Runlayer

Overview

Runlayer is the enterprise control plane for MCP servers, skills, and agents. It gives organizations a single place to host, govern, and secure the AI tools their employees rely on — across clients like Cursor, Claude Code, ChatGPT, and VS Code — without forcing users to change their workflows. The platform combines a curated catalog of vetted MCP servers with real-time threat detection, identity-aware access control, and full observability across every agent action.

Classification

Coverage surface

MCPEndpointSaaSCloudData/DBAPI

Stage

Launched

Type

Commercial

Target audience

Enterprise

Deployment

SaaSSelf-hostedHybrid

Technical profile

Spec-grounded axes, verified by the TWG.

Interception architecture (R1)

Protocol GatewaySDK Instrumentation

Policy model (R3)

Hybrid

Authorization decisions (R4)

ALLOWDENYMODIFYSTEP_UPDEFER

Conformance level

Extended (R1–R9)

Conformance review

Platform capabilities

• MCP gateway that proxies every tool call with real-time policy enforcement
• Shadow detection and enforcement at the endpoint level via MDM and EDR
• Purpose-built ML threat detection models trained on MCP-specific attacks
• Deep identity integration with Okta, Entra, SSO, and SCIM
• Tamper-evident audit logs of every agent action and tool call
• Slack-based human-in-the-loop approval workflows for sensitive actions
• Semantic distance tracking across long agent task horizons (R7)
• Telemetry export to Splunk, Datadog, Honeycomb, and S3 (R8)
• Least-privilege credential and tool scoping at execution time (R9)

Architecture

Runlayer enforces AARM requirements through two complementary interception patterns. The primary gateway pattern sits between AI clients and MCP servers, proxying every tool call through a control plane where policies and ML security models evaluate the request before it reaches downstream systems. A secondary shadow pattern extends visibility and enforcement to endpoints, so activity originating on local developer machines is brought under the same policy surface. Context accumulation is handled through full session reconstruction across clients and tools, giving the platform end-to-end visibility into agent intent and actions across the full lifecycle. Authorization decisions, identity bindings, and policy evaluations are written to an append-only audit layer.

Key facts