shopify-chatgpt-ads-mcp
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- AlicenseNot gradedqualityDmaintenanceEnables management of OpenAI Ads campaigns, ad groups, ads, and insights through MCP, with approval-gated live mutations for safe write operations.127 npmMIT
- AlicenseNot gradedqualityCmaintenanceLets MCP clients build and manage ChatGPT ad campaigns — campaigns, ad groups, ads, budgets, bids, targeting, audiences, conversion tracking, product feeds and performance reporting — through the OpenAI Ads Advertiser API. Writes are guarded by dry-run mode, confirm words and an audit log with before-snapshots.MIT
- AlicenseNot gradedqualityBmaintenanceConnects Meta (Facebook/Instagram) ad accounts and a Shopify store to AI assistants, letting them read live campaign performance and profit after returns and, with owner approval and a 7-day undo, pause or enable ads, adjust budgets, and build new campaigns that start paused.1MIT
- AlicenseBqualityCmaintenanceEnables managing ChatGPT Advertiser campaigns from MCP-capable agents, including campaign creation, creative uploads, audience management, conversions setup, and insights retrieval.8938 npmMIT
- FlicenseNot gradedqualityCmaintenanceConnects AI assistants to Google Ads, Meta Ads, ChatGPT Ads, TikTok Ads and LinkedIn Ads so users can query live campaign performance, budgets and audiences in the account's own currency and prepare changes as proposals that only take effect after explicit approval. Reads run immediately, while every write is staged as an approvable proposal with before/after values, and newly created campaigns, ad sets and ads start paused.1-
- AlicenseNot gradedqualityCmaintenanceConnects AI agents to Shopify, Meta Ads, Google Ads, and TikTok Ads for cross-platform reporting, creative management, and approval-gated campaign and store changes.MIT
TDQS
Scored across 46 tools
The core OpenAI surface (list_campaigns, get_campaign, get_insights, list_feeds) is cleanly separated by resource and action, but the parallel Avada surface creates near-twins: list_campaigns vs measurement_list_campaigns, get_campaign vs measurement_get_campaign, get_insights vs measurement_get_ads_report, list_feed_uploads vs measurement_get_feed_status. Descriptions do draw a real distinction (OpenAI-attributed vs store-measured true ROAS, and the AVADA_API_KEY requirement), which saves it from being a 2, but an agent still has to reason carefully before choosing between two similarly named tools for the same object.
Names are consistently snake_case verb_noun (list_/get_/create_/update_/pause_/archive_/set_), and the app-side tools share a uniform measurement_ namespace prefix, which is a deliberate and predictable convention. Small friction comes from prefix-stacked names like measurement_get_campaign that duplicate the base tool's name, blurring the namespace advantage somewhat.
46 tools for a single ad account surface is heavy, and the count is inflated because two separate backends (the OpenAI Ads API and the Avada measurement app) each get a full parallel tool family. Individual tools are mostly substantive rather than trivial, but the duplication of campaign/feed/reporting tools across two surfaces pushes this well past what an agent can hold in working context.
The lifecycle is broadly covered: campaigns, ad groups and ads all have create/get/list/update/pause/archive plus activation, budget and bid controls, along with feeds, uploads, feed product edits, pixels, conversion event settings, audit logs and insights. Gaps are mostly API-imposed (no un-archive, no single-feed get, no pixel or conversion-setting creation), which agents can work around but leaves a few dead ends.