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TIDY 6.11 gives customers more control over their property details, expands how you can reach the AI agent, and resolves a set of bugs across scheduling, property selection, and automation.

New Features & Improvements

• Edit Property Details: You can now update bedrooms, bathrooms, square footage, year built, and WiFi details directly from your property settings — no need to contact support to make corrections.
• Phone & SMS Access to AI Agent: You can now call or text the TIDY AI agent via a dedicated phone number. It works just like the in-app chat — ask questions, manage properties, or get help with your account.
• Automatic Account Manager Assignment: Every new customer is now automatically assigned a dedicated account manager (concierge) at signup, so you have a consistent point of contact from day one.
• Payment Method on AI Shared Links: Shared links generated by the AI agent now support adding a payment method, making it easier for your team or guests to complete bookings end-to-end.

Bug Fixes

• Fixed an issue where the property selector (tidy-select) wasn't working for some users, preventing them from switching between properties.
• Fixed an issue where job requests were not appearing when viewing the Monthly Schedule, causing some upcoming jobs to appear missing.
• Fixed the Automations page timing out for customers with many automations — the page now loads reliably regardless of how many workflows you have configured.
• Fixed an issue where creating a workflow from a template returned no data, which could cause the new workflow to not appear immediately after creation.

If you manage Airbnb or VRBO properties, you already know the grind: check the calendar, message the cleaner, confirm the turnover, update the listing, repeat. What if your AI coding agent could handle all of that?

With TIDY's agent skills, you can install a single command and let Claude Code (or Codex CLI, Cursor, or any compatible agent) manage your vacation rental operations directly. Schedule turnovers, track maintenance, and coordinate pros — all through natural language.

This tutorial walks you through setting it up from scratch.

What You Need

• A TIDY account — sign up free
• Claude Code, Codex CLI, Cursor, or another compatible AI agent
• 5 minutes

Step 1: Get Your API Token

Sign up or log in to TIDY, then generate an API token. You can do this via the API:

curl -X POST https://api.tidy.com/v1/customer/login \
  -H "Content-Type: application/json" \
  -d '{"email": "you@example.com", "password": "your-password"}'

Save the token:

export TIDY_API_TOKEN=your-token-here

Step 2: Install the Skill

For vacation rental management, install the tidy-vacation-rental skill:

npx skills add TIDYAPP/tidy-agent-skills --skill tidy-vacation-rental

That's it. Your agent now understands TIDY's vacation rental workflows.

Step 3: Add the MCP Server (Optional but Recommended)

Skills teach your agent how to use TIDY. The MCP server gives it the actual tools to call. For the best experience, add both:

claude mcp add tidy -- npx @tidyapp/mcp-server

Step 4: Try It

Now ask your agent something like:

"I have a guest checking out of 123 Beach Rd on Saturday at 11am. A new guest arrives at 3pm. Schedule the turnover clean."

Your agent will use TIDY to create the reservation, schedule the cleaning between checkout and check-in, and confirm the booking. You can follow up with:

"What cleanings are scheduled across all my properties this week?"

"Cancel the turnover clean for 456 Oak Ave, the guest extended their stay."

Real Workflow Example

Here's what a typical session looks like. You open Claude Code and type:

You: Set up a new Airbnb listing at 789 Pine St,
     gate code is #4521, park in the driveway.

Agent: ✓ Address created at 789 Pine St.
       Gate code and parking instructions saved.

You: I have a guest checking out Sunday at 10am,
     new guest arrives at 4pm. Schedule the turnover.

Agent: ✓ Turnover cleaning scheduled.
       Sunday 10:30 AM - 2:00 PM at 789 Pine St.
       Pro will receive gate code automatically.

No app switching. No manual coordination. Your agent handles the logistics while you handle the strategy.

Not Just Vacation Rentals

If you manage properties that don't have guest turnover cycles — like your home or office — install the tidy-cleaning-maintenance skill instead:

npx skills add TIDYAPP/tidy-agent-skills --skill tidy-cleaning-maintenance

This skill focuses on recurring cleanings, maintenance issue tracking, and pro management.

Learn More

• Developer Hub — All 5 ways to connect to TIDY
• MCP Server — Connect any MCP-compatible agent
• Agent Skills — All available skills and marketplaces
• Authentication — Getting your API token

TIDY's MCP server lets any MCP-compatible AI agent manage your properties. Claude Desktop, Claude Code, Cursor, Codex CLI, VS Code with Copilot — if it supports MCP, it can now schedule cleanings, report maintenance, and coordinate turnovers through TIDY.

Setup takes under 5 minutes. Here's how.

What is MCP?

Model Context Protocol (MCP) is the open standard for connecting AI agents to external tools and services. Instead of hard-coding API calls, your agent discovers available tools through MCP's protocol and calls them as needed. This means your agent doesn't need to know TIDY's API schema in advance — it learns what's available automatically.

Step 1: Get Your API Token

You need a TIDY account and API token. If you don't have one:

1. Create a free TIDY account
2. Get your token via the login endpoint:

   curl -X POST https://api.tidy.com/v1/customer/login \
     -H "Content-Type: application/json" \
     -d '{"email": "you@example.com", "password": "your-password"}'

3. Save the returned token for the next step.

Step 2: Add the MCP Server

Choose your platform:

Claude Code

claude mcp add tidy -- npx @tidyapp/mcp-server

Set your token as an environment variable: export TIDY_API_TOKEN=your-token

Claude Desktop

Go to Settings > Developer > Edit Config and add:

{
  "mcpServers": {
    "tidy": {
      "command": "npx",
      "args": ["@tidyapp/mcp-server"],
      "env": {
        "TIDY_API_TOKEN": "your-token"
      }
    }
  }
}

Cursor

Go to Settings > MCP and add the same JSON configuration as Claude Desktop.

VS Code (Copilot)

Create .vscode/mcp.json in your project:

{
  "servers": {
    "tidy": {
      "command": "npx",
      "args": ["@tidyapp/mcp-server"],
      "env": {
        "TIDY_API_TOKEN": "your-token"
      }
    }
  }
}

Codex CLI

codex mcp add tidy -- npx @tidyapp/mcp-server

Step 3: Test It

Open your agent and try:

"Use TIDY to list my addresses"

If you don't have any addresses yet:

"Use TIDY to add a new property at 123 Main St, Miami FL 33101. Gate code is #1234, park in the driveway."

Then try something more practical:

"Schedule a 2-hour cleaning next Tuesday afternoon at 123 Main St"

What Your Agent Can Do

Once connected, your agent has access to 5 MCP tools:

• message_tidy — The primary interface. Send any natural language request.
• get_status — Check status of a request or job.
• list_addresses — See all your properties.
• list_bookings — View upcoming and past cleanings.
• list_issues — Track maintenance issues.

The message_tidy tool is the most powerful — it accepts natural language and TIDY figures out what to do. Your agent can say "the bathroom faucet is leaking" and TIDY will create a maintenance issue, categorize it, and optionally assign it for resolution.

Bonus: Add Agent Skills Too

MCP gives your agent the tools. Skills give it the knowledge. For the best experience, install a TIDY agent skill alongside the MCP server:

npx skills add TIDYAPP/tidy-agent-skills

This teaches your agent TIDY-specific workflows, like how to handle a guest turnover or set up recurring maintenance.

Learn More

• MCP Server landing page — Platform-specific setup details
• Full MCP documentation — Tool schemas, troubleshooting, advanced config
• Developer Hub — All 5 ways to connect to TIDY

If you live in the terminal, you shouldn't have to leave it to manage your properties. The TIDY CLI brings property management to the command line — schedule cleanings, report maintenance, check bookings, and manage your portfolio without opening a browser.

Install in Seconds

npm install -g @tidyapp/cli

Or run without installing:

npx @tidyapp/cli message "Schedule a cleaning next Tuesday"

What It Does

The TIDY CLI wraps our REST API into a developer-friendly interface. Everything you can do through the API, you can do from your terminal:

• Natural language requests — tidy message "Book a cleaning next week"
• Booking management — List, create, and cancel cleanings
• Maintenance tracking — Report issues, track resolution
• Property management — Manage addresses, access notes, parking info
• Guest reservations — Track check-ins and check-outs
• JSON output — Pipe results to jq, scripts, or other tools

Quick Tour

Authenticate

$ tidy login
Email: you@example.com
Password: ********
✓ Logged in successfully. Token saved.

Schedule a cleaning with natural language

$ tidy message "Schedule a 2-hour cleaning next Tuesday afternoon at my office"
✓ Booking created: #78901
  Date: Tuesday March 25, 1:00 PM - 5:00 PM
  Address: 456 Oak Ave

Check what's scheduled

$ tidy bookings list --upcoming
ID      Date         Address          Status
78901   Mar 25       456 Oak Ave      Confirmed
78902   Mar 27       123 Main St      Pending

Report a maintenance issue

$ tidy issues create --address 1001 --urgent "Kitchen faucet leaking"
✓ Issue created: #4567
  Priority: Urgent
  Status: Open

Get JSON output for scripting

$ tidy bookings list --upcoming --json | jq '.[].address'
"456 Oak Ave"
"123 Main St"

Why a CLI?

We built the TIDY CLI for developers who want to:

• Script property management — Cron jobs, CI/CD pipelines, or custom automation scripts
• Quick status checks — Faster than logging into a web app
• Combine with other tools — Pipe JSON output to jq, grep, or your own scripts
• Test API integrations — Verify requests before building them into your app

CLI vs MCP vs Skills

The CLI is for humans working in the terminal. If you want your AI agent to use TIDY:

• MCP Server — Direct tool access for Claude, Cursor, Codex, and other MCP agents
• Agent Skills — Pre-built workflow knowledge for the skills.sh ecosystem

All three use the same underlying REST API, so you can mix and match based on your workflow.

Get Started

npm install -g @tidyapp/cli && tidy login

Full command reference: CLI Reference Docs

See all developer tools: Developer Hub

Most software today is designed for humans. A person opens an app, navigates menus, fills out forms, clicks buttons. The entire interface assumes a human is on the other end.

We believe that assumption is about to change—fundamentally and permanently. Over the next several years, the majority of interactions with software like TIDY will not come from humans clicking through a UI. They will come from AI agents acting on behalf of humans—personal assistants, property management agents, home automation systems, and general-purpose agents that handle the logistics of daily life.

We are building accordingly. Today we are launching TIDY's new MCP server and general-purpose API, designed from the ground up for the agentic era.

What We Are Launching

Two things, both aimed at making TIDY the easiest way for any AI agent to handle cleaning and maintenance.

A new MCP server. Model Context Protocol is the open standard for connecting AI agents to external tools and services. Any MCP-compatible agent—Claude, and a growing number of others—can now connect to TIDY's MCP server and make cleaning and maintenance requests directly. The agent does not need to know our API schema in advance. It discovers TIDY's capabilities through MCP's tool discovery protocol, understands what actions are available, and calls them as needed.

A new general-purpose API. We have updated and expanded our REST API with endpoints designed specifically for agent consumption. These endpoints accept natural language alongside structured data, so an agent can describe a problem in plain English—"the kitchen faucet is dripping and there's water on the floor"—and TIDY's AI interprets the request, routes it to the right service category, and returns a structured response the agent can act on.

The core idea is simple: an agent can call into TIDY with almost any cleaning or maintenance request, and we can respond back—with actions, status updates, options, or clarifying questions. TIDY becomes a service that agents can use the same way a human would use a property manager: describe what you need, and we handle it.

Why Agents Change Everything

Consider how property maintenance works today. A homeowner notices a problem. They open an app or make a phone call. They describe the issue, wait for a response, compare options, confirm a time, and follow up to make sure the work was done. Each step requires the human's attention.

Now consider what happens when an AI agent handles this. The homeowner tells their assistant—in conversation, by text, or through any interface—"the kitchen faucet is dripping." The agent takes it from there. It files the request with TIDY. TIDY's system classifies the issue, checks the property's digital twin for relevant context (what kind of faucet, when it was last serviced, which plumber has the best track record for this type of repair), proposes options, and sends them back to the agent. The agent confirms on behalf of the owner, or asks a clarifying question if needed. The repair is scheduled, the pro is dispatched, and the agent follows up when the job is complete.

The owner's total involvement: one sentence.

Or take a more proactive scenario. A general-purpose home management agent notices it's been three months since the last deep clean. Based on the owner's preferences, it initiates a request through TIDY—no prompt from the owner at all. TIDY schedules the cleaning, the pro confirms, the job gets done. The owner gets a notification that their home was cleaned. That is it.

The interface shifts from UI to conversation. From human-driven to agent-driven. TIDY needs to be on the other end of that conversation, and with our new MCP server and API, we are.

How It Works

MCP Server

MCP is an open protocol that lets AI agents discover and use external tools. When an agent connects to TIDY's MCP server, it receives a list of available tools—things like requesting a cleaning, scheduling maintenance, checking job status, or getting a quote. The agent can then call these tools as part of a conversation with the user.

From the agent's perspective, TIDY is just another tool in its toolkit. The agent does not need custom integration code or knowledge of our internal data model. It discovers what TIDY can do, and uses those capabilities as needed.

General-Purpose API

Our updated REST API is designed for flexibility. Traditional APIs require callers to know the exact endpoint, parameters, and data format. That works for human developers building integrations, but agents operate differently. They reason about problems in natural language and need interfaces that can meet them where they are.

TIDY's new API endpoints accept both structured requests and natural language descriptions. An agent can send a fully structured request if it has the data, or a plain English description if it does not. TIDY's AI layer handles the interpretation either way—classifying the request, extracting relevant details, and routing it to the right workflow.

Responses are structured and machine-readable, designed for agents to parse and act on without ambiguity. Status codes, action options, estimated timelines, and next steps are all returned in a format that agents can reason about programmatically.

Webhooks for Agent Awareness

Agents need to stay informed. Our webhook system notifies agents when events happen—a job is completed, an issue is detected, a pro confirms or reschedules. This allows agents to proactively update their users or take follow-up actions without polling.

Full documentation is available in our developer docs.

Why We Are Building for Agents First

This is not a side project or a nice-to-have integration. We believe agents will be the primary way people interact with services like TIDY within the next few years.

Think about the trajectory. Today, most people manage their homes reactively. Something breaks, they deal with it. Cleaning gets scheduled when someone remembers to schedule it. Maintenance gets done when it becomes urgent. The friction of coordinating these things means they are often deferred, forgotten, or handled poorly.

Agents eliminate that friction entirely. When your AI assistant can handle a maintenance request in the time it takes you to mention it, the entire model shifts from reactive to proactive. Homes get maintained better because the cost of coordinating maintenance drops to near zero.

We have spent 12 years building the infrastructure to coordinate cleaning and maintenance at scale—digital twins of properties, AI models trained on data from over 100,000 homes, a vetted network of service providers, predictive scheduling, quality verification. All of that infrastructure now sits behind an interface that any agent can use.

The hard part was never the interface. The hard part was building the operational backbone that makes it possible to say "fix my faucet" and have it actually happen, reliably, at scale. That backbone exists. Now we are opening it up to every agent that wants to use it.

What This Means

For property owners and homeowners: Your AI assistant—whatever form it takes—can now manage your cleaning and maintenance through TIDY. Describe a problem in conversation and it gets handled. Set preferences once and let your agent manage the rest proactively.

For developers building agents: If your agent needs to handle anything related to cleaning or maintenance, TIDY is the backend. Connect via MCP for the simplest integration, or use our REST API for more control. Either way, you get access to TIDY's full operational infrastructure—scheduling, pro dispatch, quality verification, digital twins—without building any of it yourself.

For the industry: The coordination layer is becoming invisible. The future is not humans managing software that manages properties. It is agents managing properties through services like TIDY, with humans involved only when they want to be. We are making sure TIDY is ready for that future.