Making your inventory available to AI agents

AI agents are starting to buy media. When an agency’s AI assistant is evaluating ad inventory across platforms, it needs a way to discover what you sell, understand your pricing and targeting options, and execute a buy — all through a standard interface. AdCP (Ad Context Protocol) provides that interface. If you’re a publisher, SSP, or ad platform, implementing AdCP makes your inventory accessible to any compliant buyer agent without requiring custom integrations for each one.

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Why this matters

Today, every platform requires buyers to learn a proprietary API. That works when humans are doing the buying. But AI agents work across many platforms simultaneously, and they need a shared language for common operations. Platforms that implement AdCP are discoverable by buyer agents out of the box. Platforms that don’t require each buyer to build a custom integration — which limits the pool of agents that can access your inventory.

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What you need to implement

AdCP sell-side integration has three parts:

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Industry-specific guidance

The core integration steps above apply to all sellers. If you’re an ad network aggregating across multiple platforms, see the network aggregation pattern in the AI media guide for product modeling, account chains, catalog forwarding, and adagents.json for networks. For vertical-specific product modeling, pricing patterns, and measurement:

• AI platforms and AI ad networks: See the AI media guide for sponsored responses, AI search products, generative creative from catalogs, and Sponsored Intelligence handoffs.
• Retail media networks: See the commerce media guide for sponsored product listings, closed-loop attribution, and in-store measurement.

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Accounts and sandbox

Production sales agents should implement the accounts protocol. sync_accounts and list_accounts let buyers establish billing relationships, track spend per advertiser, and manage multiple operators buying on behalf of different brands through a single agent. The account model depends on your platform:

• Walled gardens (social platforms, AI platforms, retail media networks) typically use explicit accounts — set require_operator_auth: true in get_adcp_capabilities so each operator authenticates independently.
• Open platforms (publishers, SSPs) can use implicit accounts — the agent is trusted and declares accounts via sync_accounts.

See Accounts and Agents for full workflows. Sandbox support is strongly recommended. Declare account.sandbox: true in your capabilities so buyers can provision test accounts and validate the full integration — product discovery, media buy creation, delivery reporting — before committing real spend. Without sandbox, buyers must test against live inventory, which slows adoption and increases onboarding friction. See Sandbox mode for implementation details.

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Optional: delivery reporting

Implement get_media_buy_delivery to let buyer agents pull performance data — impressions, clicks, spend, conversions — in a standardized format. This is how agents monitor campaigns across platforms without logging into each dashboard individually.

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Product design patterns

Different inventory types use different AdCP features: For content-centric inventory, see Shows and episodes. For exclusivity and sponsorship patterns, see Media products.

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Governance enforcement

Buyer agents increasingly require governance compliance before committing spend. Implementing governance makes your inventory eligible for brand-safe campaigns, reduces post-campaign disputes, and signals to buyer agents that your platform takes brand suitability seriously. Three governance domains are relevant to sellers.

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Property governance via adagents.json

Your adagents.json file is the foundation of property governance. It declares which properties you sell, which agents are authorized to sell them, and which governance agents have data about your inventory. Buyer agents use this to verify supply path authorization and discover property intelligence — if your adagents.json is missing or incomplete, buyer agents cannot verify that you are authorized to sell what you claim. Declare property_features entries to point buyers toward governance agents that score your properties for quality, sustainability, or brand safety. See the property governance specification for the full schema and the adagents.json tech spec for publisher-side setup.

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Content standards enforcement

When a buyer includes a content_standards_ref in a get_products or create_media_buy request, they are asking you to enforce brand suitability rules during delivery. Your responsibilities: fetch the standards from the referenced governance agent, evaluate whether you can enforce them, reject the buy if you cannot, and calibrate your local evaluation model against the governance agent via calibrate_content. After delivery, push content artifacts back to the buyer so they can validate compliance independently. If you cannot meaningfully enforce a buyer’s content standards, reject the buy rather than accepting it and failing silently. See the content standards implementation guide for the full sales agent workflow.

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Creative governance

Buyer agents may require creative evaluation before delivery — security scanning, content categorization, or quality scoring. As a seller, you participate by submitting creative manifests to governance agents via get_creative_features and honoring the feature requirements the buyer sets (for example, blocking creatives flagged for auto_redirect or credential_harvest). You do not need to implement the evaluation yourself; specialist governance agents handle that. See the creative governance overview for the feature-based evaluation model and multi-agent collaboration pattern.

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For AI media sellers: generation-time enforcement

Traditional sellers apply governance as a post-delivery filter — classify content, then block what fails. AI media platforms generate creative at serve time, which means governance rules can be enforced during generation rather than after the fact. When a buyer pushes content standards, apply them as constraints on your generation pipeline so unsuitable content is never produced. This gives brands a fundamentally stronger guarantee: suitability is built into the output, not bolted on as a check afterward. See the AI media guide for how content standards integrate with catalog-driven creative generation.

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How it connects to your existing stack

AdCP sits alongside your existing APIs and dashboards. It doesn’t replace your self-serve platform or your internal campaign management system. It adds a standard interface that AI agents can use.

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Getting started