Independent trust and safety assessments for the AI agents and MCP servers connecting to your business systems.
Designed for the agent economy
AI tools request access to systems without standardized trust verification.
Security, governance, and compliance posture is hard to assess from the outside.
Anyone can publish an MCP server. Few are independently assessed.
Prompt injection, tool poisoning, and supply-chain attacks are accelerating.
Approve or block AI tools using independent trust assessments.
See how reviews work →Create safer ecosystems and trusted integrations.
Partner with Metinc →Increase credibility and adoption through independent validation.
Submit your server →Enterprise apps with AI agents by end of 2026
Leaders say AI governance is inadequate
Plan agentic AI deployments within two years
Increase in worker access to AI systems
One independent assessment connects every party — from the agent requesting access to the business system granting it.
One assessment · Every party protected
As organizations adopt AI at speed, understanding the security and governance fundamentals has never been more important.
A Model Context Protocol (MCP) server is a software component that exposes tools, data, and APIs to AI agents and large language models. MCP servers allow AI systems to read files, query databases, execute code, and interact with enterprise applications. Because an MCP server acts as a gateway between an AI agent and business systems, its security posture, permission scope, and data handling practices must be independently assessed before enterprise deployment.
An AI Trust Assessment is an independent, structured evaluation of an AI agent, MCP server, or AI platform. It produces a quantitative Trust Score and risk report covering security architecture, permission boundaries, data handling, abuse resistance, and governance maturity. Enterprises use AI Trust Assessments to make evidence-based decisions about which AI tools to approve, monitor, or block before granting access to Jira, GitHub, Slack, Salesforce, or internal systems.
AI Governance is the set of policies, processes, and controls organizations use to manage AI systems responsibly. Enterprise AI governance addresses risk assessment frameworks, AI tool procurement approval, access management, continuous monitoring, audit logging, and incident response. As AI adoption accelerates, AI governance is becoming a regulatory and operational requirement for enterprises in financial services, healthcare, and other regulated industries.
Agentic AI Risk refers to the security and governance risks that arise when AI agents operate autonomously — taking sequences of actions, using tools, and accessing systems without step-by-step human oversight. Key risks include prompt injection via external data sources, excessive tool permissions, uncontrolled multi-agent delegation, data exfiltration, and unintended actions at machine speed. Independent risk assessments are the primary control for managing agentic AI risk before deployment.
Metinc was founded with a mission to help businesses succeed through technology, talent, and innovation. Today, as organizations adopt AI at unprecedented speed, Metinc is expanding its focus into AI Trust, Safety, Governance, and Compliance while continuing to provide AI consulting, staffing, staff augmentation, and training services.
Search independently assessed MCP servers and check their Trust Scores before connecting them to your systems.
The directory below is a visual concept and work in progress. Scores and assessments are illustrative examples only.
Metinc builds the trust layer. You build the future.
Tell us about the AI agent, MCP server, or AI service you want assessed. Our team will review your request and get back to you.
