@aisdlc/mcp

中文文档
3.2.0发布于 2026/11/05MITTypeScriptES Module构建来源已验证近 30 天下载 4359

Model Context Protocol (MCP) native server for AI-SDLC tools, resources, and governance

原始使用文档
文档目录18 节
  1. What is AI-SDLC?
  2. What is MCP?
  3. Installation
  4. Role in AI-SDLC
  5. Usage
  6. Running the Server
  7. Client Configuration
  8. Available MCP Tools
  9. 1. Workflow & Scaffolding Tools (Consolidated Entrypoints)
  10. 2. Spec-Driven Development (SDD) Tools
  11. 3. Granular Verification Tools (Quality Gates)
  12. 4. Reporting & Telemetry Tools
  13. Available Context Resources
  14. Related packages
  15. AI-native engineering
  16. Project
  17. Contributing
  18. License

@aisdlc/mcp

MCP integration for AI-SDLC, enabling AI-SDLC capabilities to be exposed through the Model Context Protocol.

What is AI-SDLC?

AI-SDLC is an AI-native Software Development Lifecycle framework focused on bringing engineering governance, traceability, and quality controls to AI-assisted software development.

The framework includes capabilities around:

  • Requirements and specifications
  • Software changes
  • Verification
  • Quality gates
  • Traceability
  • Engineering KPIs
  • AI-assisted workflows
  • Agent-based engineering
  • MCP integration

@aisdlc/mcp provides the MCP integration layer for the framework.

What is MCP?

The Model Context Protocol (MCP) provides a standardized way for AI applications to interact with external tools and context.

AI-SDLC uses MCP as an integration mechanism between AI clients and software-engineering capabilities.

Installation

npm install @aisdlc/mcp

Or with pnpm:

pnpm add @aisdlc/mcp

Role in AI-SDLC

The package sits between AI clients and the AI-SDLC core:

              AI client
                  │
                  │ MCP
                  ▼
            @aisdlc/mcp
                  │
                  ▼
            @aisdlc/core
                  │
                  ▼
        AI-SDLC engineering
           capabilities

This separation keeps the MCP integration independent from the underlying core capabilities.

Usage

The MCP package is intended to be used when integrating AI-SDLC capabilities with an MCP-compatible AI client or agent environment.

For the command-line entry point and local AI-SDLC workflows, see @aisdlc/cli.

Running the Server

Start the MCP server using npx or through the AI-SDLC CLI:

# Direct execution with npx
npx @aisdlc/mcp

# Or via the CLI
aisdlc mcp

Client Configuration

1. Automatic Turnkey Setup (aisdlc init)

When you initialize a repository using aisdlc init (or npx @aisdlc/cli init), the framework automatically scaffolds preconfigured MCP files out of the box for all supported IDEs and agent environments, regardless of CI provider or agent settings:

  • Google Antigravity / Gemini CLI: antigravity.mcp.json
  • Visual Studio Code / Copilot: .vscode/mcp.json
  • Cursor IDE: .cursor/mcp.json

Zero manual JSON configuration is required.

2. Manual Client Configuration

To configure other clients (e.g. Claude Desktop) or add @aisdlc/mcp manually:

{
  "mcpServers": {
    "ai-sdlc": {
      "command": "npx",
      "args": ["-y", "@aisdlc/mcp"]
    }
  }
}

Available MCP Tools

@aisdlc/mcp provides 24 deterministic tools divided into 4 functional categories:

1. Workflow & Scaffolding Tools (Consolidated Entrypoints)

ToolDescriptionParameters
newInitializes a new project or configures AI-SDLC governance and structure in an existing repository (policies, templates, hooks, and optional CI).targetDir (string), ci (enum: github, gitlab, azure, bitbucket), dryRun (boolean), agents (string), architecture (enum: minimal, full, complete, none)
verifyExecutes deterministic AI-SDLC Quality Gates (all 12 gates in full profile, or essential gates [quality, security, licenses] in lite profile) in a consolidated run and returns overall repository health.root (string), profile (enum: full, lite)
reportGenerates all AI-SDLC reports combined: interactive web dashboard with PDaC graph (HTML) and formal code quality report (Markdown).root (string), dashboardOutput (string), qualityPolicy (string)

2. Spec-Driven Development (SDD) Tools

ToolDescriptionParameters
sdd_change_newCreates the full deterministic scaffolding for a new SDD change (proposal.md, spec.md, design.md, tasks.md, handoff.yaml).name (string, required), id (string), profile (enum: patch, standard, critical), framework (enum: openspec, speckit), author (string), from (string[]), root (string)
sdd_check_fixDeterministically synchronizes Gherkin scenarios to .feature files and updates PDaC SHA-256 digests without touching source code.root (string)
sdd_depositDeposits or regenerates the canonical handoff.yaml (HOF-*) sidecar in an active SDD change.change (string, required), title (string), framework (enum: openspec, speckit), requirements (string[]), useCases (string[]), root (string)
sdd_integrateIntegrates and promotes a completed SDD change to the canonical baseline and archives its directory to completed/.change (string), auto (boolean), author (string), root (string)
get_active_handoffQueries in-memory PDaC subgraph and contents of an active change for surgical context injection into the agent.change (string, required), root (string)

3. Granular Verification Tools (Quality Gates)

ToolDescriptionParameters
verify_qualityEvaluates cyclomatic complexity, cognitive complexity, maintainability index, and function length against quality-policy.yaml.root (string), maxCyclomatic (number), maxCognitive (number), minMaintainability (number)
verify_schemasValidates specification Markdown artifacts against canonical JSON Schemas (Draft 2020-12).root (string)
verify_securityExecutes deterministic secret scanning (Gitleaks) and SAST static analysis (command injection, SQLi, SSRF).root (string), minSeverity (enum: CRITICAL, HIGH, MEDIUM)
verify_privacyAudits Personal Data Assets (DATA-ASSET-*), GDPR Art. 30 Records (PRIV-ROPA-*), Privacy Requirements (PRIV-REQ-*), DPIA gates (DPIA-*), and static PII-SAST rules (PRIV-001–PRIV-008) against privacy-policy.yaml.root (string), policyPath (string), writeReports (boolean)
verify_traceabilityAudits the 360° inverted traceability matrix (Upstream PDaC, Midstream arc42, Downstream BDD/tests).root (string)
verify_governanceAudits task governance compliance and human autonomy classification modes (AUTONOMOUS, HUMAN_REVIEW_PLAN, etc.).root (string)
verify_testingAudits that 100% of requirements and tasks have verifiable tests on disk.root (string)
verify_licensesAudits Open Source license compliance against license-policy.yaml.root (string), policy (string), depth (enum: direct, transitive)
verify_duplicatesAudits identifier collisions, redundant normative statements, and specification overlaps.root (string)
verify_frictionEvaluates progressive friction rules and anti-bypass guardrails (prevents patch-profile changes from modifying protected paths).change (string), diffFiles (string[]), root (string)
verify_pdacAudits the product graph (Product Definition as Code) and deterministically verifies the absence of cryptographic drift in citations.root (string), autoSync (boolean)

4. Reporting & Telemetry Tools

ToolDescriptionParameters
report_dashboardGenerates the interactive web dashboard and Cytoscape.js graph of the RTM / PDaC matrix at reports/dashboard.html.output (string), title (string), root (string)
report_qualityGenerates the formal polyglot code quality report at reports/QUALITY_REPORT.md.policy (string), mode (enum: STRICT, PERMISSIVE), root (string)
kpi_prCalculates commit KPI aggregation and telemetry (human vs. AI agents) for a Pull Request.base (string), head (string), root (string)
kpi_releaseCalculates consolidated Release KPIs (Defect Injection Rate, rework ratio, KLoC volume, token costs, etc.).release (string, required), base (string), outputDir (string), writeReports (boolean), root (string)
git_detect_authorUniversally and IDE-independently detects whether the current author is human or an AI agent.root (string)

Available Context Resources

The MCP server provides read-only context resources accessible via canonical aisdlc:// URIs:

Resource URIMIME TypeDescription
aisdlc://policies/qualitytext/yamlContent of quality-policy.yaml (complexity thresholds, rules, gate limits).
aisdlc://policies/licensestext/yamlContent of license-policy.yaml (permitted, restricted, and blocked licenses).
aisdlc://policies/privacytext/yamlContent of privacy-policy.yaml (GDPR/LOPDGDD/ISO 27701 rules, PII-SAST controls, allowed regions).
aisdlc://changes/activeapplication/jsonStructured list of active SDD changes in specs/changes/active/ with task and handoff status.
aisdlc://changes/completedapplication/jsonList of completed and archived SDD changes in specs/changes/completed/.
aisdlc://status/summaryapplication/jsonConsolidated repository status summary (handoffs count, policy file existence, timestamp).
PackagePurpose
@aisdlc/coreCore AI-SDLC capabilities
@aisdlc/mcpMCP integration
@aisdlc/cliCommand-line interface

AI-native engineering

AI-SDLC is designed around an important principle:

AI-assisted development should increase engineering leverage without removing engineering controls.

MCP provides one of the integration mechanisms that makes this possible by allowing AI systems to interact with controlled engineering capabilities.

Project

AI-SDLC is an open-source project.

GitHub: https://github.com/altromon/AI-SDLC

The repository contains the complete architecture, governance model, development processes, and documentation.

Contributing

Contributions, issues, and architectural discussions are welcome.

Please see the GitHub repository for contribution guidelines and development information.

License

See the repository license for the current licensing terms.

版本与发布记录

@aisdlc/mcp 共发布 30 个版本,首次发布于 2026/10/02;过去 12 个月发布了 30 个版本。最新版本附带 npm provenance 构建来源证明,可追溯到公开的 CI 构建记录。

版本发布日期距今
3.2.0latest2026/11/051 天前
3.1.02026/11/042 天前
3.0.02026/11/024 天前
2.5.12026/11/015 天前
2.5.02026/10/316 天前
2.4.02026/10/306 天前

关于 @aisdlc/mcp 的常见问题

@aisdlc/mcp 是什么?

Model Context Protocol (MCP) native server for AI-SDLC tools, resources, and governance

如何安装 @aisdlc/mcp?

在项目目录运行 npm install @aisdlc/mcp,或使用 pnpm add / yarn add / bun add。它还提供命令行工具 aisdlc-mcp,可以用 npx aisdlc-mcp 直接运行。

@aisdlc/mcp 支持 TypeScript 吗?

支持。包内自带 TypeScript 类型声明(package.json 声明了 types 入口),安装后即可获得类型提示,无需再安装 @types 包。

@aisdlc/mcp 支持 ESM 还是 CommonJS?

以 ES Module 形式发布,推荐使用 import 引入。在 CommonJS 项目中,Node.js 20.19+ / 22.12+ 可以直接 require() 不含顶层 await 的 ES Module,更早的版本需要改用动态 import()。

@aisdlc/mcp 可以商用吗?

@aisdlc/mcp 使用 MIT 许可。宽松许可:允许商业使用、修改和再分发,通常只需在分发时保留原版权与许可声明。以上为概括,不构成法律意见,请以许可原文为准。

@aisdlc/mcp 的下载量有多少?

根据 npm 官方下载统计,@aisdlc/mcp 在 2026/10/05 – 2026/11/03 这 30 天内被下载 4,359 次,日均约 145 次。下载量会把 CI 构建、镜像同步和作为其他包依赖的安装一并计入,适合横向比较热度,不能直接等同于使用人数。

@aisdlc/mcp 还在维护吗?

最新版本 3.2.0 发布于 2026/11/05(1 天前);至今共发布 30 个版本,其中过去 12 个月发布了 30 个;首次发布于 2026/10/02。发布频率只是参考信号:功能稳定的工具可能很少需要更新,建议结合源码仓库的 issue 和提交记录判断。