CatalogMCP

CatalogMCP

Enables natural-language setup and management of a governed digital product catalog, including schema, products, and rules, with dry-run previews, audit logging, and two-phase confirmations for destructive actions.

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CatalogMCP

CI

Setting up a digital product catalog today is either slow (click through a UI for every attribute and rule) or expensive (script it against an API, which turns labor cost into engineering cost for every future change). This is a spike proving a third option: an agent talking to a governed MCP tool surface can replace both. A catalog admin describes what they want in plain language — "add a Weight attribute in kg, required for all Industrial-line products" — and an agent executes it through tools that preview, log, and gate every change. Setup becomes a conversation instead of a UI marathon or an engineering ticket.

Demo

šŸŽ„ Watch the recorded demo — screen recording of the exact run described below.

The scripted client in demo/client.ts drives this server through a real Claude tool-use loop (Anthropic Messages API, no mocking) and walks through:

  1. Browsing the empty catalog.
  2. A natural-language request to set up the catalog from an attached file of products and their attribute values — including the schema (attributes, a required-for-industrial-line rule) the import depends on.
  3. A dry-run preview surfacing two rows that fail validation, a back-and-forth to fix them, then a real commit of all five products.
  4. Reading the audit log the commit produced.
  5. Browsing the catalog again, now populated — closing the loop the same way it opened, via the agent, not a human refreshing a UI.
  6. A destructive request — delete the material attribute — held for confirmation with a data-aware blast-radius disclosure (5 affected products, by name), then confirmed.
  7. A closing beat: the same request attempted against a read-only instance, cleanly refused.

The full text transcript of that same run is in demo/transcript.txt — reproducible yourself by running npm run demo.

What makes this MCP (not just an API)

MCP is a wire protocol — JSON-RPC 2.0 messages over a transport (stdio here; HTTP/SSE elsewhere) — not a coding convention. A small, fixed set of method names is standardized by the spec itself, so any compliant client (Claude Desktop, this repo's own demo/client.ts, any other agent framework) can talk to this server without knowing anything about catalogs, attributes, or rules ahead of time.

The protocol methods

Method Direction Purpose
initialize client → server Handshake: exchange protocol versions, negotiate capabilities
notifications/initialized client → server Client confirms it's ready
tools/list client → server Discovery — "what can you do?" Returns every tool's name, description, and JSON Schema input shape
tools/call client → server Invocation — "do this one, with these arguments"

That's the entire surface an agent needs to know in advance. There's no POST /create_attribute endpoint — an agent calls tools/call with {"name": "create_attribute", "arguments": {...}}. A trimmed real exchange with this server:

// → client
{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2024-11-05", ...}}

// ← server
{"jsonrpc":"2.0","id":1,"result":{"protocolVersion":"2024-11-05","capabilities":{"tools":{"listChanged":true}},"serverInfo":{"name":"catalog-mcp","version":"0.1.0"}}}

// → client
{"jsonrpc":"2.0","id":2,"method":"tools/list"}

// ← server — every tool below, as name + description + JSON Schema
{"jsonrpc":"2.0","id":2,"result":{"tools":[{"name":"list_attributes", ...}, ...]}}

How it works in this codebase

We never wrote a tools/list or tools/call handler. Every call to server.registerTool(name, config, handler) in src/tools/ appends to an internal registry inside @modelcontextprotocol/sdk's McpServer. The SDK answers tools/list by dumping that registry (converting our Zod schemas to JSON Schema along the way) and answers tools/call by looking the requested name up in the same registry and invoking its handler — none of that is our code. It's also why the governance layer (src/governance/governed-registration.ts) wraps registerTool itself rather than hooking into some HTTP middleware layer: that single call is the only seam every tool invocation is guaranteed to pass through.

The tools

12 tools, grouped by what they operate on. Every mutating tool accepts dryRun: true for a no-persist preview; full argument shapes are in src/tools/.

Schema (catalog structure — attributes, rules)

Tool Args Mutating?
list_attributes — no
get_attribute name no
create_attribute name, type, enumValues?, unit?, dryRun? yes
update_attribute name, type?, enumValues?, unit?, dryRun? yes
delete_attribute name, confirmToken? yes — destructive, two-phase
list_rules — no
create_rule attributeName, productLines, dryRun? yes

Content (actual products)

Tool Args Mutating?
list_products — no
get_product sku no
import_products rows, dryRun? yes — bulk, upsert, partial-commit
set_attribute_value sku, attributeName, value, dryRun? yes

Governance

Tool Args Mutating?
list_audit_log — no

Why the guardrails aren't optional

Nobody hands an ungoverned agent write access to a live product catalog. The preview/audit/approval layer isn't a safety feature bolted on afterward — it's the precondition that makes "just describe what you want" viable for something you can't afford to get wrong. Concretely, this server never lets a mutation happen blind:

  • Dry-run preview — every mutating tool accepts dryRun: true and returns the exact outcome without persisting anything.
  • Audit log — every tool call is recorded (timestamp, tool, args, actor, outcome) and readable via its own tool, not just claimed to exist.
  • Two-phase confirm on destructive ops — deleting an attribute first returns a blast-radius disclosure (a count and a sample of affected products) and a token; only a second call with that token executes, and if the catalog changed in between, the stale token is refused rather than honored.
  • Policy mode — the server can run fully read-only, refusing every mutating tool at the gate, for a locked-down deployment.

See CONTEXT.md for the domain glossary and CLAUDE.md for the full scope, tool surface, and explicit non-goals.

Setup

npm install
npm test     # domain, tool, and governance tests, plus the 6-step demo acceptance test
npm run dev  # start the MCP server over stdio (add --read-only to lock it down)
npm run demo # run the scripted Claude-driven demo client (needs ANTHROPIC_API_KEY)

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