LLM Tools

Give any LLM access to micro-tools through MCP servers — each powered by a specialized AI generation pipeline for a domain language.

Overview

Every Graffiticode micro-tool is an MCP server. Any agent that speaks MCP can connect, describe what it wants, and get back a working result. Each micro-tool includes a specialized AI generation pipeline for its domain language, so the calling LLM never needs to know syntax or implementation details.

How It Works

  1. LLM specifies requirements - Natural language description of the desired outcome
  2. Vertical AI generates code - Domain-specific AI translates requirements to Graffiticode
  3. Compiler produces output - Code compiles to interactive components
  4. User interacts - Rendered UI collects data or displays information

The LLM doesn't need to know Graffiticode syntax. It simply describes what it needs, and the vertical AI handles the translation.

Tool Definitions

create_item

Create an interactive component from a natural language description.

ParameterTypeDescription
languagestringThe language code (e.g., "L0152", "L0166")
descriptionstringNatural language description of what to create
namestringOptional name for the item

update_item

Modify an existing item with natural language instructions.

ParameterTypeDescription
item_idstringThe ID of the item to update
modificationstringNatural language description of the changes to make

get_item

Retrieve an item by its ID.

ParameterTypeDescription
item_idstringThe ID of the item to retrieve

list_languages

Discover available languages and their capabilities.

ParameterTypeDescription
categorystringOptional category filter
searchstringOptional search term

get_language_info

Get detailed information about a specific language.

ParameterTypeDescription
languagestringThe language code (e.g., "L0152")

Dedicated AI Architecture

Each Graffiticode micro-tool has its own dedicated AI:

LanguageDomainVertical AI Capability
L0002Base LanguageCore functionality shared across all languages
L0137Data TransformationGraphQL queries, flattening, reshaping data
L0152Interactive MapsMarkers, layers, geospatial data visualization
L0159FlashcardsLearning cards, spaced repetition, memorization
L0166SpreadsheetsFormulas, cell formatting, spreadsheet assessments

Benefits

  • No syntax learning - LLMs describe intent, not implementation
  • Domain expertise - Vertical AIs encode best practices for each domain
  • Reliable output - Consistent, working code every time
  • Iterative refinement - Use update_item to modify existing components