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Glama
benediktgirz

StoryLenses MCP Server

by benediktgirz

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
STORYLENSES_API_KEYYesYour API key from storylenses.app/mcp
STORYLENSES_API_URLNoAPI base URLhttps://www.storylenses.app

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

Server capabilities have not been inspected yet.

Tools

Functions exposed to the LLM to take actions

NameDescription

No tools

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

TDQS

A3.8/5.0

Scored across 5 tools

Disambiguation5/5

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.

Naming Consistency5/5

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.

Tool Count5/5

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.

Completeness4/5

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.