
Golf is an enterprise control plane for the Model Context Protocol (MCP) designed to give security and IT teams full visibility and governance over how AI agents and tools connect to and interact with enterprise systems. It is built for organizations adopting AI tools like Cursor, Claude Code, GitHub Copilot, and custom agents that use MCP to access sensitive data such as codebases, production databases, customer records, and deal pipelines. The platform's main purpose is to discover, enforce policies on, and audit all AI agent and MCP server activity without requiring control over the underlying LLMs or changing how engineers and teams work.
A critical problem in modern enterprises is the ungoverned proliferation of AI agents and MCP connections, creating a significant security and compliance blind spot. Engineers can rapidly connect tools like Cursor to codebases or Claude Code to production databases via MCP in seconds, enabling actions like reading customer records, updating fields, closing issues, and reassigning work without security team notification or approval. Furthermore, agents can be manipulated to exfiltrate data or escalate permissions through hidden instructions, activities that traditional security stacks cannot detect. This lack of visibility and control over AI tool integrations poses substantial risks of data leaks, unauthorized access, and compliance violations.
One of Golf's core capabilities is comprehensive discovery, which allows organizations to see every AI agent, MCP server, and data connection in their environment, including previously unknown or 'shadow' infrastructure. This monitoring extends to tracking usage, data access patterns, and the specific actions performed by each tool. The platform provides a complete inventory of AI interactions, ensuring no connection operates without oversight.
Another key feature is real-time policy enforcement through an MCP Gateway. Golf enables the definition of granular policies per tool, team, and data source to prevent threats like PII exposure, credential leaks, and unauthorized access. Enforcement occurs with sub-millisecond latency, allowing for instant threat blocking and rollback of unauthorized actions without creating friction for legitimate workflows. This functions as an IAM layer specifically for AI agent interactions.
Golf also delivers robust audit and compliance functionality, maintaining a 90-day trail of every prompt, agent action, and data access event. These logs are pre-mapped to major compliance frameworks including SOC 2, ISO 27001, NIST AI RMF, and FINRA requirements. Teams can quickly export evidence and generate compliance reports, transforming agent activity into structured, audit-ready documentation in minutes, which is critical for regulatory pressures.
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The product works by deploying across enterprise endpoints to automatically discover all AI tools and MCP connections. All subsequent MCP traffic is routed through its gateway, where policies are applied. It integrates natively with existing enterprise stacks, including SIEM systems for observability and identity providers via SSO, streaming activity logs for centralized monitoring. This approach provides governance for AI tools that the organization does not directly control, solving a unique gap in the market.
Benefits for users include eliminating the security blind spot for AI integrations, gaining enforceable governance over shadow AI infrastructure, and achieving continuous compliance readiness. Security and IT teams can prevent data breaches and policy violations in real-time, while compliance teams can efficiently meet auditor demands for AI governance documentation. The platform reduces risk without hindering developer productivity or requiring changes to existing AI tool usage.
Concrete use cases include preventing an engineer's Cursor agent from accessing and exporting sensitive customer PII from the CRM, blocking a Claude Code agent from making unauthorized schema changes to a production database, and stopping a compromised Copilot agent from injecting malicious instructions to exfiltrate source code. It also enables generating a SOC 2 compliance report detailing all AI agent access to financial data over the past quarter and enforcing that only the data engineering team's agents can query specific data warehouses.
The target users are security teams, IT administrators, compliance officers, and heads of AI in regulated enterprises, particularly those in financial services, healthcare, and software. Golf integrates with SIEM and observability tools like Splunk, Datadog, and New Relic, and identity and access systems such as Okta, Microsoft Entra ID, and Google Workspace. It addresses specific regulatory pressures including the EU AI Act, FINRA 2026 requirements, and SOC 2/HIPAA audit cycles.
In summary, Golf provides the essential control plane for enterprise AI, delivering the visibility, enforcement, and audit capabilities needed to securely adopt powerful AI agents and MCP connections while meeting stringent compliance obligations.
Golf is designed for security teams, IT administrators, compliance officers, and heads of AI within regulated enterprises, particularly in financial services, healthcare, and software. These users need to govern AI agents and MCP connections that they do not directly control but that access sensitive data like codebases, production databases, and customer records. The platform serves organizations facing regulatory pressures from frameworks like the EU AI Act, FINRA 2026, and SOC 2/HIPAA, requiring documented AI governance, human oversight, and audit trails to avoid compliance findings and penalties.
Updated 2026-03-06