Best AI Agent Security Platforms for Model Context Protocol (MCP)

Akto is an open source, instant API security platform that takes only 60 secs to get started. Akto is used by security teams to maintain a continuous inventory of APIs, test APIs for vulnerabilities and find runtime issues. Akto offers tests for all OWASP top 10 and HackerOne Top 10 categories including BOLA, authentication, SSRF, XSS, security configurations, etc. Akto's powerful testing engine runs variety of business logic tests by reading traffic data to understand API traffic pattern leading to reduced false positives. Akto can integrate with multiple traffic sources - Burpsuite, AWS, postman, GCP, gateways, etc.

AgentShield is an innovative identity platform designed to authenticate both human users and AI agents representing them. It allows organizations to verify an agent's identity, confirm the authorization from the individual behind the agent, and assess the agent's reliability, all through user-friendly APIs and JavaScript integrations. This platform also features capabilities for identifying agent interactions on websites and implements identity and permission validations for both agent-to-agent and agent-to-service communications, adhering to the open Model Context Protocol Identity (MCP-I) standards. Additionally, with the KYA feature, companies can effectively oversee agent identities and their permissions, establish audit trails, automate workflows, and apply precise access controls for autonomous systems. This comprehensive approach not only safeguards against the misuse of digital identities but also promotes clarity when AI systems operate on behalf of users, ultimately enhancing trust in digital interactions. As technology evolves, maintaining such robust security measures becomes increasingly crucial for organizations navigating the complexities of digital identity management.

Enkrypt AI is a specialized platform designed for enterprise-level security, compliance, and governance in the realm of artificial intelligence, focusing particularly on safeguarding large language models, AI agents, multimodal systems, and machine-critical processes. Catering to industries such as finance, healthcare, insurance, and government, Enkrypt AI empowers organizations to innovate quickly while ensuring safety and maintaining a competitive edge. The platform addresses the entire spectrum of AI security through several key features: Guardrails: With ultra-low latency (under 50 milliseconds), policy-driven guardrails effectively mitigate risks associated with prompt injections, unauthorized data exposure, hazardous outputs, and non-compliant behavior of agents in real-time. Red Teaming: The system implements policy-driven multimodal attack simulations for LLMs and AI agents prior to their deployment in order to identify vulnerabilities. MCP Security: The MCP Scan Hub and Secure MCP Gateway offer comprehensive protection for MCP servers, tools, and agent toolchains throughout the entire process. Compliance: Ongoing monitoring ensures adherence to standards such as NIST AI RMF, OWASP LLM Top 10, the EU AI Act, HIPAA, and FINRA, with certifications including ISO 27001 and SOC 2 Type II. Recognized as a Gartner Cool Vendor for 2025, Enkrypt AI sets itself apart in the industry.

Snapper serves as a comprehensive security platform for AI agents, aimed at ensuring thorough governance and protection for organizations that utilize AI across various applications, networks, and systems. It implements runtime enforcement by scrutinizing every action an agent takes, such as tool interactions, API calls, and data access requests, prior to execution, utilizing a multi-layered policy-driven rule engine. Additionally, Snapper provides a holistic view of AI activity by analyzing network traffic, browser usage, DNS queries, and running processes to uncover unauthorized tools and hidden AI applications. It also proactively intercepts outgoing large language model requests via SDK wrappers and a network proxy, allowing it to assess, redact, and document sensitive information in real time. Enhancing its security features, Snapper possesses sophisticated threat detection mechanisms that can recognize prompt injection tactics, exploit chains, unusual behaviors, and complex attack patterns, leveraging behavioral baselines, kill chain analysis, and a composite trust scoring system for robust protection. Ultimately, Snapper represents a critical asset for organizations seeking to navigate the risks associated with AI deployment while maintaining operational integrity.

General Analysis serves as a cutting-edge AI security platform designed to aid security teams in adversarially testing, monitoring, and safeguarding AI agents and systems that are actively deployed. Its primary objective is to enable organizations to grasp AI-related risks, avert potential incidents, and secure various real-world AI applications, which include employee copilots, coding agents, customer support tools, healthcare assistants, legal aids, financial copilots, and creative workflows. By mapping out AI applications and agents through an extensive range of parameters such as prompts, retrieval methods, tools, MCP servers, browser activities, permissions, repositories, cloud accounts, SaaS workflows, and business processes, it effectively identifies context-aware attacks that highlight vulnerabilities within the system. The platform's automated red teaming employs adaptable attacker models that respond to target behaviors and generate complex multi-step exploit chains, providing security teams with the ability to discover vulnerabilities that traditional static prompt sets or endpoint-only testing might overlook. Ultimately, General Analysis empowers organizations to enhance their AI security posture while ensuring that their deployments remain resilient against evolving threats.

Pillar Security serves as a comprehensive AI security platform designed to safeguard the agentic workforce throughout the entire AI lifecycle, encompassing stages from development to deployment and ongoing runtime protection. By integrating business context during phases of discovery, testing, and protection, it ensures that security intelligence accumulates across various AI applications, including agents, models, prompts, frameworks, tools, MCP servers, skills, coding agents, and both SaaS and cloud environments. The platform enables organizations to identify and manage AI assets effectively, even those that are unapproved or fall under shadow AI, while also evaluating risks related to supply chain and overall security posture. Additionally, it maps out the attack surfaces associated with agentic systems and verifies critical vulnerabilities that need addressing. With its AI Security Posture Management features, Pillar scrutinizes interconnected agents, tools, permissions, data sources, prompts, models, and supply chain elements to reveal high-risk pathways, policy breaches, misconfigurations, and potential threats posed by coding agents, all of which enhance the understanding of the impact when a single component encounters a breach. Ultimately, Pillar Security empowers organizations to maintain a robust security framework while navigating the complexities of AI technology.