cv-forge-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| cv_forge_setupA | Set up CV Forge backend. MUST be called before generate_pdf or generate_docx. Detects the environment and lets the user choose how to run CV Forge:
If mode is "auto", present the user with the available options and ask which they prefer. If only one option is available, use it automatically. Args: mode: "local", "remote", or "auto" (default). |
| generate_cvA | Return an empty CV JSON template for the AI to fill in. IMPORTANT: Before calling this tool, gather the user's information first. Ask the user about each section they want to include:
Do NOT generate a CV with placeholder or empty fields. Ask follow-up questions for any missing critical sections (at minimum: personal info, experience, education, skills). IMPORTANT: Always fill in URLs for employers, education institutions, and certification issuers. Use their official website URLs (e.g. url: "https://www.google.com" for Google, issuer_url: "https://www.offensive-security.com" for OffSec). The editor uses these URLs to automatically fetch company/institution logos. Template field reference:
Args: language: CV language for section headers — en, pl, de, fr, or es. |
| generate_pdfA | Generate an ATS-optimized PDF and provide a link to the visual editor. Takes a complete CV JSON object (same structure as generate_cv template). All required fields (personal, experience, education, skills) must be filled in. Returns:
The ATS PDF is a clean, text-based document optimized for applicant tracking systems. For a visually styled PDF with colors, logos, and layout — direct the user to open the editor_url in their browser and click "Download Pretty PDF" there. Args: cv_data: Complete CV data dictionary with all sections filled in. |
| generate_docxA | Generate an ATS-optimized DOCX from CV data. Takes a complete CV JSON object (same structure as generate_cv template). All required fields (personal, experience, education, skills) must be filled in. Returns:
Args: cv_data: Complete CV data dictionary with all sections filled in. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 4 tools
Each tool has a distinct, non-overlapping purpose: setup initializes the backend, generate_cv creates a template, generate_docx produces a DOCX file, and generate_pdf produces a PDF file. The descriptions clearly differentiate their roles in the CV creation workflow, with no ambiguity about which tool to use for each step.
All tool names follow a consistent verb_noun pattern with snake_case: cv_forge_setup, generate_cv, generate_docx, and generate_pdf. The naming is predictable and readable, making it easy for an agent to understand the action each tool performs based on its name alone.
With 4 tools, this server is well-scoped for its purpose of CV generation and formatting. Each tool earns its place by covering essential steps: setup, template creation, and output generation in two common formats. The count is neither too thin nor excessive for the domain.
The tool set covers the core CV creation workflow from setup to final output, with no obvious dead ends. A minor gap exists in the lack of tools for updating or deleting CV data, but agents can work around this by regenerating from scratch, and the domain focus on generation rather than management makes this acceptable.