AdCP — Property Governance

Property Governance standardizes how advertising properties (websites, apps, CTV, podcasts, billboards) are identified, authorized, enriched with data, and selected for campaigns. Ships in 3.0 as the property-lists specialism under the governance protocol. Property lists and collection lists together form the inventory list system — property lists control where ads run (technical surfaces), while collection lists control what content ads run in (programs, shows, series). Both are setup-time artifacts managed by governance agents with the same lifecycle pattern. adagents.json is intentionally broader than ads.txt: it can describe not just which sales agents are present, but which properties, placements, and delegated sales paths they are actually authorized to make available. For a side-by-side comparison, see Why adagents.json is more expressive than ads.txt.

Overview

Property Governance addresses five distinct concerns:

Concern	Question	Owner	Mechanism
Property Identity	What properties exist?	Publishers	`adagents.json` properties array
Sales Authorization	Who can sell this property?	Publishers	`adagents.json` authorized_agents with `delegation_type`
Property Data	What do we know about this property?	Data providers	Governance agents via `get_adcp_capabilities`
Property Selection	Which properties meet my requirements?	Buyers	Property lists with filters

The first three are publisher-side declarations via adagents.json. The last two are buyer-side operations that consume property data from governance agents. Authorization is bilateral — publishers declare authorized agents in adagents.json (with delegation_type), and operators declare their property portfolio in brand.json (with relationship). Both sides must agree for the supply path to be verified. This is the AdCP equivalent of ads.txt + sellers.json. See ad networks for how this works.

Publisher Side: adagents.json

Publishers declare their properties, authorize sales agents, and reference governance agents via /.well-known/adagents.json:

{
  "$schema": "https://adcontextprotocol.org/schemas/3.2.0-beta.9/adagents.json",
  "properties": [
    {
      "property_id": "example_site",
      "property_type": "website",
      "name": "Example Site",
      "identifiers": [{"type": "domain", "value": "example.com"}]
    }
  ],
  "authorized_agents": [
    {
      "url": "https://agent.example.com",
      "authorized_for": "Official sales agent",
      "authorization_type": "property_ids",
      "property_ids": ["example_site"],
      "delegation_type": "direct"
    }
  ],
  "property_features": [
    {
      "url": "https://api.sustainability-vendor.example",
      "name": "Sustainability Vendor",
      "features": ["carbon_score", "green_media_certified"]
    },
    {
      "url": "https://api.quality-vendor.example",
      "name": "Quality Vendor",
      "features": ["mfa_score", "ad_load_rating", "page_speed"]
    }
  ]
}

Governance Agent Discovery via property_features

The property_features array solves a key discovery problem: how does a buyer know which governance agents have data about a given property? Without property_features, buyers would need to query every possible governance agent to find out who has compliance, sustainability, or quality data. With property_features, publishers declare these relationships upfront:

Field	Purpose
`url`	Governance agent’s API endpoint
`name`	Human-readable agent name
`features`	Feature IDs this agent provides (e.g., `carbon_score`, `mfa_score`)
`publisher_id`	Optional identifier for looking up this publisher at the agent

Example use cases:

Sustainability: Publisher declares a carbon measurement vendor tracks their emissions
Quality: Publisher declares a verification vendor measures MFA score and ad density
Consumer experience: Publisher declares a vendor that tracks page speed and ad load

Buyers read property_features from adagents.json, then query only the relevant governance agents for detailed data. See the adagents.json Tech Spec for complete documentation including examples and the discovery workflow.

Buyer Side: Property Data and Selection

Property Data Providers

Governance agents provide data about properties - compliance scores, brand suitability ratings, sustainability metrics, consumer experience scores, etc. They advertise their capabilities via get_adcp_capabilities in the governance.property_features section:

{
  "governance": {
    "property_features": [
      { "feature_id": "mfa_score", "type": "quantitative", "range": { "min": 0, "max": 100 } },
      { "feature_id": "coppa_certified", "type": "binary" },
      { "feature_id": "carbon_score", "type": "quantitative", "range": { "min": 0, "max": 100 } }
    ]
  }
}

Buyers send property lists to these agents, and the agents filter and score the properties based on their specialized data. Different agents specialize in different data:

Brand suitability providers (content classification, risk scoring)
Quality measurement (MFA score, ad density, fraud detection)
Sustainability providers (carbon scoring, green media certification)
Consumer experience (page speed, ad load, layout shift)

Property Selection via Governance Agents

Buyers create property lists on governance agents - the agents manage these lists and apply their filtering logic:

{
  "tool": "create_property_list",
  "arguments": {
    "name": "Q1 Campaign - UK Premium",
    "base_properties": [
      {
        "selection_type": "publisher_tags",
        "publisher_domain": "raptive.com",
        "tags": ["premium_news"]
      }
    ],
    "filters": {
      "countries_all": ["UK"],
      "channels_any": ["display", "video"],
      "feature_requirements": [
        { "feature_id": "mfa_score", "min_value": 70, "max_value": 100 }
      ]
    },
    "brand": {
      "domain": "toybrand.com"
    }
  }
}

When you provide a brand reference, governance agents resolve the brand identity and automatically apply appropriate rules (COPPA for children’s brands, content filtering based on industry, etc.). A buyer agent typically works with multiple governance agents (brand suitability, quality, sustainability) and aggregates/intersects their results into a final compliant list.

How It Fits Together

The Complete Flow

Publisher declares properties, sales agents, AND governance agents in adagents.json
Buyer discovers governance agents by reading property_features from adagents.json
Buyer queries each governance agent’s get_adcp_capabilities for detailed capabilities
Buyer creates property lists on each governance agent with filters and brand references
Governance agents evaluate properties and notify buyer via webhooks when lists change
Buyer aggregates results into a final compliant list
Buyer shares property list reference with sellers (with auth token)
Seller caches resolved list for bid-time decisions

Once a buyer has a compliant property list, they share it with sellers:

Get a list reference: The buyer agent exposes the list via get_property_list
Issue an auth token: The buyer generates a token that authorizes access to the list
Pass to seller: Include the property-list reference, with auth_token, in the request’s targeting_overlay
Seller caches locally: Sellers fetch and cache the resolved list for bid-time decisions
Webhooks for updates: When the list changes, sellers are notified to refresh their cache

{
  "targeting_overlay": {
    "property_list": {
      "agent_url": "https://buyer-agent.example.com",
      "list_id": "pl_q1_uk_premium",
      "auth_token": "eyJhbGciOiJIUzI1NiIs..."
    }
  }
}

Sellers use this reference in get_products to filter available inventory:

{
  "tool": "get_products",
  "arguments": {
    "buying_mode": "brief",
    "brief": "UK video inventory for Q1",
    "targeting_overlay": {
      "property_list": {
        "agent_url": "https://buyer-agent.example.com",
        "list_id": "pl_q1_uk_premium",
        "auth_token": "..."
      }
    }
  }
}

Each returned product carries a list_applications receipt for the property list. The receipt identifies the list without echoing its auth_token, records the list resolution and seller evaluation timestamps, and reports how many resolved entries matched or did not match that product. Product pricing and forecasts reflect the eligible inventory after the list is applied. Collection lists use the same receipt shape.

Relationship to Other Protocols

Property Governance + Media Buy

The Media Buy Protocol consumes property lists at multiple stages:

Product discovery: Pass targeting_overlay.property_list to get_products to filter inventory to compliant properties
Media buy creation: Reference property lists to constrain where ads can run
Authorization: adagents.json validates agent authority to sell

Property Governance + Signals

Both protocols operate on properties but serve different purposes:

Signals Protocol	Property Governance
Audience/contextual data	Property metadata and compliance
”Who should see this ad?"	"Where can this ad run?”
Signal activation	Property filtering

Tasks

Discovery

get_adcp_capabilities: Discover governance capabilities including property features (protocol-level task)

Property List Management

create_property_list: Create a new property list on a governance agent
get_property_list: Retrieve resolved properties (with caching guidance)
update_property_list: Modify filters or base properties
delete_property_list: Remove a property list

Getting Started

Publishers:

Create /.well-known/adagents.json with property definitions
Authorize sales agents for your properties
Declare governance agents in property_features (sustainability vendors for carbon, quality vendors for MFA and ad load, suitability vendors for content classification, etc.)

Buyers:

Discover governance agents by reading property_features from publishers’ adagents.json files
Query each governance agent’s get_adcp_capabilities for capabilities
Create property lists on relevant governance agents with filters and brand references
Aggregate results into a final compliant list
Share property list references with sellers (with auth tokens)

Governance Agent Implementers:

Implement get_adcp_capabilities to advertise your capabilities in governance.property_features
Implement property list CRUD operations
Support webhooks to notify buyers when evaluations change
Work with publishers to get listed in their property_features
See the Protocol Specification for implementation details

See the Protocol Specification for detailed implementation guidance.

Getting Started

Building with AdCP

Protocol

Using AAO

FAQ

Trust & Security

Reference

Certification

Property Governance

Overview

Publisher Side: adagents.json

Governance Agent Discovery via property_features

Buyer Side: Property Data and Selection

Property Data Providers

Property Selection via Governance Agents

How It Fits Together

The Complete Flow

Relationship to Other Protocols

Property Governance + Media Buy

Property Governance + Signals

Tasks

Discovery

Property List Management

Getting Started

​Overview

​Publisher Side: adagents.json

​Governance Agent Discovery via property_features

​Buyer Side: Property Data and Selection

​Property Data Providers

​Property Selection via Governance Agents

​How It Fits Together

​The Complete Flow

​Sharing Property Lists with Sellers

​Relationship to Other Protocols

​Property Governance + Media Buy

​Property Governance + Signals

​Tasks

​Discovery

​Property List Management

​Getting Started

Overview

Publisher Side: adagents.json

Governance Agent Discovery via property_features

Buyer Side: Property Data and Selection

Property Data Providers

Property Selection via Governance Agents

How It Fits Together

The Complete Flow

Sharing Property Lists with Sellers

Relationship to Other Protocols

Property Governance + Media Buy

Property Governance + Signals

Tasks

Discovery

Property List Management

Getting Started