Secure MCP Servers and Agent Skills
Straiker secures Model Context Protocol (MCP) servers and agent skills across their lifecycle. Discover what agents connect to and load, scan for malicious code and risky capabilities, test for exploitable behavior, and enforce runtime controls to stop tool misuse, data exfiltration, and unauthorized actions.
Problem
Every MCP server and agent skill is a new trust decision.
They can give AI agents new instructions, tools, permissions, code, and access to sensitive data. Malicious or misconfigured components can turn legitimate agent capabilities into data exfiltration, unauthorized actions, or compromised systems.
Solution
Make those connections and capabilities visible, testable, and enforceable.
Straiker gives security teams one way to discover MCP servers and agent skills, assess them for risk, test how agents use them, and control dangerous behavior at runtime
Don't let MCP & Skills' strengths be its weakness
Without visibility and control, MCP-powered agent-tool workflows enable privilege escalation, unsafe tool chaining, and sensitive data exposure.
#1 Attack Vector
Tool poisoning via MCP is the top attack vector across every agent type
Straiker Agentic Risk Framework
91%
Of successful attacks on productivity agents result in silent data exfiltration — no jailbreak, no malware required
Straiker STAR Labs, July 2026
17,000+
MCP servers scanned by Straiker, expanding the attack surface every time an agent connects to a new one
The challenge of securing MCP & agent skills at scale
TOOL POISONING, MALICIOUS SKILLS & RUG PULLS
MCP servers and agent skills can change after they are trusted. Attackers can hide malicious instructions in tool descriptions, code, or skills that agents may follow without the user ever seeing them.
OUTPUT INJECTION & UNAUTHORIZED ACTIONS
Agents consume data from tools and connected systems as part of their workflow. Malicious output can manipulate what an agent does next, leading to unauthorized tool calls, data exfiltration, or actions outside the agent’s intended scope.
SHADOW MCP SERVERS, SKILLS & NO INVENTORY
Security teams often lack a complete inventory of the MCP servers and agent skills in use, what capabilities they expose, and what systems or data they can access. Unsanctioned components can bypass security review and operate without clear authorization or audit controls.
How Straiker Secures MCP Servers and Agent Skills
Discover MCP servers, agent skills, and connections
Find the MCP servers and agent skills your agents use. See the tools they expose, systems they connect to, permissions they request, and risky or unsanctioned connections.
Scan MCP servers and agent skills for security risks
Analyze MCP server code and agent skills for malicious instructions, risky capabilities, remote code execution, credential theft, persistence, data exfiltration, obfuscation, and behavior that does not match their stated purpose.
Test how agents use MCP tools and skills
Adversarially test agents for tool poisoning, indirect prompt injection, privilege escalation, unsafe tool use, data exfiltration, and unauthorized actions.
Enforce runtime controls for MCP and agent actions
Apply allow/block policies and runtime guardrails to tool calls, detect misuse, and stop unsafe agent behavior through the gateways and control points already in your environment.
Frequently Asked Questions
What is the Model Context Protocol (MCP) and why does it matter for security?
The Model Context Protocol (MCP) standardizes how AI agents connect to external tools, APIs, and data sources. Securing MCP is critical because agent-tool interactions introduce three distinct risk categories: configuration and hygiene flaws in MCP servers, runtime misuse when agents chain tools in unintended sequences, and supply chain risks from third-party MCP servers with weak authorization or unsafe defaults. Straiker has scanned more than 17,000+ MCP servers and found hygiene flaws across hundreds of them, making MCP security a high-priority control for enterprises deploying AI agents.
What are the main risks in MCP implementations?
The main MCP security risks are supply chain vulnerabilities, unsafe runtime tool use, and visibility gaps. Third-party MCP servers can introduce weak authorization and unsafe defaults, while agents can misuse tools through unintended sequences or unsafe parameters. Without complete visibility into MCP servers, clients, and permissions, security teams can also miss unauthorized access paths. Straiker's Discover AI and Defend AI address all of these risks across discovery, posture, and runtime enforcement.
How does MCP security protect agent-tool interactions?
MCP security inventories servers, applies static risk scoring, and hardens configs. At runtime, Straiker's MCP security tools enforce least privilege, validate inputs and outputs, monitor tool calls, and block unsafe actions to stop misuse and prevent data exfiltration.
How do Straiker products map to MCP security?
Straiker uses a See-Test-Protect approach for MCP security. Discover AI inventories every internal and external MCP server across your agentic ecosystem and scores each one for hygiene risks before they become threats. Ascend AI continuously red-teams your MCP connections, testing for tool poisoning, rug pulls, and privilege escalation. Defend AI enforces runtime guardrails on every tool call, blocking unauthorized actions and data exfiltration at 98%+ accuracy and low latency.
What best practices should teams follow to secure MCP?
Six practices form the foundation of MCP security:
- Maintain a complete inventory of MCP servers and clients so security teams know what exists and what agents can access.
- Scan MCP servers before deployment for hygiene flaws such as weak authorization, unsafe defaults, and misconfigured permissions.
- Enforce least-privilege authorization so agents can access only the tools and data required for their task.
- Validate MCP inputs and outputs to help block prompt injection and other malicious content delivered through tool results.
- Monitor tool calls in real time to detect unsafe chaining, parameter abuse, and policy violations.
- Maintain end-to-end audit logs mapped to compliance requirements for forensics and incident response.
Together, these controls provide visibility, prevention, and runtime enforcement across the MCP attack surface.
Protect EVERY AI AGENT
As enterprises build and deploy agentic AI apps, Straiker provides a closed-loop portfolio designed for AI security from the ground up. Ascend AI delivers continuous red teaming to uncover vulnerabilities before attackers do, while Defend AI enforces runtime guardrails that keep AI agents, chatbots, and applications safe in production. Together, they secure first- and second-party AI applications against evolving threats.
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Secure the agentic frontlines
You’re building at the edge of AI. Forward-thinking teams use Straiker to secure AI agents, detect emerging attack paths, and safely scale agentic AI across their organization. With Straiker, you have the confidence to deploy fast and scale safely.
