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> 全栈工程师 / AI 应用开发者 — 6年全栈开发经验，专注于 AI 应用落地与产品化。擅长将前沿 AI 技术转化为可交付的商业产品，具备从 0 到 1 的完整产品开发能力。熟悉 Next.js 全栈架构、大模型 API 集成、实时协作系统设计。

This site exposes resume data via the Model Context Protocol (MCP).

## MCP Endpoint

- **URL**: `http://www.leeson.cloud/mcp`
- **Transport**: HTTP (Streamable HTTP)
- **Auth**: Bearer token (invite code). Pass via `Authorization: Bearer <invite-code>` header.

## Tools

- **get_profile**: Get the candidate's public profile: name, title, summary, and social links.
- **get_experience**: Get the candidate's work experience. Optionally filter by keyword.
- **get_projects**: Get the candidate's project experience. Optionally filter by technology or keyword.
- **get_skills**: Get the candidate's skill list. Optionally filter by category.
- **get_education**: Get the candidate's educational background.
- **search_resume**: Full-text search across the entire resume with relevance ranking.
- **evaluate_fit**: Analyze candidate-job fit: matched/missing skills, overall score, and recommendations.
- **get_career_summary**: Comprehensive career analysis: seniority, domain expertise, career trajectory, core strengths.

## Resources

- `resume://full` — Complete resume data in JSON format
- `resume://summary` — Candidate summary: name, title, experience, seniority, core skills

## Discovery

- **Well-known**: `http://www.leeson.cloud/.well-known/mcp` — Machine-readable MCP metadata (JSON)
- **This file**: `http://www.leeson.cloud/llms.txt` — Human/AI-readable service description (Markdown)