ATLAS-GATE-MCP

Enterprise Model Context Protocol Security Gateway with MCP-Only Sandbox Enforcement

High-Level Overview

ATLAS-GATE-MCP is a production-grade Model Context Protocol (MCP) server that implements enterprise-grade security governance, process-level sandbox enforcement, and comprehensive audit trails for AI agent operations. The system transforms unconstrained AI agents into governed execution authorities through a multi-layered security architecture that enforces zero-trust principles, plan-based authorization, and immutable audit logging.

The system addresses the fundamental security challenge of allowing AI agents to interact with critical systems while maintaining enterprise-grade security posture, compliance requirements, and operational visibility. ATLAS-GATE-MCP serves as a security gateway that mediates all AI agent interactions with development environments, enforcing strict governance policies while providing the flexibility required for modern AI-assisted development workflows.

ATLAS-GATE-MCP operates as an MCP server/gateway in modern AI infrastructure, sitting between AI models/clients and target systems (filesystems, databases, APIs, development tools). It is designed for enterprise environments where security, auditability, and compliance are non-negotiable requirements.

MCP Fundamentals

The Model Context Protocol (MCP) is a standardized protocol for enabling AI models to securely interact with external systems, tools, and data sources. MCP provides a structured framework for AI agent operations that addresses the limitations of traditional integration approaches.

Core Concepts and Terminology

• MCP Server: A process that exposes capabilities to AI models through standardized interfaces. ATLAS-GATE-MCP is an MCP server.

• Tools: Executable functions that AI models can invoke. Tools have defined schemas, parameters, and return values. Examples include file operations, API calls, database queries.

• Resources: Read-only data sources that AI models can access. Resources represent static or dynamic data like configuration files, documentation, or system state.

• Prompts: Reusable prompt templates that guide AI model behavior for specific tasks or contexts.

• Transport Layer: Communication mechanism between AI models and MCP servers, typically JSON-RPC 2.0 over stdio or HTTP.

• Session: A bounded interaction context between an AI model and MCP server with associated state and permissions.

Design Philosophy

MCP exists to solve fundamental architectural problems in AI agent integration:

1. Security Isolation: Prevents AI models from having unrestricted system access

2. Standardization: Provides consistent interfaces across different AI models and tools

3. Governance: Enables policy enforcement and audit trails for AI operations

4. Composability: Allows tools and capabilities to be combined safely

5. Observability: Provides visibility into AI agent operations and decision-making

Compared to traditional APIs, MCP offers:

• Schema Validation: All tool inputs/outputs are validated against defined schemas

• Capability Discovery: AI models can discover available capabilities dynamically

• Security Boundaries: Built-in authentication, authorization, and audit mechanisms

• State Management: Proper session handling and state isolation

• Error Handling: Structured error responses with appropriate context

Compared to plugin-based systems, MCP provides:

• Protocol Standardization: Consistent interface across different implementations

• Security Model: Built-in security considerations rather than afterthought

• Transport Independence: Multiple communication patterns supported

• AI-First Design: Designed specifically for AI model interaction patterns

Atlas-Gate Architecture

ATLAS-GATE-MCP implements MCP through a multi-layered security architecture with strict separation of concerns and comprehensive enforcement mechanisms.

Core Components

• MCP Server Core (server.js): Central request handling, tool registration, and session management. Implements JSON-RPC 2.0 transport, input normalization, and request routing.

• Dual-Role System: Two distinct operational modes with different security boundaries:

  • Windsurf Role: Execution and mutation capabilities with full audit logging

  • Antigravity Role: Read-only analysis and planning capabilities

• Tool Registry: 17 specialized tools covering file operations, plan management, audit logging, and attestation services. Each tool implements comprehensive validation and enforcement.

• Governance Engine: Multi-layer policy enforcement including:

  • Input validation with Zod schemas

  • Plan-based authorization checking

  • Static analysis for forbidden patterns

  • Content integrity verification

  • Audit trail generation

• Security Layers:

  • Process-level sandbox enforcement

  • MCP-only operation restrictions

  • Session-based isolation

  • Cryptographic audit trails

  • Role-based access control

Trust and Authorization Boundaries

• Trust Boundary 1: Process isolation through MCP sandbox prevents direct system access

• Trust Boundary 2: Role separation ensures read-only operations cannot mutate data

• Trust Boundary 3: Plan authorization requires explicit approval for operations

• Trust Boundary 4: Content validation prevents injection of malicious code

• Trust Boundary 5: Audit logging provides non-repudiation and traceability

Component Security Responsibilities

• Server Core: Request validation, session management, transport security

• Tool Handlers: Input validation, business logic enforcement, audit generation

• Governance Engine: Policy enforcement, content analysis, authorization checking

• Audit System: Immutable logging, tamper detection, compliance reporting

• Sandbox Layer: Process isolation, resource restriction, capability limiting

Architecture Diagram

How Atlas-Gate Works (Step-by-Step)

Initialization and Startup

1. Process Launch: Server starts as either Windsurf or Antigravity role based on entry point

2. Sandbox Activation: Process-level restrictions are applied via lockdownProcess() and freezeGlobalObjects()

3. Self-Audit: Server analyzes its own code for governance violations before accepting connections

4. Session Generation: Cryptographic SESSION_ID is generated for audit trail correlation

5. Transport Binding: JSON-RPC 2.0 server binds to stdio transport for MCP communication

6. Tool Registration: All available tools are registered with their Zod schemas and handlers

7. Capability Discovery: Server publishes available capabilities to connecting clients

Configuration and Capability Registration

1. Role Determination: Server capabilities are filtered based on role (Windsurf vs Antigravity)

2. Tool Schema Definition: Each tool defines input/output schemas using Zod for validation

3. Permission Mapping: Tools are mapped to required permissions and authorization levels

4. Plan Discovery: Available plans are scanned and cached for authorization checking

5. Audit Configuration: Audit logging parameters and retention policies are established

Server Lifecycle and Request Handling

1. Connection Acceptance: New JSON-RPC connections are accepted and authenticated

2. Session Initialization: begin_session must be called to establish workspace context

3. Request Reception: JSON-RPC 2.0 requests are received via stdio transport

4. Input Normalization: Raw inputs are normalized to structured objects

5. Schema Validation: Request parameters are validated against tool schemas

6. Authorization Checking: Plan-based authorization is verified before execution

7. Content Analysis: Static analysis scans for forbidden patterns and security violations

8. Execution: Business logic is executed with comprehensive error handling

9. Audit Logging: All operations are logged with full context and cryptographic signatures

10. Response Generation: Structured responses are formatted and returned

Model Discovery and Invocation of MCP Capabilities

1. Capability Enumeration: AI models can list available tools and their schemas

2. Tool Selection: Models select appropriate tools based on task requirements

3. Parameter Preparation: Input parameters are prepared according to tool schemas

4. Plan Reference: Operations must reference an approved plan for authorization

5. Invocation: Tools are invoked via JSON-RPC 2.0 method calls

6. Result Processing: Responses are parsed and integrated into model reasoning

7. Error Handling: Structured error responses guide model recovery strategies

Request/Response Flow

1. Request Reception: JSON-RPC 2.0 call received with method, parameters, and request ID

2. Method Resolution: Appropriate tool handler is selected based on method name

3. Parameter Extraction: Parameters are extracted and type-validated

4. Context Establishment: Session context and workspace state are resolved

5. Authorization Verification: Plan-based authorization is checked and validated

6. Pre-execution Validation: Input sanitization and security scanning occur

7. Business Logic Execution: Core tool functionality is executed with error handling

8. Post-execution Processing: Results are formatted and audit entries are created

9. Response Construction: JSON-RPC 2.0 response is built with result or error

10. Transmission: Response is transmitted via stdio transport to client

State Handling and Isolation

1. Session Isolation: Each session maintains independent state and permissions

2. Workspace Binding: Operations are bound to specific workspace directories

3. Plan Context: Authorization context is maintained throughout request lifecycle

4. Audit Correlation: All operations are correlated via session and request IDs

5. Stateless Design: Server does not maintain persistent state between requests

6. Immutable Audit: Audit log provides the only persistent state management

Permission Evaluation and Enforcement

1. Role-Based Access: Windsurf role allows mutations, Antigravity role is read-only

2. Plan Authorization: Operations must reference valid, approved plans

3. Capability Scoping: Tools have scoped permissions based on their function

4. Content Restrictions: Static analysis prevents unauthorized code patterns

5. Resource Limits: Filesystem access is limited to authorized directories

6. Audit Requirements: All operations must pass audit logging requirements

7. Failure Modes: Security violations result in immediate operation termination

Security and Permission Model

ATLAS-GATE-MCP implements a comprehensive, defense-in-depth security model designed for enterprise environments where security, compliance, and auditability are paramount.

Authentication Assumptions

ATLAS-GATE-MCP operates under a zero-trust security model with the following authentication assumptions:

Transport Security: Communication occurs over controlled stdio transport or authenticated HTTP channels. The protocol assumes the transport layer provides basic authentication and integrity protection.

Session Authentication: Sessions are established via begin_session with workspace binding and cryptographic session identifiers. Session state is maintained server-side with proper isolation.

Plan-Based Authentication: Operations are authenticated against approved plans stored in the governance repository. Plans serve as capability tokens that authorize specific operations within defined scopes.

Bootstrap Authentication: Initial system setup requires bootstrap secret authentication for creating the first governance plans. This secret is single-use and destroyed after initial configuration.

Authorization and Permission Boundaries

The authorization model implements multiple, overlapping permission boundaries:

Role-Based Authorization:

• Windsurf Role: Full execution capabilities including file writes, plan creation, and system modifications

• Antigravity Role: Read-only capabilities including file reads, plan inspection, and analysis operations

• Role Separation: Strict enforcement prevents privilege escalation between roles

Plan-Based Authorization:

• Plan Reference: All operations must reference an approved plan ID

• Scope Validation: Operations are validated against plan-defined scopes and constraints

• Hash Verification: Plan integrity is verified via cryptographic hashes

• Temporal Validity: Plans may include temporal constraints and expiration

Capability-Based Authorization:

• Tool Scoping: Each tool has defined capabilities and required permissions

• Parameter Validation: Tool parameters are validated against schemas and security policies

• Resource Access: Filesystem and resource access is limited to authorized paths

• Operation Constraints: Specific operations may have additional constraints (e.g., file size limits)

Access Control Mechanisms

MCP-Only Enforcement:

• Process sandbox prevents direct system access

• All operations must go through MCP tool interfaces

• Filesystem access is mediated through authorized tools only

• Network access is blocked by default with explicit allowances

Content Security:

• Static analysis prevents injection of malicious code patterns

• Stub detection prevents deployment of incomplete or placeholder code

• Policy enforcement blocks prohibited constructs and practices

• Content integrity verification ensures file consistency

Audit and Compliance:

• Comprehensive audit logging captures all operations with full context

• Cryptographic signatures ensure audit log integrity

• Tamper detection mechanisms prevent audit log manipulation

• Compliance reporting supports regulatory requirements

Data Exposure and Capability Escalation Prevention

Data Isolation:

• Session-based isolation prevents cross-session data leakage

• Workspace binding limits operations to authorized directories

• Path traversal protection prevents unauthorized file access

• Content filtering prevents sensitive data exposure in responses

Capability Escalation Prevention:

• Role separation prevents read-to-write privilege escalation

• Plan authorization prevents unauthorized capability acquisition

• Tool scoping limits operations to defined boundaries

• Static analysis prevents privilege escalation through code injection

Least Privilege Enforcement:

• Default-deny security posture with explicit authorization

• Minimal required permissions for each operation

• Time-limited authorization tokens where applicable

• Revocation capabilities for compromised sessions or plans

Design Principles

Zero Trust: Never trust, always verify. All operations require explicit authorization regardless of source.

Fail-Secure: Security violations result in operation termination rather than risky fallbacks.

Defense in Depth: Multiple, overlapping security controls ensure no single point of failure.

Audit by Design: All operations are auditable by design with comprehensive logging and integrity protection.

Least Privilege: Operations are granted minimal necessary permissions with scoped access.

Transparency: Security decisions are logged and auditable with clear reasoning and evidence.

MCP Capabilities in Atlas-Gate

ATLAS-GATE-MCP implements comprehensive MCP primitives with enterprise-grade security extensions.

Supported MCP Primitives

Tools: 17 specialized tools covering core operations:

• File Operations: read_file, write_file with comprehensive validation

• Plan Management: list_plans, lint_plan, bootstrap_tool for governance

• Audit Operations: read_audit_log, replay_execution, verify_workspace_integrity

• Attestation: generate_attestation_bundle, verify_attestation_bundle, export_attestation_bundle

• Session Management: begin_session, read_prompt for session initialization

Resources: Read-only access to system state and configuration:

• Plan Resources: Approved governance plans and their metadata

• Audit Resources: Historical audit logs and compliance data

• Configuration Resources: System configuration and security policies

• Documentation Resources: System documentation and operational guides

Prompts: Reusable prompt templates for common operations:

• Planning Prompts: Templates for creating and validating governance plans

• Analysis Prompts: Templates for security analysis and compliance checking

• Operational Prompts: Templates for common operational tasks

Security Extensions

Enhanced Validation: All inputs undergo comprehensive security validation beyond standard MCP schema validation:

• Static analysis for security patterns

• Content integrity verification

• Policy compliance checking

• Threat pattern detection

Audit Integration: All operations are integrated with the audit system:

• Pre-execution audit logging

• Post-execution result capture

• Cryptographic signature generation

• Tamper-evident storage

Authorization Extensions: Plan-based authorization extends standard MCP capabilities:

• Capability token management

• Scope-based access control

• Temporal authorization constraints

• Revocation and renewal mechanisms

Extensibility and Interoperability

Tool Registration: New tools can be registered with comprehensive security validation:

• Schema definition and validation

• Security policy integration

• Audit logging integration

• Authorization mapping

Protocol Compatibility: Full MCP protocol compliance ensures interoperability:

• Standard JSON-RPC 2.0 transport

• Compliant tool and resource definitions

• Standard error handling and response formats

• Capability discovery mechanisms

Integration Points: Well-defined interfaces for system integration:

• Authentication provider interfaces

• Authorization system hooks

• Audit log consumers

• Monitoring and alerting endpoints

Differentiation from Other MCP Servers

Enterprise Security Focus: Unlike development-focused MCP servers, ATLAS-GATE-MCP prioritizes security, compliance, and auditability over flexibility.

Governance Integration: Built-in plan-based governance system provides structured authorization lacking in standard MCP implementations.

Comprehensive Auditing: Immutable, cryptographically-signed audit trails exceed standard MCP logging capabilities.

Process Isolation: MCP-only sandbox enforcement provides stronger isolation than typical MCP server implementations.

Static Analysis Integration: Real-time code analysis and security scanning are unique capabilities not found in standard MCP servers.

Usage Overview

Primary Use Cases

Enterprise AI Development: Secure AI-assisted development in regulated environments where code quality, security, and compliance are mandatory.

Compliance-Driven Development: Development workflows requiring comprehensive audit trails, change approval, and regulatory compliance documentation.

High-Security Environments: Development of security-critical systems where code injection, privilege escalation, and data leakage must be prevented.

Multi-Tenant Development: Shared development environments where strict isolation and auditability between teams and projects are required.

Governed AI Operations: Organizations requiring structured approval processes for AI-assisted operations with clear accountability and traceability.

Typical Deployment Scenarios

Development Gateway: ATLAS-GATE-MCP deployed as a gateway between AI development tools and code repositories, enforcing governance policies and maintaining audit trails.

Compliance Enforcement: Integration with compliance systems to ensure all AI-assisted development meets regulatory requirements and organizational policies.

Security Monitoring: Integration with security operations centers to monitor AI agent activities and detect potential security violations.

Audit and Forensics: Providing comprehensive audit trails for incident response, forensic analysis, and compliance reporting.

Target Users

Platform Engineers: Responsible for maintaining secure development infrastructure and ensuring compliance with organizational policies.

Security Engineers: Focused on preventing security vulnerabilities, maintaining audit trails, and ensuring secure AI operations.

Compliance Officers: Ensuring development activities meet regulatory requirements and organizational standards.

Development Teams: Using AI assistance while maintaining security, quality, and compliance standards.

DevOps Engineers: Integrating AI-assisted development into CI/CD pipelines with proper governance and monitoring.

When to Use Atlas-Gate

Use Atlas-Gate when:

• Enterprise-grade security is non-negotiable

• Comprehensive audit trails are required

• Regulatory compliance must be maintained

• Multiple teams share development resources

• AI assistance is needed but must be tightly controlled

• Code quality and security standards must be enforced

• Change approval processes are required

Consider alternatives when:

• Development speed is the primary concern over security

• Simple, single-developer projects without compliance requirements

• Experimental development where flexibility is more important than governance

• Organizations without established security and compliance frameworks

How Atlas-Gate Compares to Alternatives

Traditional REST/GraphQL APIs

Security Model:

• REST/GraphQL: Typically rely on network-level security (TLS, API keys) with application-level authorization

• Atlas-Gate: Multi-layer security with process isolation, content validation, and comprehensive audit trails

State Management:

• REST/GraphQL: Often stateless or require explicit session management

• Atlas-Gate: Built-in session management with cryptographic isolation and audit correlation

Schema Validation:

• REST/GraphQL: Schema validation varies by implementation; often optional

• Atlas-Gate: Mandatory schema validation with Zod and additional security scanning

AI Integration:

• REST/GraphQL: Not designed for AI model interaction patterns

• Atlas-Gate: Specifically designed for AI model interaction with appropriate error handling and response formats

Compliance:

• REST/GraphQL: Audit logging must be implemented manually

• Atlas-Gate: Comprehensive, immutable audit trails built into the protocol

Plugin-based LLM Systems

Security Boundaries:

• Plugin Systems: Often rely on plugin developer security practices; vulnerabilities can affect entire system

• Atlas-Gate: Process-level isolation prevents plugin vulnerabilities from affecting system security

Update Mechanisms:

• Plugin Systems: Dynamic loading can introduce security risks and version conflicts

• Atlas-Gate: Static tool registration with comprehensive validation prevents runtime security issues

Authorization:

• Plugin Systems: Authorization varies by plugin implementation

• Atlas-Gate: Consistent, plan-based authorization across all capabilities

Audit Trail:

• Plugin Systems: Audit logging is inconsistent across plugins

• Atlas-Gate: Uniform, comprehensive audit trail for all operations

Agent Frameworks with Embedded Tools

Tool Isolation:

• Agent Frameworks: Tools often run in same process as agent, increasing attack surface

• Atlas-Gate: Process isolation and sandbox enforcement provide stronger security boundaries

Governance:

• Agent Frameworks: Governance varies by implementation; often lacks enterprise-grade controls

• Atlas-Gate: Built-in governance system with plan-based authorization and compliance features

Scalability:

• Agent Frameworks: Often designed for single-agent scenarios

• Atlas-Gate: Designed for multi-agent, multi-session enterprise environments

Compliance:

• Agent Frameworks: Compliance features vary; often inadequate for regulated environments

• Atlas-Gate: Enterprise-grade compliance features with comprehensive audit trails

Other MCP Servers

Security Focus:

• Other MCP Servers: Often prioritize flexibility and ease of use over security

• Atlas-Gate: Security-first design with comprehensive enforcement mechanisms

Governance Integration:

• Other MCP Servers: Limited or no governance capabilities

• Atlas-Gate: Built-in plan-based governance system with approval workflows

Audit Capabilities:

• Other MCP Servers: Basic logging capabilities

• Atlas-Gate: Comprehensive, cryptographically-signed audit trails with tamper detection

Enterprise Features:

• Other MCP Servers: Often designed for development or experimental use

• Atlas-Gate: Designed specifically for enterprise production environments

Design Decisions and Tradeoffs

Key Architectural Choices

MCP-Only Sandbox Enforcement:

• Decision: Restrict all operations to MCP protocol interfaces

• Rationale: Prevents direct system access and ensures all operations are auditable

• Tradeoff: Reduced flexibility for significantly improved security posture

Plan-Based Authorization:

• Decision: Require all operations to reference approved governance plans

• Rationale: Provides structured authorization and change approval processes

• Tradeoff: Additional complexity for improved governance and compliance

Static Analysis Integration:

• Decision: Scan all content for security patterns before execution

• Rationale: Prevents injection of malicious code and policy violations

• Tradeoff: Performance overhead for enhanced security assurance

Immutable Audit Trails:

• Decision: Maintain cryptographically-signed, tamper-evident audit logs

• Rationale: Provides non-repudiation and compliance support

• Tradeoff: Storage overhead and complexity for audit integrity

Constraints and Limitations

Performance Considerations:

• Static analysis and content validation add latency to operations

• Comprehensive audit logging generates significant data volume

• Process isolation introduces communication overhead

Scalability Limitations:

• Single-server architecture limits horizontal scaling

• Session state management constrains concurrent operations

• File-based audit storage has performance implications

Operational Complexity:

• Plan governance requires administrative overhead

• Security configuration requires specialized knowledge

• Audit management and retention policies add operational burden

Flexibility Constraints:

• Strict security policies limit certain development patterns

• Plan-based authorization can slow rapid iteration

• MCP-only restriction prevents direct system integration

Non-Goals

General-Purpose Server: ATLAS-GATE-MCP is not designed to replace general-purpose application servers or API gateways.

Development Speed Optimization: The system prioritizes security and compliance over development velocity.

Multi-Protocol Support: Focus on MCP protocol rather than supporting multiple integration protocols.

Real-time Performance: Not optimized for high-frequency, low-latency operations typical of trading systems or real-time analytics.

Dynamic Configuration: Runtime reconfiguration is limited to maintain security guarantees.

Future Directions / Roadmap

Plausible Future Enhancements

Distributed Architecture: Multi-server deployment with load balancing and horizontal scaling capabilities.

Database Integration: Support for external databases for audit storage and session management.

Advanced Authentication: Integration with enterprise authentication systems (LDAP, SAML, OAuth2).

Policy Engine: Rule-based policy engine for more sophisticated authorization decisions.

Performance Optimization: Caching mechanisms and optimized static analysis for improved performance.

Monitoring Integration: Enhanced monitoring and alerting integration with enterprise observability platforms.

Compliance Automation: Automated compliance reporting and regulatory requirement mapping.

Areas of Exploration

Machine Learning Integration: ML-based anomaly detection for security threat identification.

Advanced Threat Protection: Integration with threat intelligence feeds and automated response capabilities.

Cross-Platform Support: Support for additional operating systems and deployment environments.

Protocol Extensions: Extensions to MCP protocol for enhanced security and governance features.

Community Ecosystem: Development of additional tools and integrations by the community.

Enterprise Features: Additional enterprise-specific features like role-based administration and advanced reporting.

Long-Term Direction

Standardization Leadership: Active participation in MCP protocol standardization and security best practices development.

Ecosystem Development: Growth of a partner ecosystem for integrations and complementary tools.

Compliance Expansion: Support for additional regulatory frameworks and compliance requirements.

Security Innovation: Continued innovation in AI security and governance mechanisms.

Performance Evolution: Ongoing performance optimization while maintaining security guarantees.

Glossary

MCP (Model Context Protocol): Standardized protocol for AI model interaction with external systems, tools, and data sources.

Atlas-Gate: Enterprise MCP server implementing security governance, sandbox enforcement, and comprehensive audit trails.

Windsurf Role: Atlas-Gate operational mode with execution and mutation capabilities, including file writes and system modifications.

Antigravity Role: Atlas-Gate operational mode with read-only capabilities for analysis and planning operations.

Plan: Governance document that defines authorization scopes, constraints, and approval requirements for operations.

Tool: Executable function exposed through MCP interface with defined schemas and security policies.

Resource: Read-only data source accessible through MCP interface with proper authorization.

Session: Bounded interaction context between AI model and Atlas-Gate server with associated state and permissions.

Audit Trail: Comprehensive, immutable log of all operations with cryptographic integrity protection.

Sandbox: Process-level isolation mechanism that restricts operations to MCP protocol interfaces only.

Static Analysis: Automated code scanning for security patterns, policy violations, and prohibited constructs.

Stub Detection: Identification of incomplete, placeholder, or non-production code patterns.

Authorization: Process of verifying that operations are permitted based on roles, plans, and security policies.

Governance: System of rules, policies, and procedures for controlling and monitoring AI agent operations.

Compliance: Adherence to regulatory requirements, organizational policies, and industry standards.

Zero Trust: Security model that assumes no implicit trust and requires verification for all operations.

Least Privilege: Security principle of granting minimal necessary permissions for required operations.

Non-repudiation: Assurance that operations cannot be denied by their performers, typically through audit trails.

Tamper-evident: Property that unauthorized modifications to data or systems can be detected.

Capability Token: Authorization credential that grants specific permissions within defined scopes.

Content Integrity: Assurance that content has not been altered in unauthorized ways.

Policy Enforcement: Automated application of security policies and governance rules.

Transport Layer: Communication mechanism between AI models and MCP servers, typically JSON-RPC 2.0.

Schema Validation: Verification that input data conforms to defined structure and type requirements.

Session Isolation: Separation of state and permissions between different concurrent sessions.

Workspace Binding: Association of operations with specific workspace directories for security and organization.

Cryptographic Signature: Digital signature used to verify authenticity and integrity of audit entries.

Threat Pattern: Recognized pattern of malicious or unauthorized activity that security systems should detect.

Enterprise Grade: Security and reliability standards suitable for large organizational deployment.

Production Ready: System state appropriate for live operational use with proper security, monitoring, and support.