inventory-ops-mcp
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@inventory-ops-mcpInvestigate oversell for SKU-STALE-CANCEL-003 and release stale reservation."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
inventory-ops-mcp
A remotely hosted MCP server that lets an ops person investigate and resolve inventory oversells without engineer involvement.
Workflow this solves
Oversell: a SKU shows more stock reserved across open orders than it
actually has (available = total_stock - active_reservations goes
negative). Root cause is usually one of two things:
A stale reservation — an order was cancelled or expired, but its stock reservation was never released. Safe to auto-fix.
A genuine conflict between paid/open orders. Not safe to auto-fix — gets escalated to a human with an audit trail instead.
Related MCP server: fix-mcp
Project structure
db/
schema.sql tables, enums, indexes
seed.sql synthetic data covering all 4 demo scenarios
src/
config.ts env config
db/
pool.ts single shared pg.Pool for the whole process
queries/ raw SQL, grouped by domain (inventory, audit)
tools/
inventory/ one file per tool + an index.ts that registers them
index.ts top-level registry - add new categories here later
server/
createMcpServer.ts builds one McpServer instance (per session)
httpServer.ts Streamable HTTP transport, session handling
index.ts entrypointTools are grouped by domain category (tools/inventory/) rather than dumped
in one file, so a second category (e.g. tools/orders/) can be added later
without touching existing code — just create the folder, register its tools
in its own index.ts, and add one line to src/tools/index.ts.
Architecture notes
One MCP server instance per client session (Streamable HTTP, session-id based) — this is the SDK's own recommended pattern, since protocol/session state can't be safely shared across clients.
One shared
pg.Poolfor the entire process — imported by the query modules, not created per session. Sessions are isolated at the protocol layer; the database connection is not.The resolution tool (
release_stale_reservation) enforces its safety boundary in code, not by trusting the model: it refuses anything that isn't a cancelled/expired order's reservation, regardless of what the AI requests.
Setup
Create a Postgres database and set
DATABASE_URLin.env(copy.env.example).Load the schema and synthetic data:
npm run db:setupInstall dependencies and start the server:
npm install npm run devPoint an MCP client at
http://localhost:3000/mcp(or your deployed Render URL). For Claude Code:claude mcp add --transport http inventory-ops http://localhost:3000/mcp
Demo scenarios (seeded)
SKU | Situation | Expected tool path |
SKU-HEALTHY-001 | No issue |
|
SKU-OVERSELL-PAID-002 | Oversold by paid + open orders | must escalate — release refused |
SKU-STALE-CANCEL-003 | Oversold by a stale reservation (cancelled order) |
|
SKU-STALE-EXPIRED-004 | Same, order expired instead of cancelled |
|
Out of scope (explicit)
Stale physical-count reconciliation (a related but separate workflow) — not built in this pass; escalation for that case is created but not auto-resolved.
Authentication, a frontend, and CI/CD — excluded per the assignment brief.
Multi-SKU orders (one line item per order, to keep the schema simple).
Verification
See AI-WORKLOG.md (to be added) for how each tool's behavior was verified
against the seeded scenarios above.
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