# Coverlttr

> Coverlttr is a cover-letter application workflow. It turns an uploaded CV and job description into a tailored, persuasive case for the candidate's fit.

A cover letter should make a case, not repeat a résumé. Coverlttr helps active job seekers produce role-specific, defensible applications at sustainable effort—without resorting to generic AI output or manual drafting from scratch.

## Core Capabilities

- **Evidence-Grounded Drafting**: Connects the applicant's real experience from uploaded CVs to the employer's stated job requirements and terminology.
- **Candidate Control & Iteration**: Plain editable text. Applicants can edit drafts directly or regenerate with targeted feedback (e.g., tighten length, emphasize leadership) at discounted credit costs.
- **Reusable Context**: Store multiple CVs, personal contact details, and writing preferences for reuse across multiple job applications.
- **Professional Templates & Multi-Format Export**: Choose from 8 curated layout templates (including Modern Professional, Executive Suite, Tech Innovator, Fresh Graduate, and Academic Research) and export to PDF, Word (.docx), Markdown (.md), Plain Text (.txt), LaTeX source (.tex), or PNG image.
- **LinkedIn Job Capture**: Chrome extension saves LinkedIn job listings directly to Coverlttr while browsing.
- **Model Context Protocol (MCP)**: Native MCP integration lets developers and power users create and manage letters directly within AI tools such as Cursor, Claude Desktop, ChatGPT, Windsurf, Claude Code, and Gemini.

## Model Context Protocol (MCP) Integration

Coverlttr provides a native **Model Context Protocol (MCP)** server that connects your AI assistants, coding IDEs, and LLM workflows directly to your Coverlttr account over secure OAuth.

Instead of switching tabs, copying job descriptions, and manually pasting resumes into prompt windows, you can draft, iterate, and export cover letters directly inside your preferred AI environment:
- **Direct CV & Context Access**: Your AI assistant can inspect your uploaded CVs and profile details to ground letters in verifiable career evidence.
- **Credit-Aware Operations**: Query available credits and preview cost estimations before triggering generations.
- **In-Chat Letter Generation & Iteration**: Draft tailored cover letters, refine drafts with specific feedback, and apply layout templates without leaving your editor.
- **Instant Export**: Export directly to PDF, Word (.docx), Markdown (.md), Plain Text (.txt), LaTeX (.tex), or PNG.

### Install the Coverlttr MCP Server

Connect Coverlttr to your AI client in seconds:
Find step-by-step instructions, one-click deep links, JSON configurations, and CLI commands for every platform, at [Coverlttr MCP Setup & Installation](https://www.coverlttr.com/mcp.md).

## How It Works

1. **Upload Experience**: Upload one or more CVs. Contact details and preferences are preserved for future letters.
2. **Specify the Role**: Provide the job title, company, and job description (or import via the Chrome extension).
3. **Configure Parameters**: Choose tone, length, language, target job market, and key points to emphasize. The credit cost is displayed before generation.
4. **Generate & Refine**: Coverlttr identifies matching qualifications and generates an editable draft highlighting stated keywords. Revise manually or regenerate with specific feedback.
5. **Format & Export**: Apply a design template and download the finalized document in the required file format.

## Credits & Pricing

Coverlttr uses a transparent credit model:
- New accounts receive a complimentary starting credit balance.
- Letter generation costs credits based on context size and selected options.
- Iterative regenerations, template applications, and document exports use fewer credits.
- Additional credits can be purchased as one-off credit packs or through monthly, quarterly, or yearly subscriptions (Starter, Pro, Agency).
- Subscription credit allotments: Starter 100 credits/month, Pro 250 credits/month, Agency 500 credits/month.
- Plan and credit details: [Coverlttr Pricing](https://www.coverlttr.com/pricing.md).

## LLM Resources & Documentation

Explore dedicated agent endpoints and structured references:

- [Coverlttr MCP Integration & Setup](https://www.coverlttr.com/mcp.md): Complete setup guides, deep links, CLI commands, and config JSON for Claude, ChatGPT, Cursor, Claude Code, Gemini, and Windsurf.
- [Coverlttr FAQ](https://www.coverlttr.com/faq.md): Complete answers to frequently asked questions regarding features, credits, privacy, ATS alignment, and MCP setup.
- [Coverlttr Pricing](https://www.coverlttr.com/pricing.md): Plans, per-month prices, credits granted per billing period, credit-pack prices, and how credits are spent on generation.
- [Coverlttr vs Claude](https://www.coverlttr.com/vs/claude/llms.txt): Feature-by-feature comparison between Coverlttr's tailored workflow and general-purpose Claude drafting.
- [Coverlttr vs ChatGPT](https://www.coverlttr.com/vs/chatgpt/llms.txt): Feature-by-feature comparison between Coverlttr's grounded workflow and ChatGPT prompting.
- [Coverlttr vs Gemini](https://www.coverlttr.com/vs/gemini/llms.txt): Feature-by-feature comparison between Coverlttr's application positioning tool and Google Gemini.