LangProtect Vector is an AI agent and MCP security gateway built to secure the connections between autonomous AI agents, tools, APIs, and MCP servers. It provides a security layer around agentic AI workflows so organizations can inspect and control actions before an agent interacts with external systems or executes sensitive operations.
What LangProtect Vector does
AI agents can do more than generate text. They can call APIs, access tools, interact with business systems, retrieve data, and trigger actions. That creates a different security problem from traditional LLM applications.
Vector evaluates agent activity at the point where AI intent becomes an action. It helps validate tool calls, detect indirect prompt injection and malicious instructions, enforce security policies, and reduce unauthorized use of connected tools and services.
This gives security and engineering teams greater control over how AI agents behave across MCP-based and other agentic workflows.
Security for MCP and agentic AI
Model Context Protocol makes it easier for AI agents to connect with external tools, data sources, and services. That flexibility also expands the attack surface when agents process untrusted content or receive manipulated instructions.
Vector is designed to help organizations apply controls around these interactions rather than relying only on the model to decide what is safe. This is especially important for autonomous workflows where an unsafe instruction could result in a real action against an API, internal application, database, or connected business tool.
Key capabilities
AI agent security
MCP security gateway
Tool-call validation
Indirect prompt injection protection
Intent-aware policy enforcement
Unauthorized tool-use prevention
Sensitive data protection
Agent permission controls
Real-time threat detection
MCP server protection
Security monitoring
Audit logs and activity visibility
Who LangProtect Vector is for
Vector is designed for AI engineers, developers, security teams, platform teams, DevOps teams, CISOs, and enterprises building or deploying autonomous AI agents.
It is particularly relevant for organizations using MCP servers, agent frameworks, AI assistants with tool access, multi-step automated workflows, or AI systems that interact with sensitive enterprise applications and data.
Why agent security matters
Agentic AI increases the potential impact of prompt injection and permission mistakes because agents can turn model decisions into actions. Organizations therefore need security controls around permissions, tool execution, sensitive data access, and agent activity rather than depending only on prompts or built-in model safeguards. Agentic systems introduce risks such as prompt injection and task hijacking as their autonomy increases.
LangProtect Vector is part of the https://www.langprotect.com/" title="LangProtect Enterprise AI Security (opens in new tab)">LangProtect Enterprise AI Security platform. https://www.langprotect.com/guardia-for-employees" title="LangProtect Guardia (opens in new tab)">LangProtect Guardia protects employee use of generative AI, while https://www.langprotect.com/armor-for-ai-apps" title="LangProtect Armor (opens in new tab)">LangProtect Armor protects enterprise AI applications at runtime.
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