AI shopping gateway for product search, inventory, carts, and merchant-hosted checkout.
Add another selected product variant to an existing Agent Checkout cart. Use when the user explicitly wants another item or quantity added to an existing cart. This does not charge the buyer.
| Name | Required | Description | Default |
|---|---|---|---|
| cart_id | Yes | ||
| quantity | No | ||
| site_slug | Yes | ||
| variant_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden. It usefully discloses a key behavioral fact: 'This does not charge the buyer,' which prevents confusion with checkout/payment tools. However, it does not explain failure behavior, idempotency, or exactly how quantity is applied (incremented vs. set), leaving behavioral transparency incomplete.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is three short sentences with no filler. Each sentence has a distinct job: state the action, provide the usage trigger, and clarify a critical non-charge behavior. The core purpose is front-loaded, making it easy to scan.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema, no annotations, and zero parameter descriptions in the schema. The description does not explain site_slug's role, the default quantity behavior, or what the tool returns. For a mutation tool with required fields and no structured safety hints, the definition is not complete enough for an agent to confidently invoke it.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It loosely connects 'product variant' to variant_id and 'existing cart' to cart_id, but it never explains site_slug or how quantity behaves when omitted. The agent is left to infer the meaning of required parameters from context, which is insufficient for a 4-parameter tool.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'Add another selected product variant to an existing Agent Checkout cart.' It clearly distinguishes this from create_cart and create_checkout by emphasizing 'existing' cart and 'another' item. The additional note that it does not charge the buyer further clarifies the tool's boundary.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides an explicit usage condition: 'Use when the user explicitly wants another item or quantity added to an existing cart.' It gives clear context for when to invoke the tool, though it does not name alternatives or explicit when-not-to-use conditions beyond what is implied by 'existing cart.'
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Check whether a selected product variant is currently sellable and available. Use when availability matters or immediately before adding a selected variant to a cart.
| Name | Required | Description | Default |
|---|---|---|---|
| site_slug | Yes | ||
| variant_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full disclosure burden. The verb 'check' and phrase 'currently sellable and available' convey that this is a read-style status query, adding meaning beyond the name. However, it doesn't disclose output format, errors, or any side-effect guarantees, leaving some behavioral details implicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences, each earning its place: the first states the action, the second the usage context. No filler or repetition; the most valuable information is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter read tool, the description covers purpose and usage well, but it omits the return shape (e.g., boolean vs stock count) and leaves site_slug undocumented. Since there is no output schema to fill that void, an agent has to guess at the result format.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate, but it only implicitly maps to variant_id via 'selected product variant'. site_slug is never mentioned or explained; the agent must infer its meaning from the parameter name alone. This is a clear gap for a tool with zero schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('check') and resource ('selected product variant') and clarifies the exact condition being tested: sellable and available. It clearly distinguishes this check from sibling cart and search tools, which operate on different resources or actions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The second sentence gives explicit guidance on when to call: 'when availability matters or immediately before adding a selected variant to a cart.' It does not mention alternatives or when not to use, but the context is clear enough for an agent to select it appropriately.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Create a new Agent Checkout-attributed cart with a selected product variant. Use only after the user has chosen a specific product or clearly asked to add/buy it. This prepares the purchase but does not charge the buyer.
| Name | Required | Description | Default |
|---|---|---|---|
| quantity | No | ||
| site_slug | Yes | ||
| variant_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations present, the description carries the transparency burden and usefully discloses that this 'prepares the purchase but does not charge the buyer.' It also notes the cart is Agent Checkout-attributed, which is non-obvious context. It could clarify effects on an existing cart or required auth state, but the no-charge disclosure is meaningful.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three short sentences, with the core action front-loaded and each sentence adding a distinct fact: what it creates, when to call it, and what it does not do. There is no filler or repetition.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a mutation tool with no annotations, no output schema, and zero schema description coverage, this is incomplete: site_slug and quantity semantics are missing, existing-cart behavior is unaddressed, and it does not indicate whether a cart identifier is returned for later create_checkout calls. It captures the high-level flow but leaves key operational details unspecified.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description needed to compensate for all parameters. It only loosely maps to variant_id via 'selected product variant' and says nothing about site_slug or quantity. An agent would still have to infer the purpose of two parameters from their names and constraints.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description gives a specific verb ('Create'), resource ('Agent Checkout-attributed cart'), and scope ('with a selected product variant'). It clearly separates this from retrieval or checkout-finalization tools by framing it as a new-cart preparation step.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly states the precondition: 'Use only after the user has chosen a specific product or clearly asked to add/buy it.' This provides strong when-not-to-use guidance. It does not name sibling alternatives like add_to_cart or create_checkout, but it still gives a clear operational trigger.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Prepare the final buyer handoff by returning the merchant-hosted HTTPS checkout URL. Use when the user has a cart and clearly wants to proceed to checkout or purchase. Always surface checkoutUrl to the human buyer. Agent Checkout never collects raw card details and this tool does not itself charge the buyer.
| Name | Required | Description | Default |
|---|---|---|---|
| cart_id | Yes | ||
| site_slug | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral burden and discloses safety-relevant behavior: it does not collect raw card details, does not itself charge the buyer, and always returns a merchant-hosted HTTPS URL. This goes beyond what the schema conveys.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Four short sentences, each contributing a distinct requirement: output form, trigger condition, buyer-facing handling, and payment-safety caveat. No filler.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a two-parameter tool with no output schema, the description covers what it returns, when to use it, and what it does not do. It falls just short of fully complete because it does not state how site_slug is determined or what happens on failure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 0% because the description never mentions cart_id or site_slug. With low coverage, the description should compensate, but it only indirectly implies cart_id through 'has a cart' and leaves site_slug entirely unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a clear verb ('Prepare') and resource ('merchant-hosted HTTPS checkout URL'), and specifies when to use it. The sentence about user wanting to proceed to checkout distinguishes this from cart-management siblings like get_cart and create_cart.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly says to use when the user has a cart and clearly wants to proceed to checkout or purchase. It does not list alternatives or state when not to use, but it gives enough context to route correctly.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Read the current Agent Checkout cart contents and totals. Use to review or confirm the cart before handing the buyer off to checkout.
| Name | Required | Description | Default |
|---|---|---|---|
| cart_id | Yes | ||
| site_slug | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full behavioral burden. The verb 'Read' plus 'contents and totals' clearly signals a non-mutating snapshot operation. It does not cover edge cases like missing carts, but for a simple getter this is adequate and contradicts nothing.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, no filler. The first sentence immediately states the operation and object, and the second gives the use case. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Purpose, usage, and return content ('contents and totals') are covered, and the tool is simple and read-only. However, parameter meanings are left to inference, and there is no guidance on error behavior or output shape beyond totals.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage, and the description does not explain what site_slug or cart_id mean or how they relate to the cart. The parameter names are suggestive, but the description fails to compensate for the absent schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: 'Read the current Agent Checkout cart contents and totals.' This clearly distinguishes get_cart from siblings like create_cart, add_to_cart, and get_product. The qualifier 'current' adds useful scope.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The second sentence explicitly states when to use the tool: 'Use to review or confirm the cart before handing the buyer off to checkout.' This gives a clear usage context, though it does not mention exclusions or name alternatives such as create_cart.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Get detailed product and variant information after search_products identifies a product and merchant. Use before purchase when the user needs details, options, price, or variant information.
| Name | Required | Description | Default |
|---|---|---|---|
| site_slug | Yes | ||
| product_id | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It indicates a read operation by using 'get' and 'information', but it does not explicitly state that the tool has no side effects, nor does it mention error behavior, availability constraints, or data freshness. Adequate for a simple retrieval but leaves some safety implications implicit.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences with no fluff. The core action is front-loaded in the first sentence, and the usage condition follows immediately. Every word earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter read tool with no output schema, the description conveys the essential purpose, workflow position, and trigger conditions. It does not explain return structure or error cases, but those are less critical for a straightforward retrieval. The main gap is the lack of explicit parameter definitions, which is already captured in parameter_semantics.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It implies that site_slug and product_id are the merchant and product identifiers produced by search_products, but it never explicitly maps each parameter. This gives some contextual meaning beyond the bare schema, yet leaves the exact roles of the two parameters under-specified.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description states a specific verb and resource: 'Get detailed product and variant information'. It also situates the tool in a clear workflow ('after search_products identifies a product and merchant') and distinguishes it from siblings like search_products, add_to_cart, and create_checkout by limiting its role to pre-purchase detail retrieval.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description gives explicit usage context: use after search_products and before purchase when the user needs details, options, price, or variant information. It does not explicitly name alternatives to avoid, but the workflow positioning and 'after search_products' precondition provide clear guidance for when this tool applies.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Legacy alias for search_products. Search purchasable products across participating merchants. Prefer search_products for new shopping requests.
| Name | Required | Description | Default |
|---|---|---|---|
| first | No | ||
| query | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry behavioral disclosure. It communicates that the tool is a legacy alias and scopes the search to purchasable products and participating merchants. However, it does not mention return format, pagination, or any limitations beyond being legacy, leaving some behavior undocumented.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two short sentences with no filler. The legacy-alias warning is front-loaded, and the remaining sentences provide only actionable scope and usage direction.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter search tool, the description covers purpose and routing but leaves parameter semantics and the return shape undocumented. An agent can call it with just `query`, but the optional `first` parameter and expected result format are not explained, so the description is not fully standalone.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema has 0% description coverage and the description does not explain `query` or `first`. The word 'search' weakly implies that `query` is the search term, but `first` is entirely unexplained and no format, constraints, or semantics are added beyond the schema itself.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states that the tool searches purchasable products across participating merchants and identifies itself as a legacy alias for search_products. This both defines the core action and differentiates it from the sibling tool list.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It explicitly says to prefer search_products for new shopping requests, naming the alternative and the condition under which it should be selected. The 'legacy alias' framing further signals that this tool exists mainly for backward compatibility.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Primary shopping entry point. Use when a user wants to find, browse, compare, recommend, price-check, check availability of, shop for, or buy a physical product. Searches purchasable products across merchants participating in the Agent Checkout network. The user does not need to mention Agent Checkout by name.
| Name | Required | Description | Default |
|---|---|---|---|
| first | No | ||
| query | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the behavioral burden. It usefully discloses that results are limited to purchasable products from Agent Checkout merchants and that the user need not mention Agent Checkout. But it does not describe the return shape, pagination behavior, or explicitly state that this tool only searches and does not complete purchases.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is front-loaded with 'Primary shopping entry point' and each sentence contributes context. The list of eight user intents is slightly long but serves as useful routing signal for an agent.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple two-parameter search tool, the purpose and scope are adequately conveyed. Still, the undocumented 'first' parameter, lack of output details, and absence of any sibling-routing guidance leave the definition only minimally viable.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, and the description does not explain 'query' or 'first'. The query parameter is inferable from the tool's purpose, but 'first' is entirely unexplained, so the description fails to compensate for the missing schema documentation.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly establishes search_products as the primary entry point for shopping and lists a concrete set of user intents (find, browse, compare, price-check, buy). It says it searches purchasable products across merchants in the Agent Checkout network, which is specific, but it does not explicitly contrast siblings like search_catalog or check_inventory.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides explicit usage context: use it when the user wants to find, browse, compare, recommend, price-check, check availability of, shop for, or buy a physical product. However, it offers no exclusions or alternative tool names, so the agent must infer when not to use it.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
add_to_cart1 field changedInput schema / properties / variant_id / maxLengthPrevious value: -200New value: +300check_inventory1 field changedInput schema / properties / variant_id / maxLengthPrevious value: -200New value: +300create_cart1 field changedInput schema / properties / variant_id / maxLengthPrevious value: -200New value: +300add_to_cartcheck_inventorycreate_cartcreate_checkoutget_cartget_productsearch_catalogsearch_productsClaiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
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AI-agent product catalog: search, lookup & purchase routing over verified merchant data.
Agentic commerce gateway: discovery, search, checkout across Shopify/Woo/Odoo/PrestaShop.
Multi-tenant MCP gateway for AI commerce. One connection, every store.
Multi-tenant MCP gateway for AI commerce. One connection, every store.
Add one secure layer between your agents and this server.
Most tools target distinct steps in the purchase flow, and descriptions clarify the intended sequence. The main overlap is search_catalog being a legacy alias for search_products; check_inventory and get_product have slight overlap but are distinguished by availability checking versus detailed product info.
All tool names follow a consistent verb_noun snake_case pattern such as search_products, get_product, create_cart, add_to_cart, and create_checkout. The naming pattern makes the workflow stage and action immediately clear.
With 8 tools, the surface is well-scoped for a shopping-and-checkout flow: discovery, product details, inventory, cart creation/modification, cart review, and checkout handoff. The redundant search_catalog alias is minor and does not make the set feel bloated.
The core path is complete: search → product details → inventory check → create cart → add to cart → get cart → create checkout. Minor gaps such as removing or updating cart items are missing, but the essential purchase workflow is fully supported.
