# io.github.benediktgirz/storylenses (npm · @storylenses/mcp-server)

AI cover letter generation for agents. Job analysis, profile matching, narrative letters.

- Trust score: 67/100 (medium)
- Change this week: +21
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-08-03

## Components

- remote · `www.storylenses.app`: 71/100, [markdown](https://verifymcp.io/servers/benediktgirz-storylenses/api-mcp-endpoint.md), [page](https://verifymcp.io/servers/benediktgirz-storylenses/api-mcp-endpoint)
- npm · `@storylenses/mcp-server`: 67/100 (this document), [markdown](https://verifymcp.io/servers/benediktgirz-storylenses/storylenses-mcp-server.md), [page](https://verifymcp.io/servers/benediktgirz-storylenses/storylenses-mcp-server)

## Channel facts

- Registry: `npm`
- Package: `@storylenses/mcp-server`
- Version: `0.1.3`
- Transport: `stdio`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-08-03.

- **Supply Chain Security**: 87/100
  - No malware found by supply-chain analysis.
  - Only part of the dependency tree could be resolved (95 of 99), so this covers what we could see, not the whole tree.
  - No install/post-install scripts declared.
  - Only part of the dependency tree could be resolved (95 of 99), so this covers what we could see, not the whole tree.
- **Provenance & Transparency**: 45/100
  - Source repository is publicly reachable at the declared URL.
  - Provenance check failed: no build-provenance attestation is published.
  - Clear OSI-approved license (MIT).
  - Actively maintained (last published 117 days ago).
  - Disclosure check failed: no security disclosure policy was found in the source repository.
- **Schema Quality & AI Usability**: 66/100
  - AI-judged instruction clarity (good).
  - Tool/resource definitions use about 424 tokens (~84/item across 5 items; 5 tools + 0 resources), lean.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 27/100
  - Stability observed for 8 of 30 days with no destabilising changes; credit accrues until the full window elapses.
- **Tool Coverage**: 100/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 100% of tool parameters carry a description.
- **Capabilities**: 100/100
  - Implements a supported MCP spec version (2025-11-25); the latest is 2026-07-28.

## Install

### Claude

```bash
claude mcp add benediktgirz-storylenses -- npx -y @storylenses/mcp-server
```

### Codex

```bash
codex mcp add benediktgirz-storylenses -- npx -y @storylenses/mcp-server
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "benediktgirz-storylenses": {
      "type": "local",
      "command": [
        "npx",
        "-y",
        "@storylenses/mcp-server"
      ],
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add benediktgirz-storylenses --command npx --arg -y --arg @storylenses/mcp-server
```

### Hermes

```yaml
mcp_servers:
  benediktgirz-storylenses:
    command: "npx"
    args: ["-y", "@storylenses/mcp-server"]
```

### Other

```json
{
  "mcpServers": {
    "benediktgirz-storylenses": {
      "command": "npx",
      "args": [
        "-y",
        "@storylenses/mcp-server"
      ]
    }
  }
}
```

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-08-02 (score 67, +46)

- [security regression] Provenance: unverified → fail
- [security improvement] Install scripts: unverified → pass
- [security improvement] Known CVEs: unverified → partial
- [security improvement] Malware scan: unverified → pass
- [security] Stability: Stability not yet verified: not enough scan history yet (needs a 30-day window).
- [functional improvement] Stability: unverified → 0.23
- [functional improvement] Schema quality: unverified → good
- [functional improvement] MCP protocol: unverified → pass
- [functional improvement] Maintenance: unverified → pass
- [functional improvement] Dependency health: unverified → partial
- [functional improvement] License: unverified → pass
- [functional] Licence: MIT

### 2026-07-31 (score 21, −25)

- [functional] We updated how we score, so this day's move reflects our rubric, not a change to the server

### 2026-07-27 (score 46)

First indexed and scored.

## MCP tools (5)

### `storylenses_analyze_job` (~78 tokens)

Extract 15+ structured fields from a job posting — role requirements, company challenges, culture signals, recruiter priorities

Input parameters:

- `job_text` (string): Raw text of the job posting (use if no URL)
- `job_url` (string): URL of the job posting to analyze
- `locale` (string): Response language

### `storylenses_match_profile` (~78 tokens)

Match a candidate profile/CV against job data — identifies fit score, matching skills, career gaps, and strongest narrative angle

Input parameters:

- `candidate_cv` (string, required): Candidate's CV or resume as text
- `job_analysis` (object, required): Job analysis output from storylenses_analyze_job
- `locale` (string): Response language

### `storylenses_generate_letter` (~148 tokens)

Generate a story-driven cover letter using matched data and a narrative archetype. Supports en/de/es/pt.

Input parameters:

- `archetype` (string): Narrative archetype ID (use storylenses_list_archetypes to see options)
- `candidate_name` (string, required): Candidate's full name
- `job_analysis` (object, required): Job analysis from storylenses_analyze_job
- `length` (string): Letter length: short (150-200 words), medium (250-350), full (400-500)
- `locale` (string): Output language
- `match_data` (object, required): Match data from storylenses_match_profile
- `tone` (string): Writing tone

### `storylenses_quality_check` (~81 tokens)

Score and evaluate a cover letter for relevance, narrative strength, and completeness. Returns score 0-100 with actionable feedback.

Input parameters:

- `job_analysis` (object, required): Job analysis from storylenses_analyze_job
- `letter_text` (string, required): The cover letter text to evaluate (min 200 characters)
- `locale` (string): Feedback language

### `storylenses_list_archetypes` (~39 tokens)

Return available narrative archetypes with descriptions so the agent or user can select a style

Input parameters:

- `locale` (string): Description language

## Diagnostics

Captured diagnostic sections: Provenance, Dependencies. The full working is on the page: https://verifymcp.io/servers/benediktgirz-storylenses/storylenses-mcp-server#diagnostics

## Score history

- 2026-08-03: 67
- 2026-08-02: 67
- 2026-08-01: 21
- 2026-07-31: 21
- 2026-07-30: 46
- 2026-07-28: 46
- 2026-07-27: 46

## Links

- npm package: https://www.npmjs.com/package/@storylenses/mcp-server
- Socket report: https://socket.dev/npm/package/@storylenses/mcp-server
- Repository: https://github.com/benediktgirz/storylenses-mcp-server
- Changelog RSS feed: https://verifymcp.io/servers/benediktgirz-storylenses/storylenses-mcp-server/changelog.xml
- Changelog JSON feed: https://verifymcp.io/servers/benediktgirz-storylenses/storylenses-mcp-server/changelog.json
- HTML version of this page: https://verifymcp.io/servers/benediktgirz-storylenses/storylenses-mcp-server