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Shopify Admin GraphQL Gateway MCP

by samson10504

Shopify Admin GraphQL Gateway MCP

A security-focused MCP stdio server for a restricted LibreChat agent. It obtains short-lived Shopify Admin API tokens internally, permits read-only GraphQL by default, and puts mutations behind a preview plus one-time confirmation flow.

The gateway does not search documentation itself. Configure Shopify's separate Dev MCP beside it so the agent can search current docs and introspect the selected Admin API schema before sending a query to this gateway:

LibreChat agent
  ├─ Shopify Dev MCP (documentation and schema; no store credentials)
  └─ Shopify Admin Gateway (fixed store and API version; credentials stay server-side)

Security model

  • The store origin is always https://<shop>.myshopify.com. The model cannot provide a domain, URL, API version, client credential, or access token.

  • Shopify client credentials and cached access tokens exist only in the gateway process. They are never tool inputs or outputs.

  • shopify_admin_graphql_query parses the GraphQL document and only accepts a selected query operation. It rejects mutations and subscriptions.

  • Tool schemas are strict. There is no generic HTTP, REST, shell, filesystem, or environment-reading tool.

  • Token scopes must exactly match SHOPIFY_ALLOWED_SCOPES. This prevents a broader app token from silently widening the gateway's authority.

  • Mutation execution defaults off. A preview is bound server-side to the authenticated LibreChat user, normalized query hash, canonical variables hash, configured store, and expiry. Tokens are HMAC-authenticated, one-time, and held only in memory. LibreChat's native human-in-the-loop policy requires approval before it invokes the execute tool.

  • Audit logs contain operation/resource identifiers and outcome, not mutation variables, secrets, or full customer data.

  • Cursor pagination is opt-in, bounded by page size, page count, and an overall timeout. Rate-limit extensions are preserved.

  • Product counts use productsCount; they are never inferred from a paginated product connection.

The process never loads .env or /opt/data/.env. Supply environment variables through the process supervisor or container orchestrator.

Related MCP server: Shopify MCP

Shopify app setup

The OAuth client-credentials grant works only for an app developed by the same Shopify organization that owns the store and installed on that store. Public and externally owned custom apps must use a different OAuth flow; this gateway intentionally does not implement those flows.

  1. In Shopify's Dev Dashboard, create an app owned by your organization.

  2. Configure only the Admin API scopes the gateway needs.

  3. Release/install that app on the target store.

  4. Copy the app's client ID and client secret into the server-side deployment environment.

For the read-only example configuration, grant exactly:

read_products,read_inventory,read_orders

The token endpoint's returned scope set must exactly match SHOPIFY_ALLOWED_SCOPES. If you later enable a mutation, add only its documented write scope to both the app and the allowlist. Preview uses an exact-name catalog and rejects every mutation name it does not recognize; it does not infer scope from a broad prefix. The initial catalog covers productCreate, productUpdate, productDelete, productSet, inventoryAdjustQuantities, inventorySetQuantities, orderUpdate, draftOrderCreate, customerUpdate, discountCodeBasicCreate, fileCreate, and metaobjectCreate. Verify each catalog result against Shopify Dev MCP/current documentation whenever the API version changes.

Environment variables

Variable

Required/default

Purpose

SHOPIFY_STORE_DOMAIN

Required

Accepts your-store or your-store.myshopify.com; schemes, paths, ports, and other domains are rejected.

SHOPIFY_CLIENT_ID

Required

Server-side Shopify app client ID.

SHOPIFY_CLIENT_SECRET

Required

Server-side Shopify app secret. Never expose it to LibreChat's model or Code Interpreter.

SHOPIFY_API_VERSION

2026-07

Fixed quarterly Admin API version. Must use YYYY-01, YYYY-04, YYYY-07, or YYYY-10.

SHOPIFY_ALLOWED_SCOPES

Required

Comma-separated exact scope allowlist.

SHOPIFY_ENABLE_MUTATIONS

false

Mutation execution kill switch. Preview remains available.

SHOPIFY_TOKEN_REFRESH_BUFFER_SECONDS

300

Refresh before token expiry.

SHOPIFY_REQUEST_TIMEOUT_MS

30000

Overall request/pagination deadline, from 1–120 seconds.

SHOPIFY_MAX_PAGE_SIZE

100

Maximum first or last, capped at 250.

SHOPIFY_MAX_PAGES

10

Maximum pages in one tool call, capped at 100.

SHOPIFY_CONFIRMATION_TTL_SECONDS

300

Mutation confirmation lifetime, from 30–900 seconds.

SHOPIFY_LIBRECHAT_USER_ID

Empty

Trusted authenticated user identity. Required for mutation preview/execution.

SHOPIFY_LIBRECHAT_AGENT_ID

Empty

Trusted active-agent identity. Required for mutation preview/execution and recorded in audits.

See .env.example. It is a template only; the application does not load it.

Local development

Node.js 20 or newer is required. Every build dependency is pinned and the lockfile fixes the transitive dependency graph. The published CLI is a single bundled executable with no runtime package dependencies.

npm ci --ignore-scripts
npm run check

For a local stdio run, export the variables in your shell and run:

npm run build
npm start

Do not type protocol messages into the stdio process manually. Use an MCP client or Inspector. Logs go only to stderr because stdout is reserved for MCP.

Tools

shopify_admin_graphql_query

Required input: query. Optional inputs: variables, operationName, and bounded pagination.

For automatic pagination, the query must use variable-backed first and after arguments and select pageInfo { hasNextPage endCursor }. Tell the gateway where the connection appears below data:

{
  "query": "query Products($first: Int!, $after: String) { products(first: $first, after: $after) { nodes { id title } pageInfo { hasNextPage endCursor } } }",
  "operationName": "Products",
  "variables": {},
  "pagination": {
    "connectionPath": ["products"],
    "pageSize": 50,
    "maxPages": 3
  }
}

The response includes data, errors, extensions, httpStatus, apiVersion, operationName, and Shopify's request ID when present. Preserving httpStatus ensures a non-2xx GraphQL envelope cannot be audited as a successful mutation. Paginated results also include pagesFetched, partial, limitReached, hasNextPage, and rate-limit snapshots. The gateway concatenates nodes and/or edges at the specified connection path.

Do not paginate for counts. Use Shopify count fields or shopify_admin_product_counts.

shopify_admin_product_counts

Runs five aliased productsCount(limit: null, ...) fields for total, active, draft, archived, and unlisted products. Explicit limit: null avoids Shopify's default 10,000-count cap. It returns each count and Shopify's precision.

Mutation approval flow

  1. The agent searches Shopify Dev MCP and prepares exactly one top-level mutation.

  2. Call shopify_admin_graphql_preview_mutation. Nothing is sent to Shopify.

  3. The user reviews the mutation name, complete requested variables, required scope catalog result, resource IDs, and change summary.

  4. Call shopify_admin_graphql_execute_mutation with only the confirmation token. LibreChat interrupts the agent before invoking the tool and shows its native approve/reject UI.

  5. After explicit approval, the gateway checks the kill switch, authenticated user/agent, token MAC, expiry, store binding, query hash, variables hash, and one-time preview record before sending the stored mutation.

Direct execution is impossible because the execute tool accepts no query or variables. A token is consumed before execution and cannot be replayed, including after a failed Shopify request.

The supplied LibreChat configuration enables its durable human-in-the-loop toolApproval policy, allows the read/preview tools, and places only shopify_admin_graphql_execute_mutation on the ask list. It uses the exact normalized runtime name LibreChat assigns to that MCP tool. In @librechat/agents 3.4.x, an explicit ask rule wins over allow and every mode except deny, including bypass. MongoDB checkpoints allow a paused approval to resume. Pin and retest LibreChat before enabling mutations or upgrading it.

LibreChat configuration

The complete configuration is in config/librechat.yaml. The gateway block is:

mcpServers:
  shopify-admin-gateway:
    type: stdio
    command: npx
    args:
      - -y
      - 'shopify-admin-graphql-gateway-mcp@1.0.0'
    env:
      SHOPIFY_STORE_DOMAIN: '${SHOPIFY_STORE_DOMAIN}'
      SHOPIFY_CLIENT_ID: '${SHOPIFY_CLIENT_ID}'
      SHOPIFY_CLIENT_SECRET: '${SHOPIFY_CLIENT_SECRET}'
      SHOPIFY_API_VERSION: '${SHOPIFY_API_VERSION}'
      SHOPIFY_ALLOWED_SCOPES: '${SHOPIFY_ALLOWED_SCOPES}'
      SHOPIFY_ENABLE_MUTATIONS: '${SHOPIFY_ENABLE_MUTATIONS}'
      SHOPIFY_TOKEN_REFRESH_BUFFER_SECONDS: '${SHOPIFY_TOKEN_REFRESH_BUFFER_SECONDS}'
      SHOPIFY_LIBRECHAT_USER_ID: '{{LIBRECHAT_USER_ID}}'
      SHOPIFY_LIBRECHAT_AGENT_ID: '${SHOPIFY_LIBRECHAT_AGENT_ID}'
    chatMenu: false
    timeout: 60000
    initTimeout: 30000
    serverInstructions: |
      Use Shopify documentation tools first when available.
      Use read-only Shopify queries by default.
      Never execute mutations without preview and explicit confirmation.
      Never expose credentials or tokens.

The companion Shopify Dev MCP is pinned in the supplied configuration as @shopify/dev-mcp@1.14.4. It has no store credentials and cannot execute against the store.

LibreChat exposes MCP tools to its policy layer as <tool>_mcp_<normalized-server>. Therefore the protected execute name is shopify_admin_graphql_execute_mutation_mcp_shopify-admin-gateway; a policy string in the form mcp:<server>:<tool> does not match. The supplied exact ask rule enforces the correct name.

{{LIBRECHAT_USER_ID}} causes LibreChat to create a user-scoped stdio process, allowing that user's in-memory preview record to remain available during approval. Set SHOPIFY_LIBRECHAT_AGENT_ID to the immutable ID of the one restricted agent receiving these tools, and enforce that assignment with LibreChat ACLs. Treat both generated values as trusted identity assertions: users and models must not be able to edit the MCP definition. Mutations fail closed if either identity is absent or unresolved.

Keep chatMenu: false, assign both MCP servers only to the restricted agent through LibreChat's role/resource ACLs, prevent normal users from adding arbitrary MCP servers, and keep Code Interpreter credentials/filesystem separate from the LibreChat API process.

Publish and install with npx

The repository is publish-ready under the currently available unscoped name shopify-admin-graphql-gateway-mcp. Publishing is deliberately not automated because it changes external state:

npm login
npm run check
npm publish

An unscoped npm package is public. The package contains executable code and documentation only—never Shopify credentials—but review your organization's policy before publishing. Its UNLICENSED declaration is intentional until the owner chooses a source license; make that choice explicitly before a public release. For a private package, first change name in package.json to a scope your organization owns, such as @your-company/shopify-admin-gateway, set publishConfig.access to restricted, update the exact package name in config/librechat.yaml, and configure registry authentication only in the LibreChat API container.

The prepack lifecycle rebuilds and type-checks the package. npm run package:check creates the real tarball, verifies that source, tests, configuration, and environment files are excluded, installs it without lifecycle scripts or network dependencies, and executes the installed CLI through its generated npm binary.

After publishing, the supplied configuration needs no custom LibreChat image: npx -y shopify-admin-graphql-gateway-mcp@1.0.0 downloads and runs the exact package version inside the LibreChat API process. Keep the package version pinned and review upgrades before changing it. This convenience depends on npm registry availability and gives the credential-holding LibreChat API container outbound registry access; use a controlled registry/cache or the preinstalled Docker alternative below when production policy requires a smaller supply-chain surface.

Docker deployment

Build the pinned, non-root runtime image:

docker build -t shopify-admin-gateway:1.0.0 .

Docker remains an alternative for environments that do not permit runtime npm downloads. Because stdio MCP servers are child processes, the gateway must be present inside the LibreChat API container that launches it. Do not mount the Docker socket or a host source directory. In your controlled LibreChat API Dockerfile, use this repository's build stage and copy the immutable runtime tree into /app/shopify-admin-gateway, then change the gateway MCP command from npx back to node /app/shopify-admin-gateway/dist/index.js:

FROM shopify-admin-gateway:1.0.0 AS shopify_gateway

# Replace this line with your pinned LibreChat API image.
FROM your-pinned-librechat-api-image
USER root
COPY --from=shopify_gateway --chown=node:node /app/shopify-admin-gateway /app/shopify-admin-gateway
USER node

Inject Shopify variables through your secret manager/orchestrator into the LibreChat API container. Do not bake them into either image, place them in librechat.yaml, mount a host .env, or expose them to the Code Interpreter container.

Read-only validation

Start with SHOPIFY_ENABLE_MUTATIONS=false, then verify:

  1. shopify_admin_product_counts returns plausible values and precision.

  2. A small query such as query ShopName { shop { name } } succeeds.

  3. A mutation sent to shopify_admin_graphql_query returns MUTATION_REJECTED.

  4. Mutation preview returns a token but execute returns MUTATIONS_DISABLED.

  5. Logs and tool responses contain neither the client secret nor the access token.

Run the automated suite with npm test. It covers token acquisition/caching/refresh, invalid credentials/domain, query responses/errors, mutation rejection/preview/confirmation/execution, scope enforcement, product statuses, pagination limits, rate-limit retry/preservation, and secret redaction.

Audit logs

Each mutation attempt that passes confirmation validation writes one JSON line to stderr:

{"level":"audit","event":"shopify_mutation","timestamp":"2026-08-07T16:00:00.000Z","userId":"...","agentId":"...","operationName":"UpdateProduct","mutationName":"productUpdate","resourceIds":["gid://shopify/Product/123"],"success":true}

Send stderr to your centralized log collector with access controls and retention appropriate for operational audit data. Query payloads, mutation variables, response bodies, secrets, and customer records are deliberately excluded.

Security limitations

  • Scope control is the primary authorization boundary. A valid read query can access any field allowed by the app's scopes; this version does not implement a per-field or per-resource policy engine.

  • read_orders and similar scopes can expose personal data. Give the LibreChat agent only the scopes and audience it genuinely needs, and apply data retention controls to chat histories.

  • Stdio MCP has no standard end-user authentication of its own. Mutation identity relies on LibreChat's trusted user-scoped environment substitution and locked administrator configuration.

  • A confirmation token proves preview continuity, not human intent by itself. Human intent is enforced by LibreChat's native HITL ask rule before the MCP call. Do not expose the mutation execute tool through a host that lacks an equivalent approval boundary.

  • Confirmation state and Shopify tokens are in memory. A restart safely invalidates confirmations and causes a fresh Shopify token exchange.

  • Required scopes come from a deliberately small exact-mutation-name catalog; unsupported names fail closed. Verify catalog entries through Shopify Dev MCP/current Shopify documentation whenever the API version changes.

  • Automatic pagination supports one explicitly identified connection and merges its nodes/edges. Complex multi-connection queries should be split into smaller operations.

  • Rate-limit responses can still occur. Read queries retry one HTTP 429 within the total timeout; mutations are never automatically retried because doing so could duplicate a write.

  • This version intentionally has no arbitrary REST facility. Add a narrowly scoped REST operation only for a documented GraphQL gap.

References

Available Tools

4 tools
shopify_admin_graphql_execute_mutationExecute confirmed Shopify Admin GraphQL mutationA
Destructive

Executes a previously previewed mutation using its one-time confirmation token. Disabled unless SHOPIFY_ENABLE_MUTATIONS=true.

ParametersJSON Schema
NameRequiredDescriptionDefault
confirmationTokenYes

TDQS

A4.2/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare destructiveHint=true and readOnlyHint=false, so the mutation behavior is known. The description adds useful context about the one-time token and environment gating, but does not elaborate on side effects or error behavior beyond what annotations imply.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is two short sentences that front-load the core purpose and immediately follow with the critical prerequisite. Every part is necessary and no irrelevant details are included.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the single parameter, sibling tools, and annotations, the description covers the essential workflow and gating requirement. It does not explain response payloads, but this is acceptable given the execution-oriented nature and lack of output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema only provides format constraints for confirmationToken, but the description explains its meaning as a one-time token from a previously previewed mutation. This adds semantic clarity that compensates for the 0% schema description coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb-resource pair: 'Executes a previously previewed mutation' and identifies the one-time confirmation token as the key input. This clearly distinguishes it from the sibling preview mutation and query tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description clearly states that this tool is for executing a mutation that was already previewed, implying that preview_mutation should be used first. It also mentions the SHOPIFY_ENABLE_MUTATIONS=true prerequisite, giving clear context for when the tool is available.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

shopify_admin_graphql_preview_mutationPreview Shopify Admin GraphQL mutationA

Validates but does not execute exactly one Shopify mutation. Returns the variables, estimated scopes, affected resource IDs, change summary, and a short-lived user-bound confirmation token.

ParametersJSON Schema
NameRequiredDescriptionDefault
queryYes
variablesNo
operationNameNo

TDQS

A4.1/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the key non-execution behavior and lists the output (variables, scopes, IDs, change summary, confirmation token). This goes beyond a simple 'validates' by explaining what the user can expect, though it omits details like error handling or rate limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, tightly worded sentence. It front-loads the most critical information (validates, does not execute) and lists the key return values efficiently. There is no wasted verbiage.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity and absence of output schema or annotations, the description covers the essential aspects: what it does, what it returns, and the confirmation token. It does not explain how the token should be used for a subsequent execution, but that is outside the immediate scope of a preview tool. Overall, it provides enough context for an agent to invoke the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema has zero description coverage for its three parameters. The description does not explain the query, variables, or operationName parameters beyond the tool's overall purpose. It does not add syntax, format, or usage details for these inputs, leaving the agent to infer from the parameter names alone.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool validates but does not execute a Shopify mutation, using a specific verb ('validates') and resource ('Shopify mutation'). It also differentiates from the sibling execute_mutation by explicitly noting it does not execute, making the purpose unambiguous.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use this tool: when you need to validate or preview a mutation without executing it. The contrast with execute_mutation is implicit rather than explicit, but the context is clear enough that an agent would know to use this for dry-run validation.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

shopify_admin_graphql_queryShopify Admin GraphQL queryA

Executes one read-only Shopify Admin GraphQL query against the configured store. The store and API version cannot be overridden. Optional bounded cursor pagination requires explicit connection metadata.

ParametersJSON Schema
NameRequiredDescriptionDefault
queryYesA Shopify Admin GraphQL operation. URLs and credentials are not accepted.
variablesNoOptional GraphQL variables as a JSON object.
paginationNo
operationNameNo

TDQS

A4.2/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full burden. It discloses that the operation is read-only, cannot override the store/API version, and that pagination is bounded and requires explicit connection metadata. These are meaningful behavioral constraints. However, it omits response format, error handling, and authentication expectations, which would have made it more transparent.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, front-loaded with the core action and scope. Every sentence provides useful information: the first states what and how, the second adds limitations and pagination requirements. No fluff or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (4 parameters, nested objects, no output schema) and lack of annotations, the description covers the key constraints: read-only, single query, store/API fixed, pagination boundary. It falls slightly short by not mentioning expected return shape or error behavior, but for a raw GraphQL execution tool the most critical contexts are addressed.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is only 50%, so the description must compensate. It explicitly associates 'query' with the GraphQL operation and adds the crucial constraint that pagination requires explicit connection metadata. However, it does not clarify the 'variables' or 'operationName' parameters, leaving them to the schema. Thus it adds some value but does not fully compensate for the coverage gap.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific action ('Executes'), a clear resource ('Shopify Admin GraphQL query'), and a key scope ('read-only', 'against the configured store'). It clearly distinguishes itself from sibling mutation tools by emphasizing read-only, and from product_counts by being a general query tool.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context: it is read-only, executes a single query, and the store/API version cannot be overridden. While it doesn't explicitly name alternative tools, the read-only label implicitly tells the agent not to use this for mutations, and the mention of 'one query' sets expectations. No exclusions are stated, but the context is useful.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

shopify_admin_product_countsShopify product counts by statusA

Uses productsCount—not paginated products—to return total, active, draft, archived, and unlisted product counts.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A4.3/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description discloses the underlying method (productsCount) and the output categories, which helps. However, with no annotations, it does not mention whether this is read-only, any rate limits, or how counts are calculated. It leaves some behavioral aspects unstated.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence that efficiently conveys the method and the list of counts returned. It contains no filler and is easy to parse.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple, no-parameter tool, the description is complete: it specifies what it does, how it does it, and what the output includes. The absence of an output schema is offset by the explicit enumeration of counts, and no further context seems necessary.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has zero parameters, and the schema reflects that. Baseline for zero parameters is 4; the description does not need to add parameter semantics, and it doesn't, which is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: returning total, active, draft, archived, and unlisted product counts using the productsCount method. It explicitly distinguishes itself from paginated product queries and from generic GraphQL operations, making it unique among siblings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The phrase 'Uses productsCount—not paginated products' implies that for product count needs, this tool should be used instead of paginating through products via GraphQL. This gives clear context, though it stops short of explicitly naming when-not-to-use or listing alternative tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. 4 tool updatesv1.0.0
    • First observedshopify_admin_graphql_execute_mutation
    • First observedshopify_admin_graphql_preview_mutation
    • First observedshopify_admin_graphql_query
    • First observedshopify_admin_product_counts

TDQS

A4.4/5.0
Disambiguation5/5

Each tool has a clearly distinct purpose: product counts, read-only queries, mutation preview, and mutation execution. There is no overlap or ambiguity between them.

Naming Consistency4/5

All tools share the consistent 'shopify_admin' prefix and use snake_case. The three GraphQL tools follow a clear 'graphql_<action>' pattern, but 'product_counts' deviates as a noun phrase rather than a verb_noun structure.

Tool Count5/5

With only 4 tools, the server is tightly scoped to its purpose as a GraphQL gateway. Each tool is necessary and covers a distinct aspect of the interaction model.

Completeness5/5

The set provides complete lifecycle coverage for the gateway domain: read operations via query, mutation handling via preview and execute, and a convenience count tool. No obvious missing operations within the stated scope.

Maintenance

ActivityMaintained
ResponsivenessNo issues

Resources

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