Modern ecommerce relies on layers of infrastructure that keep data flowing and interactions secure. There are complex systems needed to coordinate product information, process orders, authorize payments and support customers.

As these systems become more advanced, so do the risks that come with them. Malicious actors use automation to test vulnerabilities, scrape sensitive information and attempt account takeovers.

Autonomous agents

Businesses are starting to shift toward agentic ecommerce models that use autonomous tools to support customer journeys and internal workflows. This shift brings both promise and new points of vulnerability. Agentic commerce security has become a priority because automated agents need permissions and data access that can be exploited if they aren’t properly controlled.

A recent report from McKinsey suggests AI agents will mean a new era for consumers and merchants. Trust is fundamental to business success; Deloitte Insights has shown trusted businesses can experience stronger per capita real GDP growth. These developments highlight why merchants are searching for techniques that make permissions clear, actions auditable and integrations easier to govern.

The Model Context Protocol known as MCP has become an important foundation for these needs. MCP allows tools, models and applications to communicate through controlled interfaces. By adopting MCP based systems, ecommerce teams can create predictable boundaries around how automated tools function.

Datadome

Datadome has introduced MCP protection and agent trust management to address the risks that emerge when autonomous agents interact with ecommerce systems. Its platform analyses every MCP request and classifies traffic based on identity, intent and behaviour. This gives merchants real visibility into which agents are accessing their MCP enabled infrastructure. The system highlights unusual or unwanted activity which helps teams detect issues early.

Datadome’s approach centers around continuous trust evaluation. Agents receive trust scores that change according to how they behave over time. If an agent moves from normal behaviour to patterns that resemble scraping or probing, it can be blocked or rate-limited automatically. This supports safer use of MCP servers without interrupting legitimate agent activity.

Datadome also gives businesses policy-based control over how AI agents operate on their sites and APIs. Merchants can allow, block, rate limit or monetize agent traffic by name or source, and they can apply those rules at page, API or action level. This creates a structured way to manage growing volumes of agent driven requests and to separate trusted agent activity from traffic that poses commercial or security risks.

Integration is straightforward since Datadome provides an MCP enabled module for environments such as Node.js and AWS CloudFront’s Lambda at Edge. This means teams can add protection without major changes to their architecture. Combined with real time classification, trust scoring and clear policy controls, Datadome offers a practical layer of security for merchants adopting agentic commerce and MCP based workflows.

MCP Manager

MCP Manager provides a gateway for securing, observing, and governing MCP deployments. Its platform offers observability through detailed, end-to-end logging of all MCP traffic,  including session and correlation IDs, so teams can audit exactly which agents are calling which tools.

You can define policies for which prompts agents may use, which tools they can call, and which resources they can access. The system also monitors for abnormal behaviour through traffic pattern analysis, helping detect potential risks like misuse or exfiltration.

MCP Manager supports enterprise identity providers such as Okta and Entra, so you can integrate it with existing SSO and SCIM setups. It allows distinct identities to be created for AI agents (separate from human users), which helps maintain least-privilege access and improves traceability.

Golf.dev

Golf.dev offers a protocol-aware firewall and a framework for building secure, production-ready MCP servers. Its Golf Firewall sits in front of MCP servers and inspects MCP traffic at the protocol level, enforcing authentication, authorization, rate limiting, and other security controls.

The firewall supports role-based access control (RBAC), token validation (JWT, OAuth), and detailed event logging. It also provides a single management interface (dashboard) where teams can define security policies, monitor traffic, and trace data flows.

To help protect against MCP-specific threats, Golf Firewall checks for prompt injection, token hijacking and other risks that standard API gateways may miss. It also integrates with enterprise identity systems like Okta and Auth0 and can validate tokens without acting as an identity provider.

GolfMCP (the open-source framework) lets developers build MCP servers with minimal boilerplate. Developers define tools, resources, and prompts in plain Python files, and Golf compiles this into a MCP server. The framework includes support for authentication (JWT, OAuth, API keys), telemetry (OpenTelemetry), and observability. For testing, it supports test suites that validate different aspects of your server, including conversational workflows, security, and compliance.

Last word

A growing share of ecommerce activity now depends on autonomous agents. As this expands, businesses need structured controls that protect data and maintain trust. Choosing a secure MCP aligned solution helps make sure these agent driven processes are safe.