About
The NovaCV MCP Server bridges the Model Context Protocol with NovaCV’s resume services, enabling clients to generate PDF resumes, retrieve templates, convert text to JSON Resume format, and analyze resume content—all through simple command-line or environment configurations.
Capabilities
Lightbaby MCP Server for NovaCV
The Lightbaby MCP Server for NovaCV bridges the gap between AI assistants and the NovaCV resume‑building platform. By exposing a set of well‑defined tools over the Model Context Protocol, it lets developers and AI agents transform raw résumé text into polished PDFs, retrieve template catalogs, convert to the JSON Resume standard, and perform deep content analysis—all without writing any custom integration code.
Problem Solved
Creating professional résumé documents typically requires manual formatting, template selection, and keyword optimization. Developers building AI‑powered career advisors or onboarding bots often need to offer users a seamless way to generate, evaluate, and refine résumés. The server solves this by providing an API‑style interface that encapsulates NovaCV’s capabilities behind a lightweight, reproducible MCP service. This eliminates the need for each client to handle authentication, request orchestration, or error handling.
Core Functionality
- Generate PDF Résumés – Convert plain text into a polished PDF using any of NovaCV’s pre‑designed templates. The tool automatically applies layout, styling, and page breaks.
- Template Discovery – Retrieve a list of all available résumé templates, complete with IDs, names, and thumbnail previews. Clients can present these options to users for easy selection.
- Text‑to‑JSON Resume – Parse unstructured résumé text and output a structured JSON object that conforms to the widely adopted JSON Resume schema, enabling further automation or data ingestion.
- Résumé Analysis – Perform content analysis on raw résumé text, evaluating completeness, keyword density, skill alignment, and providing actionable improvement suggestions.
These capabilities are exposed as distinct MCP tools (, , , and ), each with clear input requirements and predictable outputs.
Use Cases
- Career Coaching Bots – An AI assistant can ask a user for their résumé text, automatically generate a PDF, and provide feedback on keyword usage or missing sections.
- Onboarding Pipelines – Human resources systems can ingest new hires’ résumé text, convert it to JSON for database storage, and generate branded PDFs for record‑keeping.
- Template Libraries – Design teams can expose NovaCV’s template catalog to internal tools, allowing employees to pick a style before content entry.
- Resume‑Quality Audits – HR analytics platforms can batch‑process résumé texts, score them, and surface improvement recommendations for recruiters.
Integration with AI Workflows
Developers configure the server in their MCP‑enabled clients (e.g., Cursor, Cherry Studio) by specifying a command and environment variables for the NovaCV API key. Once registered, an AI assistant can invoke any of the tools through simple command names (, etc.), receiving structured JSON responses that can be parsed, displayed, or fed into downstream processes. Because the server handles authentication and rate limiting internally, AI agents can focus on conversational logic rather than API plumbing.
Unique Advantages
- Zero‑Code Integration – No need to write HTTP wrappers; the MCP server already translates tool calls into NovaCV API requests.
- Security‑First Design – API keys are passed via environment variables or CLI options, keeping credentials out of source code.
- Extensibility – The server’s modular tool set can be expanded to include additional NovaCV features or custom logic without changing client code.
- Developer Friendly – Built with lightweight tooling (, ) and supported by debugging utilities like MCP Inspector, making it straightforward to develop, test, and deploy.
By consolidating NovaCV’s résumé generation and analysis features behind a standardized MCP interface, the Lightbaby server empowers AI assistants to deliver polished, data‑driven résumé experiences with minimal effort.
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