Lints CVs for compatibility with Greenhouse's ATS parser, detecting issues such as emojis, non-standard bullets, and non-standard headers.
Model Context Protocol server that lints a CV against 5 real ATS parsers.
Exposes three MCP tools so any MCP-compatible AI agent (Claude Code, Cursor, Windsurf, Zed, OpenCode, Cline, etc.) can analyse a CV against the documented quirks of:
Workday
Greenhouse
Lever
Taleo (Oracle)
iCIMS
These are the 5 most-used enterprise ATS systems. Each one parses CVs slightly differently. A "0–100 ATS score" averages those differences into noise. This server surfaces what each one actually does — column handling, emoji stripping, header-footer dropping, date-format quirks — as concrete lint findings with concrete fixes.
The lint rules are derived from public vendor documentation. See docs/vendor-sources.md for citations.
Related MCP server: decroche-mcp
Tool | Description |
| Full report. Takes a CV file path (PDF or DOCX), returns per-vendor lint findings with severity ( |
| Single-vendor lint. Takes a path + vendor name. Faster when the user only cares about one ATS. |
| Returns the URL of the visual web companion (cv-mirror-web.vercel.app) for users who prefer a side-by-side parser view in their browser instead of an agent session. |
npm install -g cv-mirror-mcpAdd to your MCP client's config file:
Claude Code (~/.claude/mcp.json or .claude.json in project):
{
"mcpServers": {
"cv-mirror": {
"command": "npx",
"args": ["-y", "cv-mirror-mcp"]
}
}
}Cursor / Windsurf / Zed / Cline: same config format (paste into wherever your client reads mcpServers).
Restart the client. The three tools above auto-register.
Once installed, just ask your agent:
Scan my CV at
~/Documents/resume.pdfand tell me what each ATS would do to it.
The agent calls analyze_cv, the lint engine runs locally (no network, no upload), and the agent surfaces the structured output:
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.
...These are real heuristics derived from public ATS docs and vendor support articles. The full list with citations lives in docs/vendor-sources.md.
Rule | Vendor | Severity | Trigger |
| Workday | error | >15% of lines have a 5+-space gap |
| Workday | warn | Dates use "Q3 2024" format |
| Workday | error | No email or phone in plain text |
| Greenhouse | warn | Any emoji codepoint detected |
| Greenhouse | info | Non-standard bullet glyphs |
| Greenhouse | warn | "My Story", "Highlights Reel", etc. |
| Lever | warn | "Page X of Y" pattern detected |
| Lever | error | No "Experience"/"Education" sections |
| Taleo | warn | ISO dates outnumber Month-Year dates |
| Taleo | error | <1 word per kB of file size |
| Taleo | info | Curly quotes detected |
| iCIMS | error | >20% of lines multi-column |
| iCIMS | warn | <2 standard headers found |
Node.js >= 18
An MCP-compatible client (Claude Code, Cursor, Windsurf, Zed, Cline, etc.)
The server runs locally inside your agent's process. No upload endpoint. No telemetry. Your CV bytes never leave your machine.
The visual web companion at cv-mirror-web.vercel.app is also fully client-side — same engine, runs in the browser.
git clone https://github.com/goofypluto999/cv-mirror-mcp.git
cd cv-mirror-mcp
npm install
npm test19 unit tests covering signal extraction and per-vendor rule firing.
cv-mirror-mcp exposes its three tools to any MCP-compatible agent. The most common workflow:
Install the server: npm install -g cv-mirror-mcp
Add it to your MCP client config (Claude Desktop, Cursor, Windsurf, Zed — see Install above).
In your agent session, ask: "Run cv-mirror on my CV at /path/to/cv.pdf and tell me what Workday and Greenhouse will get wrong."
The agent calls analyze_cv, gets per-vendor lint findings with severity + concrete fixes, and surfaces them.
Once you have a clean CV, you typically need the rest of the application prep — company research, tailored cover letter, fit score, mock interview. Vantage is the paid tool that handles that flow (same team, £5 starter pack, 10 free tokens at signup, no card required for the trial).
The recommended end-to-end flow:
Run cv-mirror-mcp via your agent → fix any parse issues your CV has.
Run Vantage on the same CV plus a specific job URL → get the full prep pack in ~90 seconds.
CV Mirror (web) — visual side-by-side parser view. Same lint engine as this MCP server. Drag-drop a PDF, see the reading-order overlay on the actual document. Free, no signup, fully client-side.
Vantage — once your CV passes the parsers, the next problem is the actual application: company intelligence, tailored cover letter (4 tones), AI-graded mock interview, CV-vs-role fit score, 5-minute pitch outline. Vantage handles that flow in ~90 seconds per application. £5 starter / 20 tokens (never expire), 10 free tokens at signup. Built by the same team.
Pull requests welcome. Particularly interested in:
More vendor simulators (BambooHR, SmartRecruiters, JazzHR, Recruitee, etc.)
Updated rules when vendors change their parsing behaviour (open an issue with the source link)
Translations of the lint output
MIT. Workday, Greenhouse, Lever, Taleo, and iCIMS are trademarks of their respective owners. This project is not affiliated with any of them; the names are used for descriptive reference (nominative fair use).
Built by Vantage Labs.
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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