MCP Registry Readiness Engineering: Enterprise Security & Governance

Enterprise AI infrastructure is no longer defined solely by which tools an AI agent can discover. It is increasingly defined by which tools an organization can trust, authorize, monitor, and govern.

The Model Context Protocol (MCP) is establishing a standardized interface between AI applications and external capabilities. However, the rapid expansion of MCP servers, tool catalogs, package repositories, and autonomous agent integrations introduces a critical engineering challenge: discovery does not automatically establish trust.

A server can be discoverable without being secure. It can expose valid schemas without enforcing authorization. It can pass a static security scan while retaining dangerous runtime behavior. And it can be successfully published to a registry without meeting an enterprise organization's operational, compliance, or regulatory requirements.

This creates a missing architectural layer between MCP development and production adoption: Registry Readiness Engineering.

At SEOSiri, we define this process through the MCP Registry Pre-Initiative Framework — a proposed engineering and governance model that evaluates MCP servers before directory ingestion, enterprise broker integration, or production deployment.

The objective is to establish verifiable evidence across security, protocol conformance, semantic reliability, token economics, identity, and runtime governance before a server becomes part of an organization's mission-critical AI infrastructure.

SEOSIRI // MCP REGISTRY READINESS ARCHITECTURE

PRE-INGESTION GOVERNANCE LIFECYCLE (NIST SP 800-218 & SLSA ALIGNED)

[ SOURCE REPOSITORY ]
 Tool Definitions | API Connectors | Dependencies | Build Manifests
             |
             v
[ GATE 01: SECURITY & SUPPLY CHAIN ]
 SAST (AST Analysis) | Secret Detection | SLSA Provenance | SBOM (CycloneDX/SPDX)
             |
             v
[ GATE 02: PROTOCOL & SCHEMA CONFORMANCE ]
 MCP Lifecycle | JSON Schema 2020-12 | JSON-RPC 2.0 Strict Validation
             |
             v
[ GATE 03: SEMANTIC & TOKEN ENGINEERING ]
 Tool Descriptions | Output Contracts | Context Budgets | Deterministic Truncation
             |
             v
[ GATE 04: IDENTITY & RUNTIME ISOLATION ]
 OAuth 2.1 / DPoP | Scoped Authorization | Streamable HTTP | MicroVM/Wasm Sandboxing
             |
             v
[ GATE 05: OPERATIONAL TRUST GOVERNANCE ]
 Publisher Provenance | Immutable Audit Logs | OpenTelemetry Telemetry | Continuous Reassessment
             |
             v
[ REGISTRY READINESS DECISION ]
 Verifiable Evidence Record | Risk Classification | Enterprise Approval Gate
             |
             v
[ PUBLIC / PRIVATE REGISTRY INGESTION ]
 (e.g., Enterprise MCP Broker, Curated Directory, VPC Catalog)
             |
             v
[ CONTINUOUS POST-PUBLICATION ASSURANCE ]
  

FRAMEWORK OWNER: SEOSIRI | ARCHITECTURAL SPECIFICATION

SEOSiri MCP Registry Readiness Framework — a five-gate governance architecture for pre-ingestion verification and continuous operational assurance.

Inside this architecture

1. The MCP discovery and trust problem
2. Gate 1: Security and supply-chain assurance
3. Gate 2: Protocol and schema conformance
4. Gate 3: Semantic reliability and token economics
5. Gate 4: Identity, transport, and runtime isolation
6. Gate 5: Operational governance and provenance
7. Enterprise MCP security toolchain
8. Enterprise registry-readiness matrix
9. Continuous verification lifecycle
10. Implementation and acceptance criteria
11. The broader architectural implication
12. Technical FAQ

1. The MCP Discovery Problem: Why Registry Ingestion Needs a Trust Layer

The Model Context Protocol provides a standardized communication framework through which AI applications can discover and interact with external tools, resources, and prompt templates.

As the ecosystem expands, developers increasingly rely on public registries, community directories, package repositories, and private enterprise catalogs to distribute MCP implementations.

Our comparative research, MCP Server Registries Guide: Glama, mcp.so, Smithery and Trending MCP Servers, examines this discovery landscape.

However, registry discoverability introduces a critical distinction that enterprise engineering teams must recognize:

Discovery is not verification. Verification is not authorization. Authorization is not continuous assurance.

These are separate engineering responsibilities and should never be treated as interchangeable trust signals.

Consider an MCP server that connects an autonomous AI agent to an enterprise cloud database. Its repository may be publicly accessible, its tool definitions syntactically valid, and its package cleanly installable. None of these properties demonstrates that the server enforces appropriate attribute-based access controls, protects secrets in memory, bounds operations, or maintains tamper-evident audit trails.

Five major enterprise risk categories emerge:

• Execution risk: Unsafe runtime process invocation, excessive local permissions, or uncontained access to host resources.
• Supply-chain risk: Compromised transitive dependencies, unverified publisher namespaces, and unexpected binary modifications.
• Protocol risk: Non-conforming message handling, schema dialect drift, and inconsistent capability negotiation.
• Agent reliability risk (OWASP LLM06): Ambiguous tool descriptions that trigger catastrophic tool-selection hallucinations or uncontrolled context exhaustion.
• Governance risk: Missing cryptographic provenance, insufficient audit trails, and unmonitored production drift.

The MCP Registry Pre-Initiative Framework addresses these risks through an evidence-driven gate system before ingestion.

2. Gate 1: Static Security Auditing and Software Supply-Chain Assurance

Security verification begins at the source repository level, before an MCP server is packaged, containerized, or published.

Unlike traditional application integrations invoked through explicit deterministic code, MCP tools are selected dynamically by autonomous AI models. Consequently, security reviews must evaluate both the server's code and the threat model of indirect agent invocation.

2.1 Static Application Security Testing (SAST)

Static Application Security Testing examines source code for insecure programming patterns and architectural weaknesses.

For MCP projects, static analysis must systematically evaluate:

• Unsafe process execution (e.g., shell injection, unvalidated exec/spawn calls).
• Unrestricted filesystem access and path-traversal vulnerabilities (../ injection).
• Missing authorization boundaries around state-modifying operations.
• Insecure deserialization and unsafe payload hydration.
• Improper error handling that leaks stack traces or environment variables into tool outputs.
• Over-privileged capabilities granted to host runners.

Abstract Syntax Tree (AST) analysis identifies structural anti-patterns, but AST findings must be combined with dependency graph verification, semantic review, and runtime sandboxing. Scanner output represents evidence for investigation, not absolute proof of exploitability or immunity.

2.2 Credential and Secret Management

Credential exposure is particularly catastrophic when MCP servers connect to enterprise databases, SaaS endpoints, or cloud control planes.

Registry readiness requires proof that:

• Credentials, API tokens, and private keys are never hardcoded in source code, configuration manifests, or deployment examples.
• Secrets are never included in tool execution responses or conversation-visible logs returned to the model context.
• Authentication material is injected securely via environment variables or a hardware-backed Key Management Service (KMS).
• Token rotation, scoped time-to-live (TTL), and revocation mechanisms are supported.
• Access credentials adhere to the principle of least privilege.

2.3 Dependency and Supply-Chain Integrity (SLSA & SBOM)

An MCP server inherits the cumulative risk of its dependency tree.

Supply-chain verification must align with established standards like NIST SP 800-218 (SSDF) and SLSA v1.0 (Supply-chain Levels for Software Artifacts):

• Software Bill of Materials (SBOM): Generation of standard CycloneDX or SPDX manifests tracking all direct and transitive dependencies.
• Software Composition Analysis (SCA): Automated cross-referencing of dependencies against maintained vulnerability feeds (e.g., the Common Vulnerabilities and Exposures (CVE) system and GitHub Advisory Database).
• Lockfile Determinism: Cryptographically pinned dependency versions to prevent build-time supply-chain substitution attacks.
• Package Provenance: Verifiable build attestations establishing that the published artifact matches the source commit without tampering.

2.4 Security Evidence and Risk Classification

Instead of treating a single scan pass as a permanent clearance, the pre-initiative framework records a structured Attestation Baseline. Every evaluation preserves the Git commit SHA, scanner versions, full finding inventories, severity classifications, and remediation sign-offs.

3. Gate 2: MCP Protocol Conformance and Schema Integrity

An enterprise MCP server must strictly adhere to the transport and messaging specifications that allow heterogeneous AI clients to negotiate, invoke, and interpret its tools safely.

3.1 JSON-RPC 2.0 Message and Lifecycle Validation

MCP standardizes message interchange using JSON-RPC 2.0. Conformance testing validates:

• Strict message envelope formatting (jsonrpc: "2.0", id correlation, correct method and params).
• Deterministic lifecycle initialization: initialize handshake, protocol version negotiation, and capability advertisement.
• Standardized error responses adhering to JSON-RPC error codes (e.g., -32600 Invalid Request, -32601 Method not found, -32602 Invalid params) and application-level MCP error boundaries.
• Proper handling of notifications without expecting client response synchronization.

3.2 JSON Schema 2020-12 Dialect Conformance

A critical source of protocol friction across MCP registries involves JSON Schema dialect declarations.

The modern MCP specification establishes JSON Schema 2020-12 as the standard dialect when no alternative is explicitly declared. While older implementations may rely on Draft-07, enterprise readiness requires dialect-aware validation:

• Explicit declaration of parameter types (e.g., string, number, boolean, object).
• Strict boundary definitions (minimum, maximum, minLength, maxLength).
• Explicit enum restrictions for closed parameter sets.
• Defensive handling of additionalProperties: false to prevent prompt-injection parameter pollution.
• Validation parity between the declared schema contract and the underlying handler arguments.

3.3 Output Schema and Structured Data Contracts

Input validation is only half of the contract. Output schemas ensure that the data returned to the AI client conforms to a predictable, machine-readable structure. This predictability is critical when agent workflows pipe tool outputs into subsequent autonomous actions.

3.4 Semantic Tool Contract Engineering (Mitigating OWASP LLM06)

Language models select tools based on natural-language descriptions. A syntactically valid tool with an ambiguous description invites OWASP LLM06 (Excessive Agency) failures. Every tool contract must clearly document:

• Its precise functional scope and boundary conditions.
• Scenarios where the tool must not be invoked.
• Explicit documentation of required vs. optional parameters.
• Explicit declarations of whether the tool produces external side effects (e.g., writes, mutations, payments, deletions).
• Whether human confirmation (human-in-the-loop) is required prior to execution.

For deeper architectural insights into protocol-level standards, see our analysis on MCP Protocol Engineers vs. MCP Tooling Developers.

4. Gate 3: Semantic Reliability, Context Engineering, and Token Economics

In production enterprise deployments, an MCP server that returns unbounded data creates severe operational failures: excessive token consumption, inflated inference costs, degraded reasoning performance, and context-window exhaustion.

4.1 Context-Aware Output Design

Tool handlers must prioritize information density over raw verbosity. A database query tool should return concise summaries and targeted fields rather than dumping multi-megabyte relational tables into the model context.

Readiness verification reviews:

• Elimination of redundant payload headers and debugging traces.
• Field filtering allowing the caller to request specific attributes.
• Deterministic response ceilings preventing context saturation.
• Graceful summarization of large operational datasets.

4.2 Structured Contracts vs. Markdown Optimization

While Markdown provides efficient, human-readable representations for summary reports, structured JSON remains essential for programmatic chaining. The response format must align with the tool's declared schema and the downstream agent's consumption pattern.

4.3 Deterministic Pagination and Context Budgets

Unbounded array returns are prohibited in enterprise-grade MCP servers. All listing operations must implement deterministic pagination:

• Enforced default and maximum page limits.
• Opaque continuation cursors.
• Clear payload metadata indicating total_records, has_more, and truncation warnings.

4.4 Empirical Token Economics Benchmarking

Token optimization must be verified through empirical measurement across standardized test workloads:

• Mean and P95 token consumption per tool execution.
• Context budget impact under multi-turn autonomous loops.
• Mean round-trip execution latency.
• Failure and retry frequency under load.

5. Gate 4: Identity, Transport Security, and Runtime Isolation

Verifying a source repository does not secure its runtime environment. Runtime governance establishes strong boundaries around who can execute a server and what host resources that server can reach.

5.1 Transport Architecture: Streamable HTTP vs. stdio

The Model Context Protocol defines two primary transport patterns:

• stdio: Standard input/output transport, designed for local process execution managed directly by the host client (e.g., Claude Desktop, local developer environments).
• Streamable HTTP: The modern standard transport for remote, cloud-hosted MCP servers, supporting bidirectional HTTP communication with integrated streaming semantics.

The legacy HTTP+SSE standalone pattern is retained solely for backward compatibility. New production deployments should leverage Streamable HTTP with appropriate TLS termination.

Reference: Official MCP Transport Specification.

5.2 Identity, Scoped Authorization, and DPoP

Authentication verifies caller identity; authorization constrains caller capability. Enterprise deployments must implement:

• OAuth 2.1 & OIDC: Standardized identity token exchange for remote endpoints.
• Cryptographic Proof-of-Possession (RFC 9449 DPoP): Binding tokens to caller keypairs to eliminate token replay attacks.
• Granular Scope Enforcement: Tool-level authorization ensuring a client authenticated to read data cannot execute mutation tools.
• Tenant Isolation: Strict partition boundaries in multi-tenant SaaS environments.

5.3 Network Protection and Origin Defense

Remote Streamable HTTP endpoints must enforce strict Origin header validation to protect against cross-site DNS-rebinding attacks. Public edge listeners must operate behind TLS 1.3 reverse proxies with automated rate-limiting.

5.4 Runtime Sandboxing and Least Privilege

If an MCP tool is compromised or instructed to perform dangerous operations, the runtime sandbox represents the final barrier. Controls include:

• Containerized microVM (e.g., Firecracker, gVisor) or WebAssembly (Wasm) execution boundaries.
• Read-only host filesystem mounts.
• Restricted egress network security groups limiting communication exclusively to declared API hosts.
• Memory, CPU, and execution timeout quotas terminating runaway processes.

6. Gate 5: Operational Governance, Provenance, and Continuous Assurance

A static approval snapshot becomes obsolete the moment a developer pushes a new commit or an upstream dependency discloses a zero-day vulnerability. Enterprise readiness is a continuous lifecycle.

6.1 Publisher Provenance and Namespace Verification

Enterprise consumers require cryptographically verifiable proof connecting the distributed package to its author:

• Verified publisher namespaces in registry catalogs.
• Cryptographically signed releases (e.g., Sigstore / Cosign).
• Verification linking the published binary directly to its source Git commit SHA.

Consult the Official MCP Registry Documentation for emerging standards in publisher identity verification.

6.2 Change Management and Schema Versioning

Any modification to an MCP server's schemas, capabilities, or permissions constitutes a breaking change. Versioning must strictly follow Semantic Versioning (SemVer 2.0.0), triggering automated re-assessment upon any minor or major bump.

6.3 Observability and Telemetry (OpenTelemetry Standard)

Enterprise operational governance requires complete observability into autonomous tool usage without capturing sensitive customer payloads. Implementing OpenTelemetry (OTel) conventions enables:

• Distributed trace spans correlating agent thoughts to tool invocations.
• Structured audit logs tracking caller ID, tool name, execution latency, and authorization decisions.
• Alerting on anomalous tool invocation spikes or elevated error rates.

6.4 Continuous Trust Reassessment

Registry trust must be continuously calculated. When an underlying dependency records a critical CVE or anomalous behavioral drift is detected, the server's registry trust score must automatically downgrade, prompting architectural review.

Enterprise Governance Principle

A trustworthy MCP integration requires verifiable source provenance, strict protocol conformance, controlled permissions, observable execution, and continuous reassessment throughout its production lifecycle.

7. Enterprise MCP Security Toolchain: Leading Tools & Engineering Roles

A production-ready registry assessment integrates established developer and security tooling into an automated pipeline. The following representative toolchain illustrates an enterprise-grade CI/CD verification workflow:

Stage 1

Source Code Security Analysis (SAST & AST)

• Semgrep — Automated AST pattern matching and custom security rule enforcement.
• GitHub CodeQL — Semantic code graph analysis for data-flow and taint tracking.

Stage 2

Secret Detection & Prevention

• Gitleaks — Pre-commit and pipeline detection of hardcoded secrets and tokens.
• GitHub Secret Protection — Repository-level secret scanning and automated push protection.

Stage 3

Supply-Chain Assurance & SBOM Analysis

• Trivy — Comprehensive scanner for container images, configuration drift, and OS packages.
• OSV-Scanner — Distributed vulnerability scanner backed by the Open Source Vulnerabilities database.
• Syft — Generation of standard CycloneDX / SPDX Software Bills of Materials.
• Grype — Automated vulnerability matching against generated SBOM artifacts.

Stage 4

Protocol Conformance & Schema Validation

• MCP Inspector — Interactive testing and diagnostic tool for protocol messaging.
• JSON Schema 2020-12 Test Suite — Automated validation of parameter boundaries and schema dialects.

Stage 5

Runtime Policy & Micro-Segmentation

• Open Policy Agent (OPA) — Declarative policy-based authorization and runtime controls.
• Docker / gVisor — Container runtime isolation and syscall sandboxing.
• Kubernetes NetworkPolicies — Fine-grained egress/ingress network segmentation.

Stage 6

Observability & Continuous Telemetry

• OpenTelemetry (OTel) — Standardized distributed tracing and metrics for AI tool spans.
• Prometheus — Metric collection and automated alerting for error-rate anomalies.
• Grafana — Operational dashboards visualizing latency, token usage, and caller identity.

Engineering Note: Toolchain integration should be tailored to the MCP server's implementation language, deployment architecture, and organizational threat profile. Tool usage alone does not constitute certification.

8. Enterprise MCP Registry Readiness: Architectural Evaluation Matrix

The following evaluation matrix operationalizes the framework into verifiable engineering evidence:

Evaluation Domain	Unverified Implementation	Registry Readiness Standard	Required Evidence Artifact
Source Security	Unreviewed code and implicit permissions	Static analysis passing with zero unresolved critical findings	SAST reports, commit-pinned attestations
Supply Chain	Untracked dependencies and unpinned packages	Cryptographically signed provenance (SLSA) and SBOM generation	CycloneDX/SPDX manifest, signature receipts
Protocol Conformance	Untested message interchange and error handling	JSON-RPC 2.0 lifecycle conformance; Streamable HTTP support	Automated protocol test suites
Schema Integrity	Inconsistent or missing schema definitions	JSON Schema 2020-12 dialect-aware validation with strict bounds	Dialect test logs, schema test suites
Tool Semantics (OWASP LLM06)	Ambiguous descriptions causing agent hallucinations	Explicit functional boundaries, side-effect declarations, human gates	Annotated tool contracts, prompt test cases
Token Economics	Unbounded payloads saturating context windows	Measured token budgets, mandatory pagination, concise summaries	Empirical token consumption benchmarks
Identity & Auth	Unauthenticated access or shared API keys	OAuth 2.1 identity verification with scoped DPoP token bindings	Auth flow configurations, token policies
Runtime Isolation	Direct host access with root privileges	Non-root execution inside isolated containers or microVMs	Container manifests, syscall profiles
Operational Telemetry	Opaque execution without audit logging	Standardized OpenTelemetry distributed tracing and metrics	OTel span dashboards, audit trail archives
Continuous Assurance	One-time review before publication	Continuous vulnerability monitoring and automated trust scoring	Automated CI/CD webhook assessment history

SEOSiri Architectural Evaluation Matrix — criteria for enterprise registry readiness certification.

9. From Pre-Ingestion Validation to Continuous Registry Governance

The five-gate framework forms the foundation of a complete operational lifecycle:

1. Repository Registration: Register the source repository, publisher identity, intended scope, and architectural dependencies.
2. Automated Pre-Ingestion Pipeline: Trigger automated SAST, secret detection, SBOM generation, and protocol test suites.
3. Technical Peer Review: Human-in-the-loop audit of tool descriptions, side-effect declarations, and privilege boundaries.
4. Evidence Cryptographic Sealing: Compile test results, scan logs, and build provenance into an immutable attestation package.
5. Registry Decision Engine: Programmatic policy evaluation against enterprise thresholds (Approve, Conditionally Approve, or Reject).
6. Directory Ingestion: Catalog indexing with machine-readable verification tags, version pins, and gateway routing.
7. Continuous Assurance: Dynamic re-assessment triggered by upstream dependency CVEs, code commits, or anomalous execution patterns.

10. Implementation Blueprint: Operationalizing the Framework

Engineering teams can integrate the pre-initiative framework directly into standard CI/CD workflows:

Phase A: Baseline Definition

• Assign immutable server identifiers and semantic version tags.
• Enumerate all exposed tools, resources, and their underlying data-mutation boundaries.
• Formally specify the target MCP protocol revision.

Phase B: Automated Verification Gate

• Execute automated static analysis (Semgrep, CodeQL) blocking builds on high/critical findings.
• Validate all JSON Schemas against the 2020-12 meta-schema.
• Run simulated JSON-RPC handshake, tool-call, and error scenarios.
• Benchmark P95 token payloads against organizational context budgets.

Phase C: Attestation & Packaging

• Generate and sign CycloneDX/SPDX SBOMs using digital signatures.
• Publish deployment manifests specifying microVM or container boundary policies.
• Document access-control scopes (OAuth 2.1 scopes).

Phase D: Runtime Observability

• Emit OpenTelemetry trace spans on every tool invocation.
• Ingest audit logs into SIEM/SOC platforms for real-time anomaly detection.
• Establish automated rollback hooks if error rates or execution latencies exceed thresholds.

11. The Broader Architectural Implication: Trust Must Travel with AI Tools

The evolution of AI agent ecosystems mirrors the early history of web services and software package managers. The initial phase is characterized by an explosion of open-source discovery; the mature enterprise phase is defined by security, governance, and verifiable trust.

As autonomous agents gain the capability to query databases, write code, interact with financial systems, and trigger physical actuators, organizations cannot rely on static directory listings. Trust must be continuous, measurable, and cryptographically verified.

For the broader SEOSiri developer ecosystem, this framework underpins our development of secure MCP server gateways, enterprise AI governance planes, and resilient API infrastructure.

Explore the SEOSiri Developer Platform to inspect our live edge topology, interactive MCP tooling graph, and zero-trust developer resources.

For related deep-dive engineering guides, explore Building Production-Grade MCP Servers and DevSecOps at the Edge: Zero-Trust API Gateways and WAF Architectures.

The SEOSiri Architectural Axiom

Never confuse an available AI tool with a trusted AI capability. Production readiness requires verification before ingestion, policy enforcement during execution, and continuous governance after deployment.

Discoverability creates access. Governance establishes trust.

12. Frequently Asked Questions: MCP Registry Security and Governance

What is MCP Registry Readiness Engineering?

MCP Registry Readiness Engineering is a structured discipline for evaluating Model Context Protocol servers prior to public or private directory ingestion. It encompasses source security auditing, supply-chain verification, protocol conformance, schema dialect integrity, semantic contract reliability, identity-aware authorization, and continuous operational assurance.

What is the MCP Registry Pre-Initiative Framework?

Developed by SEOSiri, it is a proposed five-gate architecture that establishes verifiable evidence baselines before an MCP server is deployed into enterprise agent workflows: Gate 1 (Security & Supply Chain), Gate 2 (Protocol & Schema), Gate 3 (Semantic & Token Economics), Gate 4 (Identity & Runtime Isolation), and Gate 5 (Operational Governance & Provenance).

Does the MCP specification require JSON Schema Draft-07?

No. While Draft-07 was used in earlier prototypes, modern MCP specifications adopt JSON Schema 2020-12 as the standard default dialect when no alternate dialect is explicitly declared. Enterprise validation engines must support dialect-aware validation.

Is Server-Sent Events (SSE) the current standard MCP remote transport?

Streamable HTTP is the modern standard transport for remote MCP servers. While Server-Sent Events are supported within the streaming specification, standalone HTTP+SSE is considered a legacy transport maintained for backward compatibility.

Does passing a static security scan guarantee that an MCP server is safe?

No. SAST tools only detect identifiable syntax patterns. A secure MCP server also requires software supply-chain auditing (SBOM), runtime sandboxing, scoped authorization boundaries, and semantic prompt validation to prevent indirect injection attacks.

How does semantic tool contract engineering prevent agent failure?

Language models rely on tool descriptions to decide when and how to call external services. Ambiguous descriptions cause tool-hallucination loops or excessive agency (OWASP LLM06). Semantic contract engineering enforces unambiguous descriptions, explicit boundary conditions, and state-change declarations.

Why is publisher verification critical in MCP registries?

Publisher verification links a published MCP package cryptographically to an authenticated author and source repository, mitigating supply-chain poisoning, package-squatting, and malicious impersonation.

13. Technical References and Standards

• Model Context Protocol — Official Specification
• Official MCP Registry Documentation
• IETF JSON Schema 2020-12 Specification
• JSON-RPC 2.0 Specification
• NIST SP 800-218 — Secure Software Development Framework (SSDF)
• SLSA v1.0 — Supply-chain Levels for Software Artifacts
• OWASP Top 10 for Large Language Model Applications
• RFC 9449 — OAuth 2.0 Demonstrating Proof-of-Possession (DPoP)

Article Architect: Momenul Ahmad
Organization: SEOSiri
Classification: Enterprise AI Architecture | MCP Security | Software Supply Chain Governance

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