By Prefactor

Get Ready for
MCP

The Model Context Protocol is rewriting how AI agents connect to your systems. Every SaaS platform will soon have thousands of autonomous agents. Is your organisation ready to govern them?

Take the Assessment Read the White Paper
The Protocol

MCP is the connectivity layer
for the agentic era

The Model Context Protocol is an open standard that defines how AI agents communicate with tools, APIs, and data sources. It\u2019s being adopted by every major AI platform \u2014 and it changes everything.

A universal protocol for agents

MCP is the open standard that lets AI agents communicate with tools, APIs, and data sources. Think of it as USB-C for AI — one protocol, every connection.

From integration to orchestration

Before MCP, every agent-to-tool connection was custom-built. MCP standardises the interface so agents can discover, negotiate, and interact with any MCP-enabled service.

Agents as first-class citizens

MCP marks the moment AI agents stop being assistants and start being autonomous actors. They browse, execute, decide, and build — across your entire ecosystem.

119% surge in enterprise agent adoption in H1 2025
79% of senior executives deploying AI agents operationally
33% of enterprise software will include agentic AI by 2028
The Reality

AI agents are coming.
Most organisations aren't ready.

The gap between piloting agents and deploying them isn't a technology problem. It's a governance problem.

97%
of AI breach victims lacked proper AI access controls
MCP solves interoperability — but it doesn’t solve identity. It defines how agents communicate, not how they’re verified, authorised, or audited. Without identity at the protocol layer, you’re scaling connectivity without control.
⚠

Legacy IAM was built for humans

Traditional identity systems rely on MFA, CAPTCHAs, and manual provisioning — workflows agents can’t complete. Teams bypass security entirely.

⚠

No accountability without identity

Without delegated authority and clear ‘on-behalf-of’ flows, platforms risk compliance failures, data exposure, and regulatory issues.

⚠

Agent behaviour is unpredictable

Agents operate autonomously, across domains, at machine speed. Existing IAM can’t handle the scale, speed, or dynamism.

Where It Matters

MCP in the real world

MCP unlocks powerful agent capabilities. But without identity and governance, every connection is a liability.

SaaS platform integration

Scenario

Your CRM deploys an AI agent that autonomously qualifies leads, updates records, and triggers workflows across Slack, HubSpot, and your billing system.

Without governance

Without governed MCP connections, this agent has unchecked access to customer data across every integrated platform.

With MCP-native identity

With MCP-native identity, every action is attributable, scoped, and auditable — the agent operates within defined boundaries.

Multi-agent supply chain

Scenario

Procurement, logistics, and finance agents negotiate contracts, track shipments, and process payments — coordinating across organisational boundaries.

Without governance

Agents operating across trust boundaries with borrowed credentials create uncontrolled access sprawl.

With MCP-native identity

Federated MCP authentication lets agents traverse ecosystems with verifiable, scoped credentials — no shared secrets.

Autonomous compliance monitoring

Scenario

An agent continuously monitors regulatory changes, updates internal policies, and triggers remediation workflows across your tech stack.

Without governance

A compliance agent with write access to policy systems and no audit trail is itself a compliance risk.

With MCP-native identity

Agent identity with lifecycle controls ensures every policy change is traceable, approved, and reversible.

“Thinking MCP is a ‘nice-to-have’ integration layer is a mistake. It’s an identity problem at scale. Every agent, every API, every human needs to be authenticated and controlled on the same footing.”

— Simon Russell, CTO, Prefactor
The Maturity Curve

Four stages from experimentation
to agents at scale

Every organisation is somewhere on this curve. Take the assessment to find out where you are — and what it takes to move forward.

01
Unaware
“What is MCP?”
02
Exploring
“We’re evaluating MCP”
03
Integrated
“Agents connect via MCP”
04
Orchestrated
“MCP at scale, governed”
Free Assessment

Find your place on the curve

Answer a few questions about how your organisation handles AI agents today. You'll get your maturity stage and what to focus on next.

Redefining Digital Trust — White Paper Cover
Go Deeper

Redefining Digital Trust

How MCP is Securing the Next Generation of AI Agents

The definitive guide to the shift from IAM to Agent Identity and Access Management. Backed by data from IBM, Salesforce, Gartner, and real breach analysis.

  • Why traditional IAM fails in agent-driven environments
  • The shift from IAM to Agent Identity & Access Management (AIAM)
  • Real-world breach analysis: the Salesforce/Drift incident
  • How MCP-native identity delivers audit-grade trust
  • Three forces reshaping agent identity at scale
  • Why early movers gain compounding advantage
Download White Paper (PDF)
Built by Prefactor

We help organisations
move up the curve

Prefactor helps enterprises close the gap between AI experiments and AI agents in production. We build the governance frameworks, control planes, and operational infrastructure that move organisations from Stage 1 to Stage 4.

This is our open resource — raising the bar for how enterprises think about agent governance before they deploy.

Learn more about Prefactor →
🔒

MCP-Native Identity

Authentication and governance built directly into the protocol layer where agents operate

🏗️

Agent Control Plane

Centralised registry, lifecycle management, and policy enforcement for every agent

🔌

Secure Connectivity

Governed, auditable agent-to-tool connections via MCP at enterprise scale

🚀

Rapid Deployment

From MCP prototype to production in weeks, not quarters

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