MCP服务构建器
MCP Server Builder
by alirezarezvani
从 OpenAPI 一键生成 Python/TypeScript MCP server 脚手架,并校验 tool schema、命名规范与版本兼容性,适合把现有 REST API 快速发布成可生产演进的 MCP 服务。
帮你快速搭建 MCP 服务与后端 API,脚手架完善、扩展顺手,尤其适合想高效验证服务能力的开发者。
安装
claude skill add --url github.com/alirezarezvani/claude-skills/tree/main/engineering/mcp-server-builder文档
Tier: POWERFUL
Category: Engineering
Domain: AI / API Integration
Overview
Use this skill to design and ship production-ready MCP servers from API contracts instead of hand-written one-off tool wrappers. It focuses on fast scaffolding, schema quality, validation, and safe evolution.
The workflow supports both Python and TypeScript MCP implementations and treats OpenAPI as the source of truth.
Core Capabilities
- Convert OpenAPI paths/operations into MCP tool definitions
- Generate starter server scaffolds (Python or TypeScript)
- Enforce naming, descriptions, and schema consistency
- Validate MCP tool manifests for common production failures
- Apply versioning and backward-compatibility checks
- Separate transport/runtime decisions from tool contract design
When to Use
- You need to expose an internal/external REST API to an LLM agent
- You are replacing brittle browser automation with typed tools
- You want one MCP server shared across teams and assistants
- You need repeatable quality checks before publishing MCP tools
- You want to bootstrap an MCP server from existing OpenAPI specs
Key Workflows
1. OpenAPI to MCP Scaffold
- Start from a valid OpenAPI spec.
- Generate tool manifest + starter server code.
- Review naming and auth strategy.
- Add endpoint-specific runtime logic.
python3 scripts/openapi_to_mcp.py \
--input openapi.json \
--server-name billing-mcp \
--language python \
--output-dir ./out \
--format text
Supports stdin as well:
cat openapi.json | python3 scripts/openapi_to_mcp.py --server-name billing-mcp --language typescript
2. Validate MCP Tool Definitions
Run validator before integration tests:
python3 scripts/mcp_validator.py --input out/tool_manifest.json --strict --format text
Checks include duplicate names, invalid schema shape, missing descriptions, empty required fields, and naming hygiene.
3. Runtime Selection
- Choose Python for fast iteration and data-heavy backends.
- Choose TypeScript for unified JS stacks and tighter frontend/backend contract reuse.
- Keep tool contracts stable even if transport/runtime changes.
4. Auth & Safety Design
- Keep secrets in env, not in tool schemas.
- Prefer explicit allowlists for outbound hosts.
- Return structured errors (
code,message,details) for agent recovery. - Avoid destructive operations without explicit confirmation inputs.
5. Versioning Strategy
- Additive fields only for non-breaking updates.
- Never rename tool names in-place.
- Introduce new tool IDs for breaking behavior changes.
- Maintain changelog of tool contracts per release.
Script Interfaces
python3 scripts/openapi_to_mcp.py --help- Reads OpenAPI from stdin or
--input - Produces manifest + server scaffold
- Emits JSON summary or text report
- Reads OpenAPI from stdin or
python3 scripts/mcp_validator.py --help- Validates manifests and optional runtime config
- Returns non-zero exit in strict mode when errors exist
Common Pitfalls
- Tool names derived directly from raw paths (
get__v1__users___id) - Missing operation descriptions (agents choose tools poorly)
- Ambiguous parameter schemas with no required fields
- Mixing transport errors and domain errors in one opaque message
- Building tool contracts that expose secret values
- Breaking clients by changing schema keys without versioning
Best Practices
- Use
operationIdas canonical tool name when available. - Keep one task intent per tool; avoid mega-tools.
- Add concise descriptions with action verbs.
- Validate contracts in CI using strict mode.
- Keep generated scaffold committed, then customize incrementally.
- Pair contract changes with changelog entries.
Reference Material
- references/openapi-extraction-guide.md
- references/python-server-template.md
- references/typescript-server-template.md
- references/validation-checklist.md
- README.md
Architecture Decisions
Choose the server approach per constraint:
- Python runtime: faster iteration, data pipelines, backend-heavy teams
- TypeScript runtime: shared types with JS stack, frontend-heavy teams
- Single MCP server: easiest operations, broader blast radius
- Split domain servers: cleaner ownership and safer change boundaries
Contract Quality Gates
Before publishing a manifest:
- Every tool has clear verb-first name.
- Every tool description explains intent and expected result.
- Every required field is explicitly typed.
- Destructive actions include confirmation parameters.
- Error payload format is consistent across all tools.
- Validator returns zero errors in strict mode.
Testing Strategy
- Unit: validate transformation from OpenAPI operation to MCP tool schema.
- Contract: snapshot
tool_manifest.jsonand review diffs in PR. - Integration: call generated tool handlers against staging API.
- Resilience: simulate 4xx/5xx upstream errors and verify structured responses.
Deployment Practices
- Pin MCP runtime dependencies per environment.
- Roll out server updates behind versioned endpoint/process.
- Keep backward compatibility for one release window minimum.
- Add changelog notes for new/removed/changed tool contracts.
Security Controls
- Keep outbound host allowlist explicit.
- Do not proxy arbitrary URLs from user-provided input.
- Redact secrets and auth headers from logs.
- Rate-limit high-cost tools and add request timeouts.
相关 Skills
MCP构建
by anthropics
聚焦高质量 MCP Server 开发,覆盖协议研究、工具设计、错误处理与传输选型,适合用 FastMCP 或 MCP SDK 对接外部 API、封装服务能力。
✎ 想让 LLM 稳定调用外部 API,就用 MCP构建:从 Python 到 Node 都有成熟指引,帮你更快做出高质量 MCP 服务器。
Slack动图
by anthropics
面向Slack的动图制作Skill,内置emoji/消息GIF的尺寸、帧率和色彩约束、校验与优化流程,适合把创意或上传图片快速做成可直接发送的Slack动画。
✎ 帮你快速做出适配 Slack 的动图,内置约束规则和校验工具,少踩上传与播放坑,做表情包和演示都更省心。
邮件模板
by alirezarezvani
快速搭建生产可用的事务邮件系统:生成 React Email/MJML 模板,接入 Resend、Postmark、SendGrid 或 AWS SES,并支持本地预览、i18n、暗色模式、反垃圾优化与追踪埋点。
✎ 面向营销与服务场景,快速搭建高质量邮件模板,省去反复设计与切图成本,成熟度和社区认可都很高。
相关 MCP 服务
Slack 消息
编辑精选by Anthropic
Slack 是让 AI 助手直接读写你的 Slack 频道和消息的 MCP 服务器。
✎ 这个服务器解决了团队协作中需要 AI 实时获取 Slack 信息的痛点,特别适合开发团队让 Claude 帮忙汇总频道讨论或发送通知。不过,它目前只是参考实现,文档有限,不建议在生产环境直接使用——更适合开发者学习 MCP 如何集成第三方服务。
by netdata
io.github.netdata/mcp-server 是让 AI 助手实时监控服务器指标和日志的 MCP 服务器。
✎ 这个工具解决了运维人员需要手动检查系统状态的痛点,最适合 DevOps 团队让 Claude 自动分析性能数据。不过,它依赖 NetData 的现有部署,如果你没用过这个监控平台,得先花时间配置。
by d4vinci
Scrapling MCP Server 是专为现代网页设计的智能爬虫工具,支持绕过 Cloudflare 等反爬机制。
✎ 这个工具解决了爬取动态网页和反爬网站时的头疼问题,特别适合需要批量采集电商价格或新闻数据的开发者。不过,它依赖外部浏览器引擎,资源消耗较大,不适合轻量级任务。