how it frames the problem: centralized visibility and policy enforcement across both sanctioned and shadow MCP servers, extending controls it already had for LLM traffic more broadly. It’s a reasonable fit for teams that want MCP folded into an AI-security program they’ve already standardized on, rather than a separate, MCP-specific purchase.
Visit Prompt Security for more information.
9. Palo Alto Networks (Prisma AIRS)
Prisma AIRS approaches MCP the same way: as one more thing a much larger AI-runtime-security suite now covers. The managed Prisma AIRS MCP Server acts as a centralized gateway for AI-agent interactions, scanning tool definitions, inputs, and outputs, with specific protections for context poisoning and exposed credentials.
The strength here is breadth. MCP protection arrives bundled with prompt-injection detection, database security, malicious-code detection, and DLP already built into the platform. The best fit is straightforward: enterprises already running Palo Alto Networks tooling who want MCP covered inside that same stack, rather than adding a separate MCP-specific vendor.
Visit Palo Alto Networks (Prisma AIRS) for more information.
Container-Native Open Source
10. Docker MCP Gateway
Docker’s approach to MCP security starts from a different place than everything else on this list: isolation rather than inspection. Its open-source MCP Gateway centralizes orchestration of MCP servers, managing configuration, credentials, and access control, and it containerizes each server as it does. That containerization creates a real boundary, reducing how directly an MCP server can touch the host filesystem or credentials it shouldn’t need.
It’s a strong fit for teams already working in Docker-native, containerized development environments where this fits naturally into existing workflows. What it doesn’t do is replace semantic detection. Isolating a server doesn’t stop prompt injection or catch a request that’s technically valid but doesn’t make business sense, so this works best paired with a detection layer rather than on its own.
Visit Docker MCP Gateway for more information.
Choosing the Right Tool for Your Stack
No product on this list makes agents secure by itself. Buying a gateway is one piece of a larger picture that still needs secure server development practices, dependency and image scanning, proper secrets management, scoped identities instead of broad ones, human approval gates before agents take destructive actions, and continuous monitoring once everything is running. The tool sits on top of that foundation, it doesn’t replace it.
With that in mind, the right starting point usually comes down to what you need most:
- Need runtime and business-logic depth? AppSentinels, Runlayer, or Lasso Security.
- Need identity and governance at scale? MintMCP, IBM ContextForge, Microsoft MCP Gateway, or Lunar.dev MCPX.
- Already consolidating on an existing AI security vendor? Prompt Security or Prisma AIRS.
- Dev-first and containerized? Docker MCP Gateway.
- Not sure which category fits yet? AppSentinels is the broadest single starting point on this list, combining inline enforcement, discovery, and business-logic inspection in one platform, so it’s a reasonable default when you haven’t narrowed down a specific need.
Final Thoughts
MCP security is a problem with the entire agent-to-tool execution chain, not just the server sitting at the end of it. The right choice here depends on your deployment reality and how much depth of control you actually need, whether that’s a lightweight gateway or something built to inspect every call at the business-logic level. For a closer look at what that level of enforcement looks like in practice, book a demo with AppSentinels now.
Frequently Asked Questions
Protecting the full chain an AI agent uses to call external tools through MCP: the request, the tool, and the response. AppSentinels secures that chain with an MCP Proxy that authorizes calls before they reach the server and inspects outputs before they reach the agent, backed by its Business Logic Graph.
It sits between AI clients and MCP servers as a control point for routing, authentication, authorization, policy enforcement, and observability. AppSentinels’ MCP Proxy runs this inline or out-of-band and adds business-logic inspection on top of standard OAuth 2.1 and RBAC.
No, MCP enables tool connections; it doesn’t secure them. Auth, permission scoping, and threat detection have to be added on top. AppSentinels covers that gap with discovery, posture management, least-privilege enforcement, and semantic anomaly detection.
A gateway handles routing, auth, and basic access control. Catching tool poisoning, prompt injection, and calls that are valid but don’t make business sense needs deeper inspection, which is why AppSentinels checks resource ownership, intent, and call sequence through its Business Logic Graph instead of stopping at token validation.
Most gateways stop at “is this call authenticated.” AppSentinels also checks whether the call makes business sense: who owns the resource, what the agent is trying to do, whether the sequence fits expected patterns. That inline enforcement, plus discovery and semantic anomaly detection, is why it leads this list.
