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Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault

No arguments

Capabilities

Features and capabilities supported by this server

CapabilityDetails
tools
{
  "listChanged": false
}
prompts
{
  "listChanged": false
}
resources
{
  "subscribe": false,
  "listChanged": false
}
experimental
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
get_manifestA

Return the full Logic Lab art algorithm manifest as a JSON object.

The manifest contains an 'entries' array. Each entry includes:
- path (str): manifest-relative path to the source file (e.g. 'physics/wave/wave.py')
- title (str): human-readable algorithm name
- category (str): domain (physics, steering_behaviors, genetic_algorithms,
  neuro_evolution, fractals, cellular_automata, mathematical, tiling_patterns,
  research, simulation, shader)
- concepts (list[str]): key algorithmic concepts demonstrated
- visual_use (str): one-line description of the visual output
- good_for (list[str]): suggested use-cases and aesthetic tags
- complexity (str): 'low', 'medium', or 'high'
- dependencies (list[str]): required Python packages beyond py5

This tool is read-only and returns cached data for the current session.
Prefer search_algorithms for filtered discovery. Use get_manifest when you
need the full entry list or want to enumerate all available categories.
search_algorithmsA

Search the Logic Lab manifest for algorithms by keyword, category, or visual intent.

Returns a list of manifest entries sorted by relevance score. Each entry includes
path, title, category, concepts, visual_use, good_for, complexity, and dependencies.
Returns an empty list when no entries match — this is not an error.

This tool returns manifest metadata only; it never reads source files.
Synonym expansion is applied automatically so queries like 'flow' also match
'fluid' and 'stream'. Combining query with category narrows results to a
specific domain.

Recommended workflow: call this tool for discovery, then get_algorithm_summary
for short context on candidates, then get_algorithm only for paths you intend
to use.
get_algorithmA

Return the source text of a Logic Lab .py file or README.md.

This tool is read-only: it reads only .py files and README.md files within
the repository boundary. File creation, editing, deletion, and shell execution
are not available through this server.

Returns a dict with:
- path (str): normalized manifest-relative path
- content (str): file text, possibly truncated
- truncated (bool): true when the file exceeded max_chars
- notice (str | null): truncation message with the current limit and maximum,
  or null when content was not truncated

Raises AccessError when the path escapes the repository root, points to a
non-existent file, or refers to a disallowed file type (not .py or README.md).

Call get_algorithm_summary first to confirm relevance before fetching full
source. Call search_algorithms or get_manifest to discover valid paths.
get_algorithm_summaryA

Return a short summary of a Logic Lab algorithm without fetching full source.

For paths in the manifest, returns all metadata fields:
- path, title, category, concepts, visual_use, good_for, complexity, dependencies
- readme_excerpt: first ~6 non-empty lines of the nearest README.md (up to 1200
  chars) when a README.md exists in the same directory

For paths not in the manifest, returns a minimal summary derived from the file
path (title inferred from directory name, category from the first path segment)
plus readme_excerpt when available.

This tool never returns source code — call get_algorithm for that. Use this
tool to assess relevance before committing to a full source fetch. It is
cheaper in context than get_algorithm for files you may not end up using.
search_by_moodA

Search algorithms by creative mood or visual atmosphere.

Returns a dict with:
- mood (str): the normalized mood used for the query
- style (str | null): the style refinement if provided
- profile_summary (dict): the mood's associated categories and key concepts
- results (list): ranked manifest entries matching the mood

Each mood maps to a curated set of algorithm categories, concepts, and good_for
tags. The style parameter re-ranks results by matching its tokens against all
metadata fields. When the mood is unrecognized, returns an error dict containing
'error', 'available_moods', and a 'tip'.

Prefer search_algorithms for free-text queries without a clear aesthetic direction.
Use this tool when you have a specific visual mood in mind (e.g. 'cosmic',
'minimal', 'chaotic').

Available moods: ethereal, chaotic, geometric, organic, cosmic, minimal,
generative, retro, crystalline, topological, networked, geological.
recommend_combinationsA

Suggest multi-layer algorithm combinations for a given artistic intent.

Returns a dict with:
- intent (str): the original intent string
- combinations (list): ranked list of layered recipes
- tip (str): guidance for following up on returned paths

Each combination includes:
- name (str): recipe name
- description (str): recipe description
- moods (list[str]): associated creative moods
- layers (list): each layer has role (str), query (str), and suggestions
  (list of manifest entries resolved by search_algorithms)

Layer roles describe compositional function (e.g. background, agents, texture,
overlay). Suggestions are live manifest entries — use get_algorithm_summary or
get_algorithm on any suggested path for full details.

Use this tool to plan layered generative artworks from a text description.
It combines curated recipes with dynamic algorithm lookup per layer.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription
logic_lab_manifestCurated manifest of Logic Lab algorithms for search and artwork planning.
logic_lab_manifest_summarySmall summary of manifest size, categories, and recommended MCP usage.
logic_lab_readmeTop-level README for Logic Lab (falls back to MCP README when installed standalone).
logic_lab_mcp_readmeMCP server usage, tools, security notes, and manifest update workflow.

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