MCP互換エージェント向けのAI駆動型カバーレター生成ツール。求職活動向けの初のプロダクションMCPサーバーです。
ツール | 説明 |
| 求人情報から15以上の構造化フィールドを抽出 |
| 候補者の履歴書と求人データを照合 |
| ストーリー主導型のカバーレターを生成 |
| カバーレターをスコアリングおよび評価 |
| 利用可能な物語のアーキタイプとトーンを一覧表示 |
Related MCP server: laddro-career-mcp
~/Library/Application Support/Claude/claude_desktop_config.json に以下を追加してください：
{
"mcpServers": {
"storylenses": {
"command": "npx",
"args": ["-y", "@storylenses/mcp-server"],
"env": {
"STORYLENSES_API_KEY": "your-api-key"
}
}
}
}.cursor/mcp.json または VS CodeのMCP設定に追加してください：
{
"mcp": {
"servers": {
"storylenses": {
"command": "npx",
"args": ["-y", "@storylenses/mcp-server"],
"env": {
"STORYLENSES_API_KEY": "your-api-key"
}
}
}
}
}docker run -e STORYLENSES_API_KEY=your-key ghcr.io/benediktgirz/storylenses-mcp-server変数 | 必須 | 説明 |
| はい | storylenses.app/mcp から取得したAPIキー |
| いいえ | APIベースURL（デフォルト: https://www.storylenses.app） |
// 1. Analyze job posting
const job = await callTool("storylenses_analyze_job", {
job_url: "https://linkedin.com/jobs/view/12345"
});
// 2. Match candidate profile
const match = await callTool("storylenses_match_profile", {
job_analysis: job,
candidate_cv: "Senior engineer with 7 years React experience..."
});
// 3. Generate cover letter
const letter = await callTool("storylenses_generate_letter", {
job_analysis: job,
match_data: match,
candidate_name: "Alex Chen",
archetype: match.suggestedArchetype
});
// 4. Quality check
const score = await callTool("storylenses_quality_check", {
letter_text: letter.letter_text,
job_analysis: job
});npm install
STORYLENSES_API_KEY=your-key npm teststorylenses.app/mcp にアクセスしてAPIキーを取得してください。
無料: 月10回生成
開発者 ($29/月): 月200回生成
スケール ($99/月): 月1,000回生成
MIT
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v0.1.0storylenses_analyze_jobstorylenses_generate_letterstorylenses_list_archetypesstorylenses_match_profilestorylenses_quality_checkScored across 5 tools
Each tool occupies a distinct stage in the workflow pipeline: analyze_job extracts job data, match_profile compares candidate to job, list_archetypes provides style options, generate_letter creates output, and quality_check validates results. No functional overlap exists between tools.
All tools follow an identical storylenses_verb_noun pattern with consistent snake_case formatting, clear action-oriented verbs (analyze, generate, list, match, check), and uniform prefixing that prevents collisions with other servers.
Five tools is ideally suited for this focused domain, covering the complete cover letter lifecycle from input analysis and matching through generation and validation without bloat, redundancies, or missing critical steps.
Provides comprehensive coverage of the generation workflow including analysis, matching, archetype selection, creation, and scoring; minor gap requires regenerating from scratch rather than refining existing letters based on quality feedback.
Generate tailored, ATS-optimized resume PDFs and cover letters from a job description, over MCP.
Job application tracker for developers - AI agents write over MCP, you review in a dashboard.
Tailored, graded job applications: a CV, cover letter and form answers built per vacancy.
AI job search MCP — fact-checked jobs, application tracker, alerts. ChatGPT, Claude, Cursor.
