GridShot MCP gives AI agents a governed, end-to-end fashion production workflow: find the right model and garments, generate try-on grids, review the candidates, refine, and deliver publish-ready images — while you keep budget, permissions, and approvals in your hands. An operator layer for fashion production, not another image endpoint.
https://mcp.grid-shot.com/mcpThe real work is everything around the pixels: finding the right product, tracking outfit state, polling long jobs, reviewing candidates, retrying, editing, and delivering the final file. GridShot MCP hands agents that whole workflow, not just a render call.
An agent has to find the exact garment and the right model before it can generate anything. GridShot exposes searchable catalog and model discovery, so the agent works from your real inventory instead of guessing.
Try-on generation is asynchronous. Grids queue, run, and sometimes wait for approval. The agent polls a single operation for status and knows exactly when a result is ready — no brittle timing assumptions.
Production means reviewing candidates, refining what is close, editing what needs a fix, and delivering one high-resolution file. Each of those is a full step of its own, with its own cost and its own controls.
A single agent run moves from catalog lookup to a delivered, high-resolution image. Every step is a discrete, observable tool call.
gridshot.search_modelsgridshot.search_garmentsFind the model and garments in your catalog
gridshot.estimate_tryonFreePreview the cost before spending anything
gridshot.create_tryonIdempotency-Keymax_cost_centsGenerate a try-on grid with a spend ceiling
gridshot.get_operationqueuedrunningcompletedPoll one operation until the grid is ready
gridshot.get_grid_previewgridshot.get_candidate_previewReview the grid and its individual candidates
gridshot.refine_gridRefine the grid when a look is close but not final
gridshot.deliver_candidateDeliver the chosen shot in high resolution






These are real outputs from this workflow, produced with the same tools an agent calls.
Sixteen tools cover the full production arc — discovery, composition, generation, review, refinement, and delivery.
Search your model library and garment catalog to pick the exact pieces a shot needs.
gridshot.search_modelsgridshot.search_garmentsAssemble a model with one or more garments and preview the cost before any spend.
gridshot.estimate_tryonCreate a try-on grid of candidates and track the asynchronous job through to completion.
gridshot.create_tryongridshot.get_operationPull the finished grid and inspect individual candidates through short-lived preview links.
gridshot.get_grid_previewgridshot.get_candidate_previewRefine a grid into a sharper one, or apply a targeted, coordinate-based edit to a single artifact.
gridshot.refine_gridgridshot.edit_artifactTurn the approved candidate into one publish-ready, high-resolution image.
gridshot.deliver_candidateA raw image endpoint answers one question: render this. Production needs the questions around it answered too.
Takes an input, returns pixels. Your agent still has to find products, hold outfit state, invent polling, build review and retry logic, and figure out delivery — all on its own.
Discovery, cost estimation, generation, polling, review, refinement, and delivery are all modeled as tools over shared workspace state. The agent orchestrates a workflow instead of stitching one together.
Agents move fast; you stay in control. Spend, permissions, approvals, and history are enforced by GridShot, not by the agent.
max_cost_centsEvery paid action carries a maximum cost you set. If the real cost would exceed that ceiling, the call is refused rather than charged.
Each connection is limited to the scopes it was granted. An agent given read access to your catalog can never spend or deliver on your behalf.
approval_requiredSome jobs pause and wait for a human decision before they continue, so a run can require sign-off instead of proceeding unattended.
Every product, model, job, and asset an agent touches is the same record your team sees in the app — visible, attributable, and reviewable after the fact.
The products, models, jobs, and assets an agent works with over MCP are the exact same ones you manage in the GridShot app and over REST. No separate agent silo, no divergent state — one workspace, whether a person or an agent is driving.
Sixteen tools, grouped by the permission scope each one requires. Estimates and previews are free; just four tools ever spend.
No scopegridshot.get_capabilitiesFreeReport the tools, scopes, and limits the current connection can use.
catalog:readgridshot.search_modelsFreeSearch your model library for the right cast for a shot.
gridshot.search_garmentsFreeSearch your garment catalog for the exact products to feature.
tryon:readgridshot.get_operationFreeCheck the status of an asynchronous job and learn when to poll again.
gridshot.get_gridFreeRetrieve a finished grid and its candidates.
gridshot.get_grid_previewFreeGet a short-lived preview link for a whole grid.
gridshot.get_candidate_previewFreeGet a short-lived preview link for a single candidate.
tryon:generatetryon:readgridshot.estimate_tryonFreePreview the cost of a try-on grid before generating it.
gridshot.create_tryonPaidGenerate a grid of try-on candidates from a model and garments.
gridshot.estimate_refinementFreePreview the cost of refining an existing grid.
gridshot.refine_gridPaidGenerate a refined grid from an existing one.
candidate:delivertryon:readgridshot.estimate_deliveryFreePreview the cost of delivering a candidate in high resolution.
gridshot.deliver_candidatePaidProduce one publish-ready, high-resolution image from a chosen candidate.
artifact:edittryon:readgridshot.preview_annotationsFreePreview coordinate-based annotations on an artifact before editing it.
gridshot.estimate_editFreePreview the cost of a targeted edit to an artifact.
gridshot.edit_artifactPaidApply one targeted, coordinate-based edit to an artifact.
Read tools need just their read scope. The three write capabilities — generate, deliver, and edit — additionally require the matching read scope, so an agent can always see what it just changed. Reading capabilities needs nothing more than a valid connection.
tryon:readtryon:generatecandidate:deliverartifact:editcatalog:readA standards-based connection with OAuth, discovery, and predictable errors.
https://mcp.grid-shot.com/mcp2025-06-18User-driven agents connect with the authorization code flow and mandatory proof-key protection; server-side workloads use the client-credentials flow. Access tokens are short-lived, and refresh tokens rotate on every use.
https://grid-shot.com/.well-known/oauth-authorization-serverThe Claude Code CLI is tested end to end — OAuth sign-in, consent, and tool calls all work. The claude.ai and Claude Desktop custom connector is provisioned as a registered client but is not yet verified. Other registered clients may connect but are not yet verified, and open client registration is disabled.
Generation runs as a job. The agent polls a single operation, which reports its state and tells the agent how long to wait before checking again.
queuedrunningapproval_requiredcompletedfailedcancelledMissing permissions, insufficient balance, and exceeded cost ceilings come back as structured tool errors that say exactly what went wrong. A retry flag tells the agent when it is safe to try again.
INSUFFICIENT_SCOPEINSUFFICIENT_WALLET_BALANCECOST_LIMIT_EXCEEDEDretryableShort-lived credentials, signed links, and scope checks on every call.
Access tokens expire within minutes, so a leaked token is useless almost immediately. Refresh tokens rotate, and a replayed one revokes its whole family.
Preview and download links are signed and short-lived, and full-resolution images are never returned inline. Agents re-request a fresh link instead of caching one.
Service-account secrets are shown exactly once and stored as a one-way digest. Rotating a secret revokes the old one immediately, with no overlap window.
Every tool verifies the connection holds the right permission before it runs. A connection can never reach beyond the scopes it was granted.
Estimates are always free. Four actions can spend money, and each one names its own price.
FreeEvery estimate and every annotation preview is free and never reserves funds or calls the image provider. An agent can plan and price a whole run before committing to anything.
PaidGenerating a grid, refining a grid, delivering a high-resolution shot, and editing an artifact are the actions that spend. One generation produces a single grid of nine candidates; delivery renders one high-resolution file. Costs are quoted in US cents.
gridshot.create_tryongridshot.refine_gridgridshot.deliver_candidategridshot.edit_artifactEvery paid action requires a cost ceiling and a uniqueness key, so retries never double-charge and spend never exceeds what you allowed.Idempotency-Keymax_cost_cents
Self-serve today — create an account, connect your agent, and run your first try-on. No approval step and no access request needed.
Sign up for GridShot in about a minute. Every new workspace starts with $10 in credit, so you can explore and run real try-ons before spending your own money.
Open Settings → MCP in the app and follow the built-in getting-started guide to connect Claude Code or create a service account for unattended, server-side workloads.
Point your agent at your catalog and generate your first 3×3 try-on grid — from catalog discovery all the way to a delivered, high-resolution shot.
It is a connection that lets AI agents run GridShot as a fashion production workflow — discovering products and models, generating try-on grids, reviewing, refining, and delivering high-resolution images — through a standard agent protocol, with your workspace controls enforced throughout.
The Claude Code CLI is verified end to end. The claude.ai and Claude Desktop custom connector is provisioned as a registered client but is not yet verified. Other registered clients may work but are not yet verified. Open client registration is turned off, so every connection is one you or a workspace admin approved.
Estimates and annotation previews are always free and never reserve funds. Four actions can spend — generating a grid, refining a grid, delivering a shot, and editing an artifact — and each one requires a cost ceiling, so an agent can never spend more than you allow.
No. This is human-governed automation. Agents do the busywork, but spend limits, permission scopes, and approval steps are enforced by GridShot, and some jobs pause for a human decision before they continue.
Create a free GridShot account — every new workspace starts with $10 in credit — then open Settings → MCP in the app. From there, follow the built-in getting-started guide to connect an MCP client or create a service account for unattended, server-side workloads. There is no approval step and no access request to file.
The tool reference on this page lists all sixteen tools, the permission scope each one requires, and which are free versus paid. It is the clearest way to understand the full surface before you connect.
GridShot MCP is in open beta — you can connect an agent today, and it is still maturing. Create a free account and put the full try-on-to-delivery workflow in reach of your agents.