5つの主要なATSパーサーに対して履歴書をリント（検証）するModel Context Protocolサーバー。
3つのMCPツールを公開しており、MCP互換のAIエージェント（Claude Code、Cursor、Windsurf、Zed、OpenCode、Clineなど）が、以下のATSの文書化された特性に基づいて履歴書を分析できます。
Workday
Greenhouse
Lever
Taleo (Oracle)
iCIMS
これらは最も広く使用されている5つのエンタープライズATSシステムです。それぞれ履歴書の解析方法が微妙に異なります。「0〜100のATSスコア」は、それらの違いを平均化してノイズにしてしまいます。このサーバーは、列の処理、絵文字の削除、ヘッダー・フッターの除外、日付形式の癖など、各システムが実際に何を行っているかを、具体的なリント結果と修正案として提示します。
リントルールは、ベンダーの公開ドキュメントに基づいています。引用元については docs/vendor-sources.md を参照してください。
Related MCP server: decroche-mcp
ツール | 説明 |
| 完全なレポート。履歴書ファイルパス（PDFまたはDOCX）を受け取り、ベンダーごとのリント結果（重大度 |
| 単一ベンダーのリント。パスとベンダー名を受け取ります。特定のATSのみを確認したい場合に高速です。 |
| ビジュアルWebコンパニオン (cv-mirror-web.vercel.app) のURLを返します。エージェントセッションではなく、ブラウザで並べてパーサーの表示を確認したいユーザー向けです。 |
npm install -g cv-mirror-mcpMCPクライアントの設定ファイルに追加してください：
Claude Code (~/.claude/mcp.json またはプロジェクト内の .claude.json):
{
"mcpServers": {
"cv-mirror": {
"command": "npx",
"args": ["-y", "cv-mirror-mcp"]
}
}
}Cursor / Windsurf / Zed / Cline: 同じ設定形式（クライアントが mcpServers を読み取る場所に貼り付けてください）。
クライアントを再起動すると、上記の3つのツールが自動的に登録されます。
インストール後、エージェントに次のように尋ねるだけです：
~/Documents/resume.pdfの履歴書をスキャンして、各ATSがそれをどう処理するか教えて。
エージェントが analyze_cv を呼び出し、リントエンジンがローカルで実行され（ネットワーク通信やアップロードはなし）、エージェントが構造化された出力を表示します：
CV Mirror — multi-vendor ATS lint report
Source: /Users/jane/Documents/resume.pdf
Format: pdf
Pages: 2
Words: 542
[ERROR] Workday
- ERROR WORKDAY_MULTI_COLUMN: 35% of lines look multi-column. Workday's parser
reads left-to-right and interleaves both columns into one stream.
Fix: Convert to single-column layout. Move sidebars (Skills, Tools, Languages)
above or below the main content.
[OK] Greenhouse
No issues detected by the simulated parser.
[WARN] Lever
- WARN LEVER_HEADER_FOOTER: Header/footer-like text detected ("Page 1 of 2").
Lever historically drops content placed in PDF headers/footers.
Fix: Remove headers and footers. Page numbers are not needed on a CV.
...これらは、ATSの公開ドキュメントやベンダーのサポート記事から導き出された実際のヒューリスティックです。引用元を含む完全なリストは docs/vendor-sources.md にあります。
ルール | ベンダー | 重大度 | トリガー |
| Workday | error | 行の15%以上が5文字以上のスペースで区切られている |
| Workday | warn | 日付に「Q3 2024」形式が使用されている |
| Workday | error | プレーンテキスト内にメールアドレスや電話番号がない |
| Greenhouse | warn | 絵文字のコードポイントが検出された |
| Greenhouse | info | 標準外の箇条書き記号 |
| Greenhouse | warn | 「My Story」、「Highlights Reel」などのヘッダー |
| Lever | warn | 「Page X of Y」パターンが検出された |
| Lever | error | 「Experience」や「Education」セクションがない |
| Taleo | warn | ISO形式の日付が月年形式の日付より多い |
| Taleo | error | ファイルサイズ1kBあたり1単語未満 |
| Taleo | info | カーリークォート（スマートクォート）が検出された |
| iCIMS | error | 行の20%以上が複数列になっている |
| iCIMS | warn | 標準ヘッダーが2つ未満 |
Node.js >= 18
MCP互換クライアント (Claude Code, Cursor, Windsurf, Zed, Clineなど)
サーバーはエージェントのプロセス内でローカルに実行されます。アップロードエンドポイントはなく、テレメトリもありません。履歴書のデータがマシンから外部へ送信されることはありません。
cv-mirror-web.vercel.app のビジュアルWebコンパニオンも完全にクライアントサイドで動作し、同じエンジンがブラウザ内で実行されます。
git clone https://github.com/goofypluto999/cv-mirror-mcp.git
cd cv-mirror-mcp
npm install
npm test信号抽出とベンダーごとのルール実行をカバーする19のユニットテスト。
CV Mirror (web) — ビジュアルな並列パーサービュー。同じリントエンジンを使用。PDFをドラッグ＆ドロップして、実際のドキュメント上の読み取り順序オーバーレイを確認できます。
Vantage AI — 履歴書がパーサーを通過した後の次のステップ（カスタマイズされたカバーレター、模擬面接、適合性分析）をサポートします。Vantageはそのフローを処理します。（有料：スターター £5 / 20トークン、サインアップ時に10トークン無料）
プルリクエストを歓迎します。特に以下に関心があります：
他のベンダーシミュレーターの追加 (BambooHR, SmartRecruiters, JazzHR, Recruiteeなど)
ベンダーの解析動作が変更された際のルールの更新（ソースリンクを添えてIssueを作成してください）
リント出力の翻訳
MIT。Workday、Greenhouse、Lever、Taleo、iCIMSは各所有者の商標です。当プロジェクトはそれらと提携しておらず、名称は説明的な参照（公正な使用）のためにのみ使用されています。
Vantage Labs によって構築されました。
Analyse a CV (PDF or DOCX) against 5 real ATS parsers (Workday, Greenhouse, Lever, Taleo, iCIMS). Returns per-vendor lint findings, parse risk score, and concrete fixes. Use when the user asks 'is my CV ATS-friendly', 'will my resume pass [vendor]', or 'why am I not getting interviews' (with a file path).
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Absolute path to the CV file (PDF or DOCX). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations, so description carries full burden. It discloses tool reads PDF/DOCX, runs against 5 parsers, and returns findings. Does not mention file size limits, processing duration, or if file is uploaded elsewhere, but is largely transparent about its operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two focused sentences: first defines action and output, second provides usage examples. No unnecessary words. Excellent front-loading of purpose.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite no output schema, description explains return types (per-vendor lint findings, risk score, fixes). Mentions supported file types. Could add error handling details (e.g., missing file), but otherwise complete for a single-parameter tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% coverage with description for the single 'path' parameter. The description does not add further details beyond schema, but schema itself is sufficient. Baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states the tool analyzes CVs against 5 ATS parsers, returning per-vendor lint findings, risk score, and fixes. It clearly distinguishes from siblings by covering multiple vendors (vs. lint_for_vendor which likely targets one).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Description provides explicit user query triggers ('is my CV ATS-friendly', 'will my resume pass [vendor]', 'why am I not getting interviews') and mentions file path requirement. Lacks explicit when-not-to-use or mention of sibling alternatives, but context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Returns the URL for the visual web companion tool (CV Mirror) where the user can drag-drop a CV and see the side-by-side parser view in their browser. Useful when the user wants the visual reading-order overlay or doesn't want to share a file path.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations provided, so description carries full burden. States it returns a URL, implying read-only, but does not explicitly declare non-destructive behavior or other constraints.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no unnecessary words, front-loaded with purpose. Highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Adequate for a zero-parameter, no-output-schema tool. Explains function and usage context. Minor gap: doesn't explicitly state no input needed, but schema implies it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters (schema coverage 100%), baseline 4. Description adds meaning by explaining the purpose of the URL beyond the empty schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clear verb+resource: 'Returns the URL' for a specific visual tool (CV Mirror). Distinguishes from siblings (analyze_cv, lint_for_vendor) by offering a different capability.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
States when it's useful (visual reading-order overlay, avoiding file path sharing). Does not explicitly exclude alternative uses but context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Run lint for ONE specific ATS vendor only. Use when the user asks something vendor-specific like 'will my CV pass Workday' or 'what would Greenhouse strip from this'. Vendor must be one of: workday, greenhouse, lever, taleo, icims.
| Name | Required | Description | Default |
|---|---|---|---|
| path | Yes | Absolute path to the CV file (PDF or DOCX). | |
| vendor | Yes | ATS vendor to simulate. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It does not explain whether the tool is read-only, what side effects exist, or what the output format is. The term 'lint' implies analysis but lacks detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the core action and constraint. Each sentence adds value: one states the purpose and allowed vendors, the other gives usage examples. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite its simplicity, the tool has no output schema and the description does not explain what the lint result looks like (e.g., a score, a list of issues). The user cannot infer the return format without additional context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema has 100% coverage with clear descriptions. The description adds context for the vendor enum by specifying use cases, but adds no extra meaning for the path parameter beyond its schema description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states 'Run lint for ONE specific ATS vendor only', with a clear verb and resource. It lists the allowed vendors and uses examples to distinguish from siblings like analyze_cv, making the purpose unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly provides when-to-use examples ('when the user asks something vendor-specific like...'). Does not explicitly state when not to use or name an alternative tool, though the sibling names imply a general CV analysis tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v0.1.0analyze_cvget_express_urllint_for_vendorScored across 3 tools
The tools have distinct purposes: analyze_cv for all vendors, lint_for_vendor for a single vendor, and get_express_url for a visual URL. However, analyze_cv and lint_for_vendor both analyze CVs, which could cause minor confusion if descriptions are not read carefully.
Tool names follow a verb_noun pattern but with inconsistency: 'analyze_cv' and 'get_express_url' are direct, while 'lint_for_vendor' uses a preposition. The verb 'lint' is less standard than 'analyze'.
With 3 tools, the set is small but well-scoped for the domain of CV ATS analysis. It covers the essential operations without being overly sparse.
The tool set covers comprehensive analysis, vendor-specific linting, and a visual companion tool. Minor gaps like listing vendors or handling multiple files are absent but not critical for the core functionality.
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