Questionnaire Component Governance MCP Demo
Enables AI agents to query component governance rules, validate component props, and generate development prompts for questionnaire editors.
README
Questionnaire Component Governance MCP Demo
一个面向问卷编辑器场景的 MCP 小 demo，用来演示如何把组件治理能力结构化为 Resources、Tools 和 Prompts，并让 AI Agent 在组件使用、规则查询和开发约束场景里复用这套能力。
项目目标
这个 demo 主要解决两个问题：
- 把组件规范从零散文档沉淀为机器可读的结构化规则。
- 让 AI Agent 在生成或修改问卷组件时，先读取规范、再执行校验，最后给出建议或约束结果。
能力设计
Resources
governance://component-guidelines- 暴露组件治理文档，提供职责边界、状态管理约束、AI 使用约束等通用规则。
governance://component-rules- 暴露完整组件规则 JSON，提供组件名称、必传属性、允许属性、禁止模式、使用示例等结构化数据。
Tools
list_component_rules- 列出当前已注册的问卷组件规范。
get_component_rule- 查询某个组件的详细规范。
validate_component_usage- 校验组件
props是否符合治理规则。
- 校验组件
build_component_prompt- 根据任务和组件规则生成给 AI Agent 使用的开发提示。
Prompts
create-question-component- 给 Agent 一个标准化的新增题型组件工作流，要求其遵守现有治理规范完成组件设计与接入。
目录结构
.
|-- rules/
| |-- components.json
| `-- guideLines.md
|-- src/
| |-- index.ts
| |-- loadRules.ts
| |-- schemas.ts
| `-- validateRules.ts
`-- dist/
本地运行
npm install
npm run ci
npm run dev
说明
这个 demo 更偏“治理能力建模”而不是完整业务系统，重点在于：
- 如何把组件规范做成可读的 MCP Resources
- 如何把组件校验做成可执行的 MCP Tools
- 如何把 AI 开发流程固化为可复用的 Prompt 模板
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