How ContextForge Fits the Criteria for Selecting an Enterprise MCP Gateway¶

A practical framework for evaluating MCP gateways, and how ContextForge addresses each criterion.

Why an MCP Gateway?¶

Organizations deploying AI agents face fragmented tool ecosystems, inconsistent security controls, and no centralized governance across agent interactions. An MCP gateway provides the unified control plane: federating tools, enforcing policy, and delivering visibility across your AI infrastructure.

This framework outlines what to evaluate and why each criterion matters.

The MCP Gateway Landscape¶

The MCP gateway market has matured rapidly. Options range from managed SaaS platforms (Composio, MintMCP, Apigee MCP Gateway) to cloud-native solutions (Azure MCP Gateway, Docker MCP Gateway) to self-hosted open source (ContextForge, Lasso Security, Bifrost).

flowchart TB
    subgraph "MCP Gateway Options"
        direction TB
        subgraph managed["Managed SaaS"]
            composio["Composio"]
            mintmcp["MintMCP"]
            apigee["Apigee MCP Gateway"]
        end
        subgraph cloud["Cloud-Native"]
            azure["Azure MCP Gateway"]
            docker["Docker MCP Gateway"]
        end
        subgraph selfhosted["Self-Hosted Open Source"]
            contextforge["ContextForge"]
            lasso["Lasso Security"]
            bifrost["Bifrost"]
        end
    end

    managed --> |"Lower ops burden<br>Vendor dependency"| decision{Your Choice}
    cloud --> |"Ecosystem lock-in<br>Tight integration"| decision
    selfhosted --> |"Full control<br>Higher ops burden"| decision

Key market distinctions:

• Managed platforms offer lower operational burden but introduce vendor dependency
• Cloud-native solutions integrate tightly with specific ecosystems (Azure, Docker)
• Self-hosted open source provides maximum control and customization

This framework applies regardless of which path you choose. ContextForge is used as a reference implementation to illustrate what "good" looks like for each criterion.

About ContextForge¶

Design principles:

The criteria in this framework reflect what we've learned matters most when deploying MCP infrastructure at enterprise scale.

Risk & Governance Models¶

Tiered Threat Model (CoSAI Framework)¶

The CoSAI OASIS framework organizes MCP threats into three tiers:

Agentic System Risk Categories¶

MCP gateways must address risk vectors across three domains: identity and access, supply chain integrity, and operational governance. Each category demands specific mitigations that traditional API gateways do not provide.

Identity & Access Risks

Supply Chain Risks

Operational Risks

The Triple Gate Security Pattern¶

Defense-in-depth architecture requiring controls at three layers:

flowchart LR
    subgraph gate1["Gate 1: AI Layer"]
        direction TB
        client["AI Client"]
        intent["Intent Classification"]
        filter["Prompt Filtering"]
    end

    subgraph gate2["Gate 2: MCP Layer"]
        direction TB
        gateway["MCP Gateway"]
        authz["Tool Authorization"]
        validate["Argument Validation"]
    end

    subgraph gate3["Gate 3: API Layer"]
        direction TB
        backend["Backend APIs"]
        rate["Rate Limiting"]
        mtls["mTLS / IP Allow-list"]
    end

    client --> intent --> filter
    filter --> gateway
    gateway --> authz --> validate
    validate --> backend
    backend --> rate --> mtls

    style gate1 fill:#e3f2fd,stroke:#1976d2
    style gate2 fill:#fff3e0,stroke:#f57c00
    style gate3 fill:#e8f5e9,stroke:#388e3c

1. Architecture & Protocol Support¶

ContextForge delivers:

• Full gateway/registry/proxy with tool hosting capabilities
• All major transports: HTTP, JSON-RPC, WebSocket, SSE, stdio, streamable HTTP
• Automatic REST-to-MCP virtualization with JSON Schema extraction
• gRPC-to-MCP translation via server reflection
• Session-aware routing with context propagation across multi-step workflows

flowchart LR
    subgraph clients["AI Clients"]
        claude["Claude"]
        openai["OpenAI"]
        custom["Custom Agents"]
    end

    subgraph transports["Transport Layer"]
        sse["SSE"]
        ws["WebSocket"]
        http["Streamable HTTP"]
    end

    gateway["ContextForge<br>Gateway"]

    subgraph backends["Backend Services"]
        mcp["Native MCP"]
        rest["REST APIs"]
        grpc["gRPC Services"]
        stdio["stdio Servers"]
    end

    clients --> transports --> gateway
    gateway --> backends

    style gateway fill:#1976d2,stroke:#0d47a1,color:#fff

2. Federation & Discovery¶

ContextForge delivers:

• Federation across multiple MCP and REST services into a single registry
• Health monitoring with automatic endpoint failover
• Redis-backed multi-cluster federation and caching
• Unified discovery API for tools, resources, and prompts
• Auto-discovery via mDNS for local deployments

3. Virtual Servers & Tool Composition¶

ContextForge delivers:

• Virtual MCP servers composing tools from any registered backend
• Per-server custom authentication flows
• Automatic schema generation from composed tools
• Tag-based organization and filtering

4. Identity & Access Control¶

ContextForge delivers:

• SSO integration: GitHub, Google, Microsoft Entra ID, Okta, Keycloak, generic OIDC
• OAuth 2.0 with Dynamic Client Registration (DCR) and PKCE
• On-Behalf-Of (OBO) token exchange support
• RFC 8707 OAuth Resource Indicators for A2A communication
• JWT authentication supporting HS256 and RS256
• Team-scoped RBAC with configurable role hierarchies
• API key management with scoped permissions
• Zero-trust secret injection: agents receive scoped tokens, never raw API keys
• Just-in-time (JIT) access and temporary privilege elevation (roadmap)

5. Multi-Tenancy & Isolation¶

ContextForge delivers:

• Full multi-tenant architecture with team scoping
• Isolated catalogs per team
• Tenant-scoped API keys and secrets
• Per-team rate limits and quota enforcement
• Resource visibility controls

6. AI Guardrails & Content Policy¶

ContextForge delivers:

• PII detection with automatic redaction (SSN, credit cards, emails, medical data)
• Content deny lists and regex-based filters
• LlamaGuard and Granite Guardian integration
• OPA and Cedar policy engine integration
• Configurable request/response inspection hooks
• Plugin-based guardrail system for custom security logic
• Secrets detection plugin (AWS keys, API keys, tokens)
• URL reputation plugin (malicious URL detection, VirusTotal integration)

7. Security Logging & Audit¶

ContextForge delivers:

• Structured audit logging with correlation IDs
• Full request/response logging with configurable redaction
• Identity attribution across all operations
• Export-ready for SIEM integration
• Retention policy support
• Compliance report generator for FedRAMP/HIPAA/SOC2 (roadmap)

8. Reliability & Resiliency¶

ContextForge delivers:

• Configurable retry policies per gateway/backend
• Per-tool timeout settings
• Built-in rate limiting with burst control
• Request throttling per user/team/tool
• Connection pooling and backpressure handling
• Production-tested at scale (powers IBM Consulting Advantage serving 160,000+ users)

Performance architecture:

9. Observability¶

ContextForge delivers:

• Native OpenTelemetry (OTLP) with W3C Trace Context propagation
• Backend support: Phoenix (LLM-focused), Jaeger, Zipkin, Arize, DataDog
• LLM metrics: token usage, prompt latency, tool error rates
• Prometheus metrics export with Grafana dashboard templates
• Structured logging with correlation IDs
• Real-time log viewer in Admin UI
• Health and readiness endpoints

flowchart LR
    subgraph cf["ContextForge"]
        otel["OpenTelemetry<br>Instrumentation"]
        prom["Prometheus<br>Metrics"]
        logs["Structured<br>Logs"]
    end

    subgraph backends["Observability Backends"]
        jaeger["Jaeger"]
        phoenix["Phoenix"]
        grafana["Grafana"]
        datadog["DataDog"]
    end

    otel --> jaeger
    otel --> phoenix
    otel --> datadog
    prom --> grafana
    logs --> grafana

    style cf fill:#fff3e0,stroke:#f57c00

10. Extensibility¶

ContextForge delivers:

• Production-ready plugin framework
• Extensible hooks: caching, compliance, guardrails, middleware
• Hot-reload for plugin updates without restart
• Full REST API with OpenAPI documentation
• CLI tooling for automation
• Webhook plugin for event delivery with retry logic and HMAC signatures
• Tool versioning with history and rollback support
• Configuration versioning and rollback

11. Semantic Discovery & AI-Assisted Operations¶

12. Agent-to-Agent (A2A) Integration¶

ContextForge delivers:

• A2A protocol support for external AI agents
• Integration with OpenAI, Anthropic, and custom agents
• Agent registration and discovery
• Multi-agent workflow orchestration

13. Deployment Flexibility¶

ContextForge delivers:

14. Developer Experience¶

ContextForge delivers:

• OpenAPI-documented REST API with interactive Swagger UI
• Built-in Admin UI (HTMX + Alpine.js) for visual management
• One-command local startup (uvx --from mcp-contextforge-gateway mcpgateway)
• Docker Compose configurations for local development with Redis, PostgreSQL, and observability stack
• CLI tools for token generation, server management, and stdio-to-HTTP translation
• MCP Inspector compatibility for interactive testing and debugging
• Desktop application (React + Electron) for local gateway management
• TypeScript SDK auto-generation via @hey-api/openapi-ts
• Comprehensive documentation site with tutorials and API reference
• Internationalization framework (i18n - roadmap)

15. Privacy & Telemetry¶

16. MCP Server Security Posture & Supply Chain¶

ContextForge delivers (current + roadmap):

• Container vulnerability scanning (Trivy/Grype integration)
• SBOM generation (CycloneDX/SPDX format)
• Source code scanning (Semgrep/Bandit integration)
• Supply chain attack detection (typosquatting, dependency confusion)
• Curated secure MCP server catalog with trust tiers
• MCP-specific security rules (custom Semgrep/CodeQL patterns)
• Centralized inventory of deployed servers
• Automated shadow deployment detection
• Version tracking with deprecation policies

17. Project Health & Sustainability¶

ContextForge project health:

18. Licensing & Commercial Model¶

ContextForge licensing:

Commercial support options:

Managed vs. Self-Hosted Trade-offs¶

Evaluation Checklist¶

Use this sequence when evaluating gateways:

flowchart TD
    A["1. Architecture Fit"] --> B["2. Security Baseline"]
    B --> C["3. Governance Controls"]
    C --> D["4. Operational Readiness"]
    D --> E["5. Scale Requirements"]
    E --> F["6. Extensibility"]
    F --> G["7. Project Health"]
    G --> H["8. Commercial Model"]

    A -.- a1["Transport & backend support"]
    B -.- b1["IdP, RBAC, isolation, audit"]
    C -.- c1["Policy, catalog, change control"]
    D -.- d1["Observability, monitoring, runbooks"]
    E -.- e1["Rate limits, caching, multi-cluster"]
    F -.- f1["Plugins, API, integrations"]
    G -.- g1["Release cadence, contributors"]
    H -.- h1["License, support, viability"]

    style A fill:#e3f2fd,stroke:#1976d2
    style B fill:#ffebee,stroke:#c62828
    style C fill:#fff3e0,stroke:#f57c00
    style D fill:#e8f5e9,stroke:#388e3c
    style E fill:#f3e5f5,stroke:#7b1fa2
    style F fill:#e0f7fa,stroke:#00838f
    style G fill:#fce4ec,stroke:#c2185b
    style H fill:#ede7f6,stroke:#512da8

1. Architecture fit: Does it support your transports and backend types?
2. Security baseline: IdP integration, RBAC, tenant isolation, audit logging
3. Governance controls: Policy enforcement, catalog management, change control
4. Operational readiness: Observability stack, health monitoring, runbooks
5. Scale requirements: Rate limits, caching, quotas, multi-cluster support
6. Extensibility: Plugin support, API completeness, integration options
7. Project health: Release cadence, contributor base, backing organization
8. Commercial model: License terms, support options, long-term viability

Additional Resources¶