Skip to main content

Documentation Index

Fetch the complete documentation index at: https://docs.stagingspaces.app/llms.txt

Use this file to discover all available pages before exploring further.

​
Using with AI Agents

StagingSpaces is designed to work seamlessly with AI agents like Claude (via Claude Code or MCP), GPT, and other LLM-based tools.

​
Machine-readable API reference

We provide several formats for AI agent consumption:
FileURLPurpose
llms.txt/llms.txtConcise API overview for LLMs
llms-full.txt/llms-full.txtComplete API reference with all parameters
openapi.yaml/docs/openapi.yamlOpenAPI 3.1 spec for tool generation
ai-plugin.json/.well-known/ai-plugin.jsonAgent marketplace discovery

​
Using with Claude Code

​
Via MCP Server

Install our MCP server to give Claude direct API access: 
# Install the MCP server
npm install -g @stagingspaces/mcp-server

# Or add to your Claude Code config
claude mcp add stagingspaces -- npx @stagingspaces/mcp-server
Then tell Claude:
“Stage this room photo with a scandinavian style”
Claude will use the MCP tools to call the API directly.

​
Via llms.txt

Point Claude at the API reference:
“Read https://stagingspaces-production-6fb7.up.railway.app/llms.txt and use the StagingSpaces API to stage my room photos”

​
Using with GPT / Custom GPTs

  1. Create a Custom GPT
  2. Add the OpenAPI spec as an Action: /docs/openapi.yaml
  3. Configure authentication with your API key
  4. The GPT can now stage images on your behalf

​
Using with any agent framework

​
LangChain

from langchain.tools import tool
import requests

@tool
def stage_room(image_path: str, style: str = "modern") -> dict:
    """Stage an empty room photo with AI-placed furniture.

    Args:
        image_path: Path to the room image file
        style: Design style (modern, scandinavian, farmhouse, etc.)
    """
    response = requests.post(
        "https://stagingspaces-production-6fb7.up.railway.app/api/v1/stage",
        headers={"Authorization": f"Bearer {API_KEY}"},
        files={"image": open(image_path, "rb")},
        data={"style": style}
    )
    return response.json()

​
CrewAI / AutoGPT

Use the OpenAPI spec at /docs/openapi.yaml to auto-generate tools.

​
Agent-friendly design decisions

  • Simple auth: Single Bearer token, no OAuth flows
  • Multipart uploads: Standard file upload format all HTTP libraries support
  • Predictable responses: Consistent JSON structure across all endpoints
  • Claim codes: Human-readable codes (SS-7X9K2M) agents can relay to users
  • Idempotent reads: GET endpoints are safe to call repeatedly
  • Clear errors: Error messages include actionable fix suggestions