AI HomeDesign MCP Server

by aihomedesign Your server? Claim it

answering

AI HomeDesign MCP is answering right now. Last checked 15 min ago. It exposes 20 tools. Last commit 9 Jul 2026.

MCP server to virtually stage, redesign, enhance and declutter real-estate photos.

Uptime history 47 days of history · worst day 95%

47 days agonow

100.0%

Uptime 24h

91 of 91 checks

Tools

read from the server

161 ms

Response time

average over 24h

Stars

last commit 9 Jul 2026

AI HomeDesign MCP does not always answer

Over the last week it answered 99.2% of our checks. We check every 15 minutes, so you hear about the next outage within the hour — not from your users.

Connect this server

Endpoint below is the one we actually reach during checks — not the one copied from a README. Last verified 15 min ago.

Claude Code Claude Desktop Codex Cursor VS Code

run in your terminal

claude mcp add aihomedesign-mcp --transport http https://mcp.aihomedesign.com/{connector_token}/mcp

~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "aihomedesign-mcp": {
      "url": "https://mcp.aihomedesign.com/{connector_token}/mcp"
    }
  }
}

~/.codex/config.toml

[mcp_servers.aihomedesign-mcp]
url = "https://mcp.aihomedesign.com/{connector_token}/mcp"

.cursor/mcp.json

{
  "mcpServers": {
    "aihomedesign-mcp": {
      "url": "https://mcp.aihomedesign.com/{connector_token}/mcp"
    }
  }
}

.vscode/mcp.json

{
  "mcpServers": {
    "aihomedesign-mcp": {
      "url": "https://mcp.aihomedesign.com/{connector_token}/mcp"
    }
  }
}

Available tools 20

Read directly from the server with tools/list, grouped by what they act on. If a tool disappears, we record the date.

change

change_ceiling

Change the ceiling finish in a room photo (AI applies a tasteful default). Detect `space` from the image. Provide image_url OR image_base64.

change_floor

Change the floor material in a room photo (AI applies a tasteful default material). Detect `space` from the image. Provide image_url OR image_base64.

change_wall

Change the wall finish/colour in a room photo (AI applies a tasteful default finish). Detect `space` (room type) from the image. Provide image_url OR image_base64.

order

create_order

Upload one or more images and create an order. Provide `image_urls` (public URLs) and/or `image_base64` (raw base64 or data: URLs) — you can use either. Returns `order_id` and an `assets` list whose `id`s you map to a tool's input slot when running a process. For two-image tools pass roles like ['primary_angle','secondary_angle'] (or 'mask' for mask tools).

get_order

Fetch an order, including its input assets and any processes run on it.

process

get_process

Fetch a process: its `status` (pending/processing/done/failed) and, when done, the `final_assets` with downloadable result image URLs. If a webhook result has already arrived for this process, it is returned immediately.

run_process

Start an AI job on an existing order (full control over every tool). `asset_map` maps each of the tool's input-slot keys to an asset id from the order. `widgets` is the raw list of {slug, item_slugs}. Use `describe_tool` to get the exact slugs. Returns `process_ids` to poll with `get_process`.

project

create_project

Create a project (a container that groups all work for one property). Returns the new project's `id`.

get_project

Fetch a single project by id.

virtual

virtual_restaging

Replace the furniture in an ALREADY-FURNISHED room with a new design style. Same workflow as virtual_staging: ask the user for the style, detect the room type from the image. Provide image_url OR image_base64.

virtual_staging

Furnish an EMPTY room photo with AI furniture in a chosen design style. Provide the photo as `image_url` OR `image_base64` (raw base64 or a data: URL). WORKFLOW — follow exactly: • Do NOT choose a `style` yourself. Call this first with style empty; it returns the list of design styles. Present them to the user and let THEM pick, then call again with their chosen style. • Detect `space` (room type) from the image yourself and pass it (bedroom, kitchen, living-room, ...). Only if you truly cannot tell, leave it empty and the tool will ask the user.

capabilities

list_capabilities

List every AI HomeDesign tool this MCP can run, grouped by category. Returns each tool's slug, display name, description and whether it needs one or two input images. Start here to discover what is available.

day

day_to_dusk

Convert a daytime EXTERIOR photo into a dusk / twilight scene. No style needed. Provide image_url OR image_base64. sky_style: leave empty to use the default sky (recommended — the 30+ named sky slugs are not publicly listed). options (multi, optional): shadow-removal, lawn-touch-up.

describe

describe_tool

Show the input slots, widgets and selectable options for one tool, plus a ready-to-use example payload for `run_process`. Use this before `run_process` when you need the exact widget/item slugs for a tool.

enhance

enhance_image

Enhance a photo: better lighting, sharpness and colour balance. No style needed. Provide image_url OR image_base64. area: indoor | outdoor (detect from the image). options (multi, optional): add-fire-to-fireplace, add-screen-to-tv.

interior

interior_design

Fully redesign a FURNISHED room (walls, floors, furniture, decor) in a style. Same workflow as virtual_staging: never pick the style yourself — ask the user; detect the room type from the image. Provide image_url OR image_base64.

items

remove_items

Auto-detect and remove furniture/clutter from a room photo (decluttering), leaving a clean empty space. No style needed. Provide image_url OR image_base64.

projects

list_projects

List your projects (paginated). Optional free-text `search` on address.

styles

list_styles

List the allowed design styles, room types and widget options. With no argument, returns the global style/room/area lists. With a tool_slug, returns that tool's widgets and their allowed values. The staging/design helpers ONLY accept these values — anything else is rejected before calling the API.

wait

wait_for_result

Poll a process until it is `done` or `failed` (or until timeout), then return the final result image URLs. Respects the API's 5s minimum poll interval.

Endpoints

URL	Transport	State	Latency	Checked
https://mcp.aihomedesign.com/{connector_token}/mcp	streamable-http	answering	191 ms	15 min ago

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AI HomeDesign MCP — questions

Answers built from our own checks of this server.

What can AI HomeDesign MCP do?

It exposes 20 tools, read directly from the server on our last check. Among them: change_ceiling, change_floor, change_wall, create_order, create_project, day_to_dusk and 14 more. The full list with descriptions is on this page — we take it from the server itself via tools/list, not from a README. How MCP servers expose tools in the first place →

What is AI HomeDesign MCP mostly used for?

Its tools cluster around change, virtual and process. That is what this server is built to work with — the grouping comes from the actual tool names, not from a category we assigned.

Is AI HomeDesign MCP working right now?

We send a real MCP handshake every 15 minutes. Over the last 24 hours 91 of 91 checks got a reply (100.0%), average response time 161 ms. The bar chart above shows every period we have measured.

How do I connect AI HomeDesign MCP?

Copy the ready config from this page — we generate it for Claude Code, Claude Desktop, Codex, Cursor and VS Code, each with the file path that client actually reads. It is a remote server, so there is nothing to install — the client connects to the address.

Does AI HomeDesign MCP need an API key?

No. AI HomeDesign MCP completed a full MCP handshake with us as an anonymous client and listed its tools without asking for anything. All 20 of them are readable on this page. This is what we observed, not what the docs claim.

How fast is AI HomeDesign MCP?

It answers our handshake in 161 ms on average, which is faster than 74% of all working MCP servers we measure. The comparison comes from our own checks across the whole registry, every 15 minutes.

Is AI HomeDesign MCP open source?

Yes — it is published under the MIT licence, written in Python and 0 stars on GitHub. The source link is on this page, so you can read exactly what it does with your data before you connect it.