Map every MCP server, tool, agent, and API dependency, then enforce ownership, intent, and business logic on every tool call in real time.

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The MCP Threat Surface Your Stack Doesn't See

Gain visibility into what’s happening inside MCP tool interactions. Expose and govern every MCP server, tool, agent, and action to prevent unauthorized access, misuse, and workflow manipulation.

Tool poisoning

A malicious or compromised MCP server ships tool descriptions crafted to steer the agent into actions the user never requested.

Rug pulls

A tool description, schema, or behavior changes after the MCP server was approved, turning a sanctioned tool into an attack vector.

MCP-mediated prompt injection

A tool returns output containing instructions the agent treats as authoritative, pivoting the workflow toward exfiltration or unauthorized actions.

Unauthorized tool invocation

An agent chains its way to a tool it should never have been able to reach, often through a sanctioned tool that exposes more than intended.

Confused-deputy attacks

The MCP server’s own privileges exceed the requesting user’s, and a tool call ends up accessing objects the user couldn’t access directly.

Shadow MCP servers

Developers wire up new MCP servers without registering them, creating ungoverned execution paths into production data.

Comprehensive MCP Security Across the Full Lifecycle

AppSentinels applies the same three pillars that secure your AI agents and APIs to the MCP layer that now sits on top of them.

Continuous Discovery and Posture Management

Inventory every MCP server, tool, agent, and downstream resource the moment it appears, including shadow servers and unregistered tools.

  • Automatic discovery of sanctioned and shadow MCP servers
  • Inventory of every tool, including schema, permissions, and data scope
  • Mapping of agent → MCP server → tool → API → object access paths
  • Detection of rug-pull events when a tool's description or schema changes
  • Posture scoring against MCP best practices and your own governance policies

Continuous Red-Teaming

Continuously probe the MCP surface with adversarial agents tuned to the attacks that matter at this layer.

  • Tool poisoning and malicious-description simulation
  • MCP-mediated prompt injection via crafted tool outputs
  • Unauthorized tool invocation and privilege escalation chains, BOLA, and BFLA testing
  • Confused-deputy and cross-server attack paths
  • Pre-production and production-safe modes

Real-Time Runtime Protection

Enforce ownership, intent, and sequence on every MCP tool call; inline through the AppSentinels MCP Proxy or out-of-band via sensors.

  • Tool-call authorization scoped to the requesting user
  • Parameter and resource-access enforcement based on the BLG
  • Detection of indirect prompt injection in tool outputs before they re-enter the agent's context
  • Workflow-graph deviation detection; blocks chains that look authorized at each step but violate intent overall
  • Sub-millisecond decisions; inline or OOB, your choice

The AppSentinels MCP Proxy

A purpose-built enforcement point for the MCP layer. Deploy in-line to enforce every tool call, or out-of-band to observe and learn before turning enforcement on. Either way, the BLG drives the decision.

In-line mode
Every MCP request and response pass through the proxy. Tool calls are authorized against the BLG before they reach the server. Tool outputs are inspected for indirect prompt injection before they re-enter the agent.
Out-of-band mode

Passive observation via sensors. Full visibility, zero added latency, used for greenfield discovery and progressive rollout.

Native integration

Works with the agent frameworks your teams use: LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, and managed runtimes like AWS Bedrock AgentCore.

How AppSentinels Compares

What Others Cover
What AppSentinels Adds
  • Prompt inspection at the LLM boundary
  • Static MCP server allowlisting
  • Generic LLM red-team libraries
  • Network-edge enforcement
What AppSentinels Adds
  • Authorization at the tool-call boundary, where data moves
  • Continuous discovery of shadow servers and rug-pull detection
  • MCP-specific attack coverage tied to your real BLG
  • Sensors and proxy inside the agent runtime, where MCP traffic lives

Don’t Let Autonomous Agent Run Blind. Secure Your MCP Layer Today.

Take control of shadow AI extensions, find logic vulnerabilities automatically, and run real-time security enforcement across your whole workflow ecosystem.

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Frequently Asked Questions

What is Model Context Protocol (MCP) security?

Model Context Protocol (MCP) security focuses on protecting the open standard that connects AI models to data sources and operational tools. Since MCP allows autonomous agents to execute actions and query systems directly, dedicated security is needed to prevent agents from being manipulated into bypassing traditional application controls.

Attackers exploit MCP environments by manipulating the AI agent’s prompt context or poisoning its data sources. This forces the agent to execute unauthorized tools, run malicious commands, or exfiltrate sensitive backend corporate data under the guise of a legitimate user request.

No. Traditional tools inspect static traffic parameters but lack the linguistic and contextual awareness required to understand AI agent behavior. They cannot differentiate between an authorized agent function call and an exploited, multi-step business logic attack.

An MCP Gateway acts as an inline proxy between AI models, agents, and downstream systems. It intercepts traffic in real-time to analyze user intent, enforce least-privilege resource access, and block unauthorized tool executions before they can affect production data.

MCP security is tested using automated red teaming and semantic fuzzing. This process simulates real-world attack workflows, such as prompt injection and tool poisoning, to find logic gaps and over-permissive agent permissions before the application goes live.