目录 / GetWinstackMCP
MCP
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已上架
GetWinstackMCP
Winstack (Winny) is a persistent career memory that lives inside your AI assistant. Ingest old resumes or just describe your experience in conversation — Winny deduplicates, asks clarifying questions, and builds a structured career profile. It remembers between sessions: new skills, side projects, shipped work, career goals. When a job description comes along, Winny scores your existing bullets against it, tells you plainly where the gaps are instead of inventing experience, and generates a tailored resume you open in the browser and download as a PDF. Free for 30 days, then a one-time $9.99 unlock for resume generation — not a subscription. Adding and reading your career data stays free forever. You bring your own AI, so there's no per-message cost. 28 tools for career profile management, benchmarking, and resume generation.
该来源不提供完整文件导出（国内平台多为平台内托管），仅存元数据与原链
接入信息
- 传输形态
- http
- 鉴权方式
- 鉴权未知
- 端点
https://winstackmcp--winstackmcp.run.tools
鉴权方式未标注，请核对官方文档后再接入——不要直接使用以下片段
{
"mcpServers": {
"GetWinstackMCP": {
"url": "https://winstackmcp--winstackmcp.run.tools"
}
}
}
能力清单
| 工具 | 说明 |
|---|---|
| get_career_profile | Get the full career profile — all experiences, bullet variations, education, skills, notes, context. Returns empty structure if no profile exists. |
| get_profile_stats | Quick counts only — use to check if profile exists without loading full data. |
| get_career_progression | Retrieve the user's career strategy, goals, company watchlist, and long-term positioning. Use this as context before job search, resume generation, or career advice. |
| update_career_progression | Store and update the user's career strategy, goals, company watchlist, and long-term positioning. Partial update — only provided fields are merged. Updated passively through conversation. Used as context for all job search and resume generation. Fields: current_status, target_roles[], target_companies[{name, status, notes, contacts[]}], five_year_plan, ten_year_plan, unique_opportunities[], ai_proofing_strategy, values_and_constraints, notes[] |
| set_contact | Set or update contact info. Merges with existing — only overwrites fields you provide. |
| add_experience | Add a work experience with ALL bullet variations. Include every version from every resume. |
| add_bullet | Add a bullet to an existing experience. Use for new variations from different resumes. |
| update_experience | Update an existing experience's fields (not bullets). |
| add_education | Add an education entry. |
| add_skills | Add skills by category. Duplicates are skipped automatically. |
| add_summary_fragment | Store a professional summary line/paragraph. Store ALL variations from different resumes. Exact duplicates are skipped automatically. |
| add_note | Store contextual clarification — 'company was acquired', 'promoted from X to Y', etc. Exact duplicates are skipped. |
| add_project | Add a side project, open source contribution, or portfolio piece to the career profile. Use this when you discover projects from GitHub, personal websites, or conversation. Projects strengthen a resume by showing initiative beyond day-job work. |
| get_projects | Get all side projects and portfolio pieces from the career profile. |
| ingest | Ingest career data from various sources. Use source='resume_text' to parse a resume, source='github' to enrich from GitHub repos, or source='url' to extract career info from a portfolio/LinkedIn/blog URL. Returns instructions for the agent to follow. |
| batch_ingest | Import a fully parsed resume in one atomic operation. ONE approval, ONE tool call — writes contact, experiences, bullets, education, skills, summary, and notes all at once. The agent should: 1. Call ingest(source='resume_text') to get existing experiences and instructions 2. Parse the resume text into structured data 3. Call batch_ingest with the parsed data — this replaces the 10+ individual tool calls Each bullet should include a quality tag: "strong", "weak:needs-metrics", "weak:vague", or "strong:qualitative". Existing experiences are matched by company + title — pass their ID in the experiences array to add bullet variations instead of duplicates. |
| log_achievement | The user is casually talking about their work — a project they shipped, a problem they solved, a metric they hit, a skill they learned. Convert their casual description into a professional resume bullet and add it to the right experience. How to use: 1. Turn the user's casual language into a strong, quantified resume bullet (action verb + what + impact) 2. Find the matching experience by company or let the user confirm 3. This tool handles both steps — it creates the bullet AND attaches it to the experience Examples of casual → bullet: - "shipped the new auth system today" → "Designed and launched authentication system, improving login success rate by X%" - "saved the team 3 hours a week with my script" → "Developed automation script reducing team manual effort by 3 hours weekly" - "led the Q3 planning session" → "Led quarterly planning session aligning cross-functional teams on product roadmap" |
| mark_resume_processed | Mark a resume file as ingested. |
| generate_tailored_resume | Save a tailored resume for a specific job. Load get_career_profile first, select best bullet variations, write a tailored summary. Output format matches the WinStack editor — user pastes the JSON into the editor's JSON view. |
| present_resume | Present a tailored resume to the user for review BEFORE sending to the editor. You (the AI) should call this tool AFTER building the resume but BEFORE generate_tailored_resume. This tool formats the resume for readable presentation in chat so the user can review and request changes. WORKFLOW: 1. Load career profile (get_career_profile) 2. Build the tailored resume in your context 3. Call present_resume — this shows it to the user with your reasoning 4. User reviews and requests changes ("make it more technical", "swap that bullet") 5. You make changes in your context and call present_resume again 6. When user approves → call generate_tailored_resume to save + get editor link 7. User taps editor link for final pixel-level tweaks + PDF download |
| list_generated_resumes | List all previously generated tailored resumes. |
| get_generated_resume | Retrieve a previously generated resume by slug. Returns concise summary + editor link. |
| benchmark_resume | Analyze the full career profile against a job description BEFORE generating a resume. WHEN TO USE: Before resume generation — this is step 1 of the pipeline. WORKFLOW after calling this tool: 1. EXTRACT JD REQUIREMENTS — skills, tools, certifications, domain keywords, soft skills, implicit requirements 2. SCORE EVERY BULLET — relevance 0-10, flag which JD requirements each addresses, note metrics 3. RANK AND SELECT — pick 3-5 best per role, avoid redundancy, pick strongest variation 4. STRENGTHEN WEAK BULLETS — for selected bullets tagged "weak:needs-metrics" or "weak:vague": Ask user ONE AT A TIME. BANNED words: spearheaded, orchestrated, leveraged, synergized, revolutionized, cutting-edge, best-in-class. GOOD words: Led, Built, Cut, Saved, Ran, Shipped, Fixed, Grew, Designed, Launched. Replace via delete_item + add_bullet with tags=["strong"]. Skip if user says "skip". 5. IDENTIFY GAPS — COVERED / AVAILABLE (in profile but not selected) / GAP (not in profile) 6. PRESENT ANALYSIS — "Scored X roles, Y bullets. Coverage: Z%. N gaps." Offer gap interview. 7. GAP INTERVIEW — one question at a time, convert answers to bullets, add to profile 8. OUTPUT FINAL SELECTION — selected bullets per role, recommended summary + skills, coverage score Then: "Ready to generate?" → present_resume → generate_tailored_resume Do NOT dump all questions at once. Ask one, wait, process, ask next. |
| delete_item | Delete items from the career profile. Items are soft-deleted by default (hidden but recoverable). Use permanent=true to permanently remove. Supported types: - experience: hides experience + all its bullets (requires id) - bullet: hides a single bullet (requires id) - education: removes an education entry (requires id) - skill: removes a skill from a category (requires category + item) - note: removes a note (requires id) - summary_fragment: removes a summary fragment (requires id) - target_company: removes a company from career progression watchlist (requires item = company name) - career_field: clears a career progression field (requires item = field name) |
| undo_delete | Restore the most recently deleted experience or bullet. Only works for soft-deleted items. |
| reset_profile | Delete ALL career data including career progression. This cannot be undone. Use only when the user explicitly asks to start over. |
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