StoryLenses MCP Server
StoryLenses MCP Server
AI-powered cover letter generation for MCP-compatible agents. The first production MCP server for job applications.
Tools
Tool | Description |
| Extract 15+ structured fields from a job posting |
| Match a candidate CV against job data |
| Generate a story-driven cover letter |
| Score and evaluate a cover letter |
| List available narrative archetypes and tones |
Related MCP server: laddro-career-mcp
Setup
Claude Desktop
Add to ~/Library/Application Support/Claude/claude_desktop_config.json:
{
"mcpServers": {
"storylenses": {
"command": "npx",
"args": ["-y", "@storylenses/mcp-server"],
"env": {
"STORYLENSES_API_KEY": "your-api-key"
}
}
}
}Cursor / VS Code
Add to .cursor/mcp.json or VS Code MCP settings:
{
"mcp": {
"servers": {
"storylenses": {
"command": "npx",
"args": ["-y", "@storylenses/mcp-server"],
"env": {
"STORYLENSES_API_KEY": "your-api-key"
}
}
}
}
}Docker
docker run -e STORYLENSES_API_KEY=your-key ghcr.io/benediktgirz/storylenses-mcp-serverEnvironment Variables
Variable | Required | Description |
| Yes | Your API key from storylenses.app/mcp |
| No | API base URL (default: https://www.storylenses.app) |
Example Workflow
// 1. Analyze job posting
const job = await callTool("storylenses_analyze_job", {
job_url: "https://linkedin.com/jobs/view/12345"
});
// 2. Match candidate profile
const match = await callTool("storylenses_match_profile", {
job_analysis: job,
candidate_cv: "Senior engineer with 7 years React experience..."
});
// 3. Generate cover letter
const letter = await callTool("storylenses_generate_letter", {
job_analysis: job,
match_data: match,
candidate_name: "Alex Chen",
archetype: match.suggestedArchetype
});
// 4. Quality check
const score = await callTool("storylenses_quality_check", {
letter_text: letter.letter_text,
job_analysis: job
});Testing
npm install
STORYLENSES_API_KEY=your-key npm testGet an API Key
Visit storylenses.app/mcp to get your API key.
Free: 10 generations/month
Developer ($29/mo): 200 generations
Scale ($99/mo): 1,000 generations
License
MIT
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
5 tool updates
v0.1.0- First observed
storylenses_analyze_job - First observed
storylenses_generate_letter - First observed
storylenses_list_archetypes - First observed
storylenses_match_profile - First observed
storylenses_quality_check
TDQS
Scored across 5 tools
Each tool occupies a distinct stage in the workflow pipeline: analyze_job extracts job data, match_profile compares candidate to job, list_archetypes provides style options, generate_letter creates output, and quality_check validates results. No functional overlap exists between tools.
All tools follow an identical storylenses_verb_noun pattern with consistent snake_case formatting, clear action-oriented verbs (analyze, generate, list, match, check), and uniform prefixing that prevents collisions with other servers.
Five tools is ideally suited for this focused domain, covering the complete cover letter lifecycle from input analysis and matching through generation and validation without bloat, redundancies, or missing critical steps.
Provides comprehensive coverage of the generation workflow including analysis, matching, archetype selection, creation, and scoring; minor gap requires regenerating from scratch rather than refining existing letters based on quality feedback.
Maintenance
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