Author Style "-esque" MCP Server

Author Style "-esque" MCP Server

Provides a catalog of curated author writing styles and tools to blend or analyze them across eight dimensions for text and image prompt generation. It enables users to apply structured literary patterns through deterministic style modeling and coordinate-based interpolation.

Category
Visit Server

README

Author Style "-esque" MCP Server

A curated catalog of 11 author writing styles decomposed into 8 orthogonal dimensions, with dual-output paths for text generation and image generation. Each style is an independent "stompbox" that colors prompts with structural writing patterns — not copied text.

Architecture

Layer 1: Taxonomy (0 tokens)     → author_style_taxonomy.py
Layer 2: Deterministic (0 tokens) → author_style_operations.py
Layer 3: Creative synthesis       → Consumer LLM responsibility
Server:  FastMCP interface        → author_style_mcp.py

Layer 1 holds the pure data — 11 author coordinates in 8D style-space, dimension specifications, and output vocabulary mappings. Layer 2 performs all deterministic operations: distance computation, weighted interpolation (blending), vocabulary extraction, and prompt generation. No LLM calls at any point. Layer 3 is left to the consuming application — a single Claude or other LLM call that uses the structured directives as creative input.

The Catalog

ID Style Origin Signature
hemingway Hemingway-esque English (American) Iceberg theory, paratactic flatness, submerged tension
de_sade Marquis de Sade-esque French Baroque nesting, exhaustive enumeration, philosophical excess
le_guin Ursula K. Le Guin-esque English (American) Balanced cadence, anthropological worldbuilding, warm precision
didion Joan Didion-esque English (American) Clinical observation, specific sensory detail, retrospective present
lovecraft Lovecraft-esque English (American) Accumulative horror, archaic register, cosmic scale
borges Borges-esque Spanish (Argentine) Labyrinthine logic, infinite recursion, philosophical miniatures
murakami Murakami-esque Japanese Flat affect, mundane surrealism, domestic loneliness
marquez Márquez-esque Spanish (Colombian) Magical realism, multigenerational fate, tropical profusion
kafka Kafka-esque German (Czech) Bureaucratic absurdism, plain surface over impossible premise
shonagon Sei Shōnagon-esque Japanese (Classical) List-form observation, radical sensory specificity, aesthetic judgment
lispector Clarice Lispector-esque Brazilian Portuguese Interior stream, philosophical viscerality, self-examining language

The 8 Dimensions

All values normalized [0.0, 1.0].

Dimension Low End High End Text Output Image Output
Syntactic Density Paratactic / flat Hypotactic / nested Sentence length, clause depth Compositional layering depth
Sensory Concreteness Abstract / conceptual Concrete / sensory Noun register, verb type Material rendering specificity
Ornamental Register Stripped / minimal Lush / baroque Adjective density, figurative language Surface detail complexity
Tension Visibility Submerged / iceberg Externalized / explicit Show vs. tell ratio Lighting drama, contrast ratio
Tension Temporality Ruptural / episodic Accumulative / inevitable Pacing, foreshadowing density Temporal framing, motion state
Reality Stability Unstable / paradoxical Stable / verifiable Epistemic mode, hedging language Spatial logic, physics accuracy
Interiority Exterior / behavioral Interior / consciousness POV mode, thought access Framing distance, depth of field
Temporal Mode Eternal present / episodic Cyclical / exhaustive Tense, temporal scope Motion blur, temporal compositing

Tools

Layer 1 — Taxonomy Lookup (0 tokens)

  • get_author_styles() — List all 11 authors with coordinates
  • get_author_style_profile(author_id) — Complete profile: coordinates, signature moves, text/image vocabulary
  • get_style_dimensions() — All 8 dimensions with low/mid/high output mappings
  • get_parameter_names() — Ordered parameter list for dynamics integration

Layer 2 — Deterministic Operations (0 tokens)

  • compute_author_distance(author_id_1, author_id_2) — Euclidean distance with per-dimension breakdown
  • blend_author_styles(blend_spec_json) — Weighted interpolation of multiple styles
  • generate_text_style_prompt(author_id | blend_spec_json | custom_coordinates_json) — Text-generation directives
  • generate_image_style_prompt(author_id | blend_spec_json | custom_coordinates_json, style_modifier) — Image-generation visual vocabulary
  • find_style_extremes() — Maximum-contrast pair across catalog
  • find_nearest_style(author_id) — Closest neighbor in style-space

Usage Examples

Single style — text prompt

generate_text_style_prompt(author_id="kafka")

Returns structured directives: sentence architecture, vocabulary constraints, forbidden words, paragraph rhythm, and a composited master prompt string.

Single style — image prompt

generate_image_style_prompt(author_id="marquez", style_modifier="photorealistic")

Returns keywords, color palette, compositional rules, and per-dimension visual directives suitable for ComfyUI / Stable Diffusion / DALL-E.

Blended style

blend_author_styles('{"hemingway": 0.6, "borges": 0.3, "shonagon": 0.1}')

Interpolates in 8D style-space. Returns blended coordinates, nearest catalog author (Didion, distance 0.406), merged signature moves, and extracted text/image vocabularies for the blend point.

Distance analysis

compute_author_distance("hemingway", "lovecraft")

Returns Euclidean distance (1.863), per-dimension breakdown, and identifies the maximum-contrast axis (ornamental_register, gap 0.80).

Dynamics Integration

Coordinates are directly compatible with aesthetics-dynamics-core tools:

# Get Hemingway coordinates
coords = get_coordinates("hemingway")
# → {"syntactic_density": 0.10, "sensory_concreteness": 0.90, ...}

# Use with integrate_trajectory for smooth style morphing
integrate_trajectory(
    start_state=get_coordinates("hemingway"),
    target_state=get_coordinates("lovecraft"),
    parameter_names=PARAMETER_NAMES,
    num_steps=30
)

Also composable with catastrophe-morph and surface-design-aesthetics servers — stack an author style brick with a catastrophe type or surface treatment for cross-domain aesthetic composition.

Composition Example: The Stompbox Chain

User prompt
  → Hemingway-esque (text structure: terse, concrete, submerged)
  → Catastrophe Morph: cusp (visual geometry: sharp vertices, crystalline)
  → Surface Design: matte_ceramic (material: chalky, light-absorbing)
  → Final synthesis (single LLM call)

Each brick is independent, deterministic, and zero-cost. Creative synthesis happens once at the end.

Deployment

FastMCP Cloud entry point:

author_style_mcp.py:mcp

Local execution:

python author_style_mcp.py

File Structure

author_style_taxonomy.py    # Layer 1: Types, dimensions, author catalog
author_style_operations.py  # Layer 2: Distance, blend, prompt generation
author_style_mcp.py         # FastMCP server with tool decorators
pyproject.toml              # Package configuration
README.md                   # This file

Style-Space Topology Notes

From validation testing:

  • Maximum contrast pair: Hemingway ↔ Lovecraft (1.863) — wider than Hemingway ↔ de Sade (1.792) due to Lovecraft's combined extremes on ornament, reality stability, and interiority
  • Surprising neighbors: Kafka ↔ Le Guin (0.636) — structurally closer than their reputations suggest, sharing balanced syntactic density and mid-range tension handling
  • Emergent blends: 60/30/10 Hemingway/Borges/Shōnagon lands in Didion's neighborhood — concreteness + interiority + sensory precision ≈ cool clinical observation
  • Unique coordinate: Sei Shōnagon occupies a region no other author approaches — low density + extreme concreteness + episodic temporality + high interiority is a combination absent from the Western literary tradition

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured