Your catalog, in every AI client you already use.
MCP (Model Context Protocol) is how external AI clients — Claude, ChatGPT, Gemini, Cursor, and your IDE — call search_products, quick_publish, and 90+ other tools against your live tenant catalog, with your permissions.
In-platform specialist agents in the Agent Control Center use the same governed catalog, with persistent insights, an approval queue, and Catalog Quality monitoring. MCP and ACC complement each other — ACC for autonomous operations inside PIM; MCP for conversational and IDE-integrated workflows.
Traditional PIMs export CSVs for chatbots. CataZenta exposes named, typed tools on the same Agentic PIM layer as the UI, syndication workers, and specialist agents — not a separate shadow catalog.
Three ways to use catalog AI
| Mode | Where | Best for |
|---|---|---|
| MCP (this page) | Claude, ChatGPT, Cursor, VS Code | Conversational ops, IDE automation, ad-hoc tool chains |
| Specialist agents | Agent Control Center | Scheduled runs, missions, insights, approval queue |
| Zen AI | Chat inside PIM | Inline assistant on product pages — same MCP tools as external clients |
All three operate on the same governed catalog. Writes from MCP are auditable API calls; in-platform agent writes default to the approval queue.
What you can do
| Use case | Example prompts | Example tools |
|---|---|---|
| Catalog Q&A | “Show products in Footwear missing SEO titles” | search_products, get_product_attributes |
| Enrichment | “List SKUs below 70% completeness in Brand X” | find_products_needing_enrichment, analyze_product_completeness |
| Approvals | “What agent proposals are pending review?” | Query via ACC in PIM; use list_tasks for workflow gates |
| Syndication | “Publish these IDs to Shopify and report failures” | list_connections, quick_publish, get_export_job_items |
| Governance | “What workflow tasks are open for my team?” | list_tasks, get_my_tasks, list_workflows |
| Analysis | “Compare these two products side by side” | compare_products, get_product_completeness |
| Media | “List assets in the Spring campaign folder” | list_dam_folders, list_assets |
| Bulk ops | “Create an export job for all active SKUs in category …” | search_products, create_export_job, start_export_job |
Copy-paste prompts and multi-step patterns → Agent workflows · Automation examples
How it works
Your AI client discovers tools from the MCP endpoint, calls them with structured arguments, and receives JSON the model can parse. Every tool maps to the same REST APIs the PIM UI uses — scoped to your tenant and roles.
Use a non-production tenant when testing write tools (set_product_attribute, quick_publish, create_product). Hosted and local connectors both respect tenant boundaries.
Connection options
| Option | Best for | Setup |
|---|---|---|
| Hosted MCP (recommended) | Claude.ai, ChatGPT | Add URL + OAuth sign-in — no local install |
| Local MCP connector | Claude Desktop, Cursor, VS Code, Windsurf | Optional package from CataZenta onboarding |
MCP URL: https://api.catazenta.com/mcp
Credentials and connector packages are provided when your tenant is enabled for MCP (same API host as the REST API).
Hosted MCP
Connect in the AI app with the URL above. Sign in when prompted — same identity as the PIM.
Local connector
Run the CataZenta MCP connector on your machine for Desktop and IDE clients.
Also supported
Any MCP-compatible client that supports Streamable HTTP or stdio transport.
Tool coverage
90+ tools across twelve capability areas — all returning JSON for the model to parse. Parameter names and types are defined in the MCP tool schema exposed to your client.
Catalog core
Products, variants, families, attributes, categories.
search_productsset_product_attributelist_categories
Quality & analysis
Completeness, enrichment gaps, comparisons.
analyze_product_completenessfind_products_needing_enrichmentcompare_products
Syndication
Channels, export jobs, quick publish.
list_connectionsquick_publishcreate_export_job
Operations
DAM, jobs, workflows, tasks, dashboard.
list_assetscreate_taskget_dashboard_stats
Full catalog with every tool name → MCP tools reference
Authentication
| Option | How it works |
|---|---|
| Hosted (Claude / ChatGPT) | Add MCP URL → OAuth sign-in → Bearer token on each request — same account and tenant as PIM |
| Local connector | Username/password or API token from onboarding — prefer a dedicated integration user with least privilege |
Hosted clients discover OAuth settings from the MCP endpoint automatically. Tokens are scoped to your organization; the assistant only sees data your roles allow — identical to REST API authentication.
Security practices
- Use HTTPS only (
https://api.catazenta.com) - Rotate passwords and tokens on the same schedule as other integrations
- Control which AI apps may use write-capable tools in your organization
- Use workflow tasks and ACC approvals for regulated catalog changes
Details → MCP authentication · Security
Agent workflow patterns
Pre-built tool chains for reliable automations — not one-off chat messages.
| Pattern | Tool chain | Guide |
|---|---|---|
| Catalog audit | find_products_needing_enrichment → analyze_product_completeness → create_task | Agent workflows |
| Publish bot | list_connections → quick_publish → get_export_job_items | Publish workflow |
| Content agent | get_product → set_product_attribute → get_product_completeness | Automation examples |
Require PIM workflow sign-off before setting update_product_status to active in regulated catalogs. In-platform agent proposals use the ACC approval queue; MCP writes are immediate API calls — design guardrails accordingly.
MCP vs Agent Control Center
| MCP clients | Agent Control Center | |
|---|---|---|
| Interaction | Conversational / IDE tool calls | Autonomous runs, schedules, missions |
| Persistence | Session-driven; you orchestrate chains | Insights, approval queue, Catalog Quality |
| Writes | Named tool calls, API-auditable | Proposals → approve → apply |
| Best for | Ad-hoc ops, developer automation | Continuous catalog intelligence at scale |
Both complement each other on the same Agentic PIM platform → Agent Control Center · AI agents (MCP clients)
Get started
- Confirm MCP is enabled for your tenant (contact CataZenta if needed).
- Follow the MCP quickstart — hosted URL or local connector.
- Pick your client guide (Claude, ChatGPT, Cursor, …).
- Test read-only: “Search for 5 products in my catalog.”
- Test analysis: “Find products below 70% completeness in category …”
- Wire write tools only after sandbox validation.
- Combine with ACC for persistent findings and governed agent writes.
MCP URL: https://api.catazenta.com/mcp
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