diagram-forge
Generates professional architecture diagrams from natural language descriptions using template-driven prompts and swappable AI image providers.
README
Diagram Forge
Turn natural language into enterprise-grade architecture diagrams. Diagram Forge is an MCP server that combines template-driven prompt engineering with swappable AI image providers to generate professional diagrams from any MCP-compatible client.
Instead of wrestling with diagramming tools or manually crafting image generation prompts, describe your system in plain English and let Diagram Forge handle the rest — template selection, prompt engineering, style application, and cost tracking.

Features
- 13 diagram templates — Architecture (TOGAF), C4 Container, Executive Infographic, data flow, component, sequence, integration, infographic, generic, product roadmap, workstreams, kanban, and brand infographic
- 2 image providers — Google Gemini (recommended), OpenAI (GPT Image)
- Auto provider selection — Each template recommends the best provider/model for its diagram type
- Template-driven prompts — YAML templates with hex-coded color systems, explicit rendering instructions, and layout rules
- Style references — Feed a visual example to guide output consistency (Gemini)
- Cost tracking — SQLite-backed usage and cost reporting
- Cross-client — Works with Claude Code, Claude Desktop, Codex CLI, Gemini CLI via stdio transport
Quick Start
1. Install
pip install diagram-forge
Or from source:
git clone https://github.com/jessepike/diagram-forge.git
cd diagram-forge
pip install -e ".[dev]"
2. Configure a provider
Set at least one API key:
export GEMINI_API_KEY="your-key" # Google Gemini (recommended)
export OPENAI_API_KEY="your-key" # OpenAI GPT Image
3. Add to your MCP client
Claude Code (.mcp.json in your project):
{
"diagram-forge": {
"command": "python",
"args": ["-m", "diagram_forge.server"]
}
}
Claude Desktop (claude_desktop_config.json):
{
"mcpServers": {
"diagram-forge": {
"command": "python",
"args": ["-m", "diagram_forge.server"]
}
}
}
Codex CLI / Gemini CLI — same .mcp.json format as Claude Code.
4. Generate a diagram
Ask your AI client naturally:
"Generate an architecture diagram of a three-tier web app with a React frontend, Node.js API layer, and PostgreSQL database"
Or be more specific:
"Create a TOGAF-style architecture diagram showing our microservices. Use the architecture template, Gemini provider, 16:9 aspect ratio."
MCP Tools
| Tool | Description |
|---|---|
generate_diagram |
Generate a diagram from a text prompt with template and style support |
edit_diagram |
Edit an existing diagram with natural language instructions |
list_templates |
List available diagram templates and their variables |
list_providers |
Show configured providers, API key status, and supported features |
list_styles |
List available style reference images |
get_usage_report |
View generation costs and usage stats by provider, type, or day |
configure_provider |
Set up an API key for a provider (session-only) |
Diagram Types
| Type | Template | Best For |
|---|---|---|
architecture |
Enterprise Architecture (TOGAF) | System architecture, layered designs |
c4_container |
C4 Container Diagram | Software system internals, C4 Level 2 |
exec_infographic |
Executive Infographic | Stakeholder presentations, semantic colors + icons |
data_flow |
Data Flow / Pipeline | ETL pipelines, data movement |
component |
Component Detail View | Service internals, module structure |
sequence |
Sequence Diagram | Request flows, protocol interactions |
integration |
Integration / Connection Map | System connections, API landscape |
infographic |
Infographic / Learning Card | Concept explanations, overviews |
product_roadmap |
Product Roadmap | Phase pipelines, gate icons, status badges |
workstreams |
Workstreams / Priority Lanes | Swimlane planning with status and dependencies |
kanban |
Kanban Board | Three-column task boards with category color bars |
brand_infographic |
Brand Infographic | Investor/marketing slides with brand aesthetic |
generic |
Custom / Freeform | Anything else |
Style References
Feed a visual example to guide output consistency. Gemini supports this natively via multi-image input.
generate_diagram(prompt="...", style_reference="c4-container")
Save your own styles to ~/.diagram-forge/styles/<name>/reference.png with an optional style.yaml for metadata.
Auto Provider Selection
Set provider="auto" (the default) and Diagram Forge picks the best provider based on the diagram type. Each template includes a tested recommendation. Override with provider="openai" or provider="gemini" when you want a specific model.
Claude Code Plugin
This repo includes a Claude Code plugin in diagram-forge-plugin/ that adds a guided UX layer on top of the MCP server:
/diagram:create— Guided diagram creation with context gathering/diagram:iterate— Refine an existing diagram/diagram:usage— View cost report/diagram:templates— Browse available templates- Context-gatherer agent — Automatically explores your project to understand what to diagram
- Diagram intelligence skill — Auto-triggers when you mention diagrams
To use, install the plugin or add the .mcp.json from the plugin directory.
How It Works
- Template selection — Matches your request to one of 13 YAML templates, each encoding proven prompt patterns (color systems, layer organization, legibility rules)
- Prompt rendering — Merges your description with the template, substituting variables and applying style defaults
- Provider dispatch — Sends the engineered prompt to your chosen provider (Gemini or OpenAI)
- Image handling — Saves the generated image, records cost and metadata to SQLite
- Iteration — Edit existing diagrams with natural language instructions via providers that support image editing
Development
# Install dev dependencies
pip install -e ".[dev]"
# Run tests (52 tests)
python -m pytest tests/ -v --cov=diagram_forge
# Lint
ruff check src/ tests/
# Type check
mypy src/
# Test MCP tools interactively
npx @modelcontextprotocol/inspector python -m diagram_forge.server
# Run low-cost model benchmark (dry-run first)
python scripts/eval_diagram_models.py --dry-run --max-cost-usd 5
python scripts/eval_diagram_models.py --execute --providers gemini,openai --resolution 1K --max-cases 6 --max-cost-usd 5
Benchmark and model-refresh docs:
docs/evaluation-runbook.mddocs/model-refresh-process.mdevals/benchmark_v1.yaml
Architecture
src/diagram_forge/
server.py # FastMCP server — 7 tools, stdio transport
models.py # Pydantic v2 models
config.py # YAML + env var config loading
template_engine.py # Template loading and prompt rendering
style_manager.py # Style reference image management
cost_tracker.py # SQLite usage/cost tracking
providers/
base.py # BaseImageProvider ABC
gemini.py # Google Gemini
openai_provider.py # OpenAI GPT Image
templates/ # 13 YAML prompt templates
License
MIT
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