Model Context Protocol (MCP) security tools focus on securing machine learning (ML) and AI systems throughout their supply chain. As AI goes through several stages, starting from data collection, model training, deployment and updates, they become vulnerable to threats. MCP scanning tools help tackle these risks by providing strong mechanisms.
In this blog we explore some of the top MCP security tools that offer strong security features to protect against multiple MCP risks and vulnerabilities.
What are MCP Security Tools ?
MCP Security tools are security solutions that protect MCP servers from various threats such as misconfigurations, data poisoning, prompt injection and cross-server attacks. These types of MCP risks commonly occur from connecting AI models to external systems and sensitive data. That is why it is imperative to adopt security tools which helps maintain compliance, trust and efficiency in complex MCP ecosystems.
Why are Security Tools Critical for MCP ?
MCP Scanning Tools are critical because they form the backbone of reliable, safe and responsible AI integrations in current interconnected era. Without strong security tools, MCP significantly increases the attack surface, exposing organizations to new wave of threats. Apart from this, MCP lacks built-in enterprise grade protections such as approval workflows, server-side validation and vigorous audit trails.
MCP security tools are essential to secure AI pipeline from various technical risks, vulnerabilities and data exfiltration. As AI systems become more advanced and integrated in digital business operations, the necessity for automated, instant threat discovery by AI-Powered MCP security tools becomes extremely important to ensure data privacy, regulatory compliance and operational integrity.
Top 10 MCP Security Tools
There are numerous reliable MCP security tools for securing MCP servers. These tools will help ensure your AI ecosystems are safe, secure, and efficient:
1. Akto.io
Akto’s is among the best MCP security tool. It has introduced industry first MCP security platform which performs automatic discovery, testing, and real-time monitoring of AI orchestration layers. The tool provides protection against prompt injection, tool poisoning, misconfigurations and sensitive data leaks.
Image source: Akto
Features:
MCP server and API discovery across cloud, hybrid or on-premise environments via 50+ connectors.
Sensitive data exposure notification alerts to capture data leaks and misconfigurations within MCP interactions.
Continuous real-time monitoring of API patterns, response structures, tool usage and execution context.
Threat detection analytics that highlight suspicious and harmful behavioral patterns, IP, and reputation insights.
Security testing with large library that targets unauthorized access, insecure authentication, tool poisoning and prompt injection.
Ideal For:
AppSec and DevSecOps teams utilizing LLM’s , agent frameworks, or AI orchestration specifically those looking for complete security visibility and security in modern AI-driven environments.
2. Palo Alto Networks
Palo Alto Network introduced MCP security within its cortex cloud WAAS to secure AI apps Model context protocol communication. It conducts validation of interactions, prevents API-based attacks, protects data and ensures model integrity which enables secure AI innovation across sensitive systems.
Image source: Palo Alto
Features:
MCP communication validation to prevent unauthorized or malformed context requests.
Model integrity implementation to ensure LLM’s receive only genuine and intended output.
API-based attack prevention, securing AI integrations from misuse or exploitations.
Secure innovation enablement, letting organizations implement AI confidently without compromising security.
Sensitive data protection, restricting unauthorized access to context and resources.
Ideal For:
AppSec, DevSecOps and Cloud security teams using AI orchestration or LLM architectures who require strong runtime protection for Model context protocol interactions.
3. Pillar Security
Pillar Security offers a unified platform to discover, analyze and protect AI systems, MCP servers, LLM’s, RAG workflows, pipelines, datasets and prompts. It ensures runtime security, visibility and data governance across complete AI lifecycle.
Image source: Pillar
Features:
Automated discovery and inventory of MCP servers and agents which removes blind spots across multiple environments.
Complete logging and anomaly detection, capturing prompts, tools calls and behaviors for auditing and compliance.
Adaptive runtime guardrails, implements custom policies, performs threat detection on MCP interactions.
Sensitive data protection, prevent data leaks or misuse of context and prompt hijack detection.
Threat analysis with dynamic modeling and red tanning, it also analyzes prompt injection, DoS, insecure outputs and agent hijacking.
Ideal For:
AI, DevSecOps, and AppSec teams handling agentic AI workflows, who are looking for full-spectrum security from visibility, risk assessment, runtime protection and compliance.
4. Teleport
Teleport’s infrastructure identity platform has introduced its zero-trust architecture to MCP. It offers security to LLM interactions and infrastructure data. It implements strict access control, least privilege authorization and comprehensive audit trails. It allows security teams to adopt AI with enterprise-grade identity governance.
Image source: Teleport
Features:
Zero-trust architecture integration, apply existing infrastructure identity controls to LLM workflows.
Complete audit logging capturing all MCP requests, successful or denied for full traceability.
Principle-of-least-privilege enforcement, tightly scoping LLM permissions to required actions only.
Unified identity governance, leveraging Teleport’s platform to handle machine identities and human consistently.
Strict, granular access control through RBAC and attribute-based policies, ensure LLM’s access only explicitly authorized resources.
Ideal for:
Security, AppSec and DevOps teams embedding LLM’s into production systems that require enterprise-grade identity-based access control, auditability and zero-trust assurance for AI-driven infrastructure workflows.
5. Invariant’s MCP-Scan
Invariant Labs empowers secure, strong agentic AI tools like explorer, guardrails, gateway and MCP scan. It offers static analysis, contextual runtime protection and auditing for MCP servers. Prevents tool poisoning, toxic flows and integrity attacks.
Image source: Invariant
Features:
MCP-Scan static server analysis to capture tool poisoning, rug pull attacks, cross origin attacks, prompt injection and suspicious flows in tool descriptions.
Runtime proxying guardrails through MCP-scan proxy to monitor, log and block dangerous MCP traffic dynamically.
Tool pinning with hashing to avoid MCP rug pulls by verifying tool integrity over time.
Cross-origin escalation detection guarding against malicious tool shadowing across MCP servers.
Integrated observability through explorer and gateway, it offers tracing, audit logs, and contextual debugging for MCP requests and agent decisions.
Ideal For:
DevSecOps and security teams who are building agentic AI or LLM orchestration platforms that need advanced MCP security to ensure static and runtime defense against protocol-level threats.
6. ScanMCP.com
ScanMCP is the first dedicated security scanner for MCP based Artificial intelligence systems. It offers fast, cloud based scanning and real-time monitoring of MCP workflows detecting context drift, protocol misconfigurations, insecure transports, tool poisoning and suspicious activity across Claude integrations.
Image source: ScanMCP
Features:
Smart context mapping visualizing data flows between GitHub, Postgres, Claude, Slack and other integrations.
AI-Powered threat detection which showcases broken links, outdated context, insecure configurations or failed syncs using advanced scanning.
Deep protocol scanning for broken transports, malformed roots and inaccurate configurations across MCP stack.
Cloud-based, zero-trust design with enterprise-grade encryption and OAuth protection which ensures privacy and secure deployment.
Real-time sync checking to capture client-server desyncs instantly and ensure context remains consistent.
Ideal For:
DevSecOps and security teams that build MCP-driven agentic workflows seeking proactive scanning, real-time monitoring and threat identification to secure context based AI infrastructure.
7. Equixly’s CLI/Service
Equixly offers MCP security such as proactive scanning, validation and governance to protect AI orchestration environments and helps in preventing critical protocol threats.
Image source: Equixly
Features:
Context-drift and prompt injection security, sanitizing parameters and implementing user confirmation or sensitive operations.
Authentication and authorization validation which enforces OAuth spec compliance and least-privilege to protect against confused-deputy issues.
It offers static vulnerability scanning to detect command injection, malformed transports path traversal, SSRF and unsafe shell calls.
Logging and anomaly detection which captures tool calls, parameter values and abnormal behaviors for auditing and alerting.
Supply-chain integrity checks which includes version pinning, code signing, SAST/SCA in CI pipelines and change notifications for MCP tools and servers.
Ideal For:
DevSecOps, AI security and AppSec teams implementing MCP-based agentic workflows that need vigorous protocol level inspection, access controls and supply chain protection.
8. MCP Guardian (by EQTY Lab)
MCP Guardian is a security first proxy platform that provides real-time control over LLM interactions with MCP servers. It provides message logging, approvals, automated scans and zero-trust guardrails across configurations which ensures enterprise grade oversight and prevention of threat.
Image source: MCP Guardian
Features:
Message logging records every LLM - MCP server interaction trace for complete visibility.
Automated message scans means planned real-time safety and privacy checks on all MCP traffic.
Real-time message approvals lets users approve or deny individual tool calls before execution.
Proxy-based guardrails, it intercepts and implements policy on MCP requests/responses without in-depth integration.
Multi-server management helps organize, switch between and apply guard profiles across collections of MCP server.
Ideal for:
Security-focused developers, DevSecOps and AppSec teams integrating MCP servers who require interactive control, authorization, auditability and policy enforcements for LLM workflows.
9. Prompt Security
Prompt security platform secures agentic AI by implementing an MCP gateway for real-time endpoint control and a risk assessment engine. It provides dynamic implementation, continuous monitoring, deep code inspection. It empowers safe, supervised execution of MCP driven workflows.
Image source: Prompt Security
Features:
Automatic implementation of security policies through blocking unauthorized actions, prevents malicious prompts and sanitizes dangerous MCP traffic in real-time.
MCP risk assessment engine performs dynamic and static analysis on MCP server code to capture vulnerabilities, misconfigurations and insecure metadata.
Comprehensive audit logging includes capturing full prompts and responses for every MCP interaction to support traceability and compliance.
Dynamic risk scoring assigns and updates risk scores to MCP servers based on their code quality, updates, governance standing and security posture.
MCP Gateway for endpoint control such as agent-based strategy monitors, governs every MCP server interaction on user devices, tracks authorized and shadow MCPs.
Ideal for:
AppSec, security teams and DevSecOps managing agentic or tool supported AI systems, particularly those implementing MCP servers in desktop, cloud or internal applications looking for endpoint-level control, real-time enforcement and continuous risk assessment.
10. Cyber MCP
CyberMCP is an open-source MCP server designed for AI-Powered security testing of backend APIs. It consist of LLM agents with tools to find authentication, injection, DoS, leakage, header risks, simplifying proactive API hardening.
Image source: CyberMCP
Features:
Injection vulnerability scanning for SQL injection and XSS vulnerabilities across API endpoints.
Data leakage identification flags data exposure and path traversal issues.
Authentication testing suite comprise of JWT analysis, bypass detection, token and OAuth2 flows to find authorization weakness.
Security headers validation helps verifying presence and correctness of OWASP recommended HTTP headers.
DoS assessment and Rate limit captures weaknesses in rate limiting and DoS protections.
Ideal for:
DevSecOps teams, AppSec professionals, Security driven AI developers who are looking for fast, context driven security testing via MCP.
Final Thoughts
All in all, the above top 10 MCP security tools are great choices, which offer reliable and strong features, if you are looking to strengthen your MCP ecosystem.
Akto recently introduced industry first AI-powered MCP security platform, where security teams can conduct instant detection of insecure agents, real time scanning, AI behavior drifting, access pattern anomaly detection and more. Akto’s MCP security solution is built for modern AI stacks which lets you identify shadow MCPs, audit AI agent activity and tackle attack even before they impact your production.
Want to be an early adopter for Akto MCP security? Connect with our security experts today!
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