amazon-business-mcp-browser

Server Quality Checklist

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Latest release: v0.1.0
Disambiguation5/5
Each tool has a clearly distinct purpose: session status, product details, login, search, cart snapshot, checkout prep, and cart mutations. The only slight overlap is between get_cart and prepare_checkout, but their descriptions clearly differentiate a snapshot from an actionable step.
Naming Consistency4/5
All tools use the consistent 'amazon_' prefix, and most follow a verb_noun pattern (get_cart, add_to_cart, update_quantity, remove_from_cart, open_login, prepare_checkout). However, 'session_status' and 'product_details' are noun phrases rather than verb-first, creating a minor stylistic deviation that is still readable and predictable.
Tool Count5/5
The 9 tools are well-scoped for a browser-based Amazon Business assistant, covering authentication, product search, cart management, and checkout preparation. The count feels neither sparse nor bloated for the intended functionality.
Completeness3/5
The tool set covers the full cart CRUD lifecycle (add, get, update, remove) plus search and product details. However, the checkout flow ends at preparation and never confirms an order, leaving a notable gap for fully automated purchasing. There is also no order history or account management, but that may be intentional for safety.
Average 3.7/5 across 9 of 9 tools scored. Lowest: 2.7/5.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 2 commits in the last 12 weeks
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is passing
This repository is licensed under MIT License.
This repository includes a README.md file.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations provided, so the description must disclose behavioral traits. It only mentions 'removes' without explaining side effects, whether the removal is permanent, or any authentication requirements. For a destructive/mutating action, this is insufficient disclosure.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness4/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single concise sentence that states the core action without unnecessary words. However, it is too sparse to fully inform the agent, though it is not verbose or redundant.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool is a mutation, has no output schema, and only one parameter, the description is under-specified. It lacks details about return values, side effects, or when to use it, making it incomplete for an agent to invoke confidently.
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 describes the 'asin' parameter with a pattern, but schema description coverage is 0%. The description only says 'un ASIN' (an ASIN), adding no extra meaning beyond the parameter name. It does not compensate for the lack of coverage, so the parameter semantics remain largely unexplained.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool removes an ASIN from the cart ("Rimuove un ASIN dal carrello reale"), which is a specific verb+resource. However, it does not differentiate from sibling tools like amazon_update_quantity or amazon_get_cart, so it is not fully distinguishing.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It lacks any context about conditions, prerequisites, or exclusions, leaving the agent without clear decision-making information.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It correctly identifies the operation as modifying and clarifies that no purchase occurs, but it omits critical details such as session/login requirements, behavior when the ASIN is already in the cart, quantity handling, or potential failure modes.
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 consists of two short, focused sentences. It is front-loaded with the core action and includes a clarifying note about the action's scope, with no unnecessary words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
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 minimal parameter explanation, the description is too sparse. It leaves unanswered important questions about prerequisites (e.g., session), quantity semantics, and likely side effects, which are necessary for safe and correct invocation.
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 defines 'asin' and 'quantity' with pattern and range constraints, but the description adds no explanatory value. Since schema coverage is 0%, the description should compensate by explaining parameter meaning or edge cases, which it does not.
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 function: adding an ASIN to the real Amazon cart. It uses a specific verb and resource, and it distinguishes itself from sibling tools like amazon_remove_from_cart and amazon_get_cart by focusing on the add action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage (adding items to a cart) and notes that it is a modifying action without making purchases, which gives some contextual boundary. However, it does not explicitly specify when to use this tool versus alternatives like amazon_update_quantity or amazon_remove_from_cart.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Non essendoci annotazioni, la descrizione è l'unica fonte di trasparenza. Rivela il comportamento importante che 'quantità zero rimuove l'articolo', ma non dettaglia altri aspetti come autenticazione, gestione errori o impatto sulla sessione. Fornisce un minimo di trasparenza comportamentale.
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?
Due frasi concise, con l'azione principale subito all'inizio e l'eccezione importante nella seconda frase. Nessuna parola superflua.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Lo strumento è semplice ma la descrizione non menziona prerequisiti (es. sessione attiva) o comportamento in caso di ASIN non presente nel carrello. Copre l'azione principale e il caso limite della quantità zero, ma non è completamente esaustivo.
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?
La descrizione dello schema ha copertura 0%, quindi la descrizione deve compensare. Aggiunge il significato che quantità zero ha un effetto particolare, ma non spiega ulteriormente il formato di ASIN o il range. Il contesto del nome e la frase principale rendono i parametri abbastanza chiari.
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?
La descrizione usa 'Aggiorna la quantità di un ASIN nel carrello' che indica chiaramente l'azione (aggiornare) e la risorsa (quantità di un ASIN nel carrello). Mette anche in evidenza il comportamento della quantità zero, che lo distingue da strumenti come add_to_cart e remove_from_cart.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
Non viene fornita alcuna indicazione esplicita su quando usare questo strumento rispetto ai sibling come amazon_add_to_cart o amazon_remove_from_cart. Non si menzionano prerequisiti (es. sessione attiva) né esclusioni.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the full burden of behavioral disclosure. It mentions the session prerequisite but does not state whether this is a read-only operation, what happens without an active session, or whether it returns a list of results. This lack of behavioral detail is a significant gap.
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 sentence, front-loaded with the action, and contains no redundant information. Every word earns its place, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
There is no output schema and no annotations, so the description should explain what the tool returns or any side effects. It only covers the search action and the session context, leaving out return value details and behavior under missing prerequisites. Given the tool's simplicity, this is incomplete.
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?
The input schema provides 100% coverage with descriptions for both parameters ('query' and 'limit'), so the baseline is 3. The description does not add additional meaning beyond the schema, which is acceptable given the schema's completeness.
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 function: 'Cerca prodotti nel marketplace Amazon configurato' (search products in the configured Amazon marketplace). It uses a specific verb and resource, and is easily distinguished from sibling tools like amazon_product_details or amazon_add_to_cart.
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 specifies a concrete usage context: using the browser's Business session. This implies when to use it (when a Business session is active) and indirectly differentiates from session-status or login tools. However, it does not explicitly name alternatives or exclusions, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. The word 'istantanea' (snapshot) implies a non-mutating read operation, and 'timestamp' adds useful context. However, it does not mention session requirements or potential errors, which are relevant for a tool interacting with a real Amazon session.
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, concise sentence that is front-loaded with the action and key details. Every word earns its place, with no redundant or filler content.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple no-parameter getter, the description is adequate but lacks a detailed account of the snapshot's structure (e.g., items, quantities, pricing) and any prerequisites like an active session. Since there is no output schema, these details would help an agent know exactly what to expect.
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 input schema has zero parameters, so there is nothing to document. The description adds no parameter information, which is acceptable under the 0-parameter baseline.
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 ('restituisce' = returns) and resource ('carrello Amazon reale' = real Amazon cart), clearly distinguishing it from sibling mutation tools like add_to_cart and remove_from_cart. It communicates exactly what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus alternatives. It only states the function, leaving the agent to infer from context that it is the read-only cart accessor among mutating siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
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 clearly indicates a read operation ('Legge') and enumerates the fields, but it does not mention potential edge cases such as invalid ASINs, error responses, or any side effects. This is adequate but lacks depth.
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 sentence that succinctly lists the data points retrieved. It is front-loaded with the verb and resource, contains no redundant information, and every word earns its place.
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?
For a simple read tool with one parameter and no output schema, the description covers the essential fields and purpose satisfactorily. It does not specify return format or error handling, but given the simplicity and the presence of sibling tool context, it is reasonably complete for an agent to invoke correctly.
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 0%, so the description must compensate for parameter meaning. It mentions 'ASIN' as the input, giving some semantic context, but does not define what an ASIN is or clarify the expected format beyond the schema pattern. It adds minimal value over the raw schema.
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 the specific verb 'Legge' (reads) and lists distinct attributes (title, price, availability, seller, features) of an ASIN, clearly distinguishing it from sibling tools that handle session, login, search, cart, and checkout operations. It precisely conveys the resource and action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for retrieving product details by ASIN, but it does not explicitly state when to use this tool over alternatives or when not to use it. No exclusions or alternative tool mentions are provided, leaving the agent to infer from the tool name and sibling context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden. It discloses that the tool navigates the browser and returns a summary, and importantly clarifies that it does not place or confirm the order. However, it does not mention prerequisites such as being logged in, potential side effects on cart state, or the structure of the returned summary.
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 extremely concise, consisting of two short sentences. The first sentence states the primary action and output, and the second clarifies what it does not do. There is no unnecessary elaboration or repetition.
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?
For a simple, no-parameter tool with no output schema, the description adequately covers its purpose and non-behaviors. It mentions returning a summary, which partially compensates for the missing output schema. However, it lacks details about return format or any side effects, leaving some gaps for an agent.
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 is trivially 100% covered. Per the guidelines, a zero-parameter tool gets a baseline score of 4, and the description adds no parameter-specific details because none are needed.
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 function: it brings the browser to the cart and returns the summary, while explicitly noting it does not place or confirm the order. This distinguishes it from sibling tools like add_to_cart, remove_from_cart, and get_cart by focusing on the checkout preparation step.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies usage for reviewing the cart before finalizing a purchase, but it does not explicitly state when to use this tool versus alternatives like get_cart. It does provide a 'when not to use' by clarifying that it does not place/confirm orders, but no direct alternative is named.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. The verb 'Controlla' implies a read-only check, but the description does not mention side effects, return format, or any prerequisites (e.g., existing login session).
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, clear sentence that front-loads the action and context. There is no wasted wording, and it is immediately understandable.
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 parameterless status check, the description is complete enough. It conveys the purpose and scope, and given the lack of parameters or output schema, there is no missing critical context.
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, so there is nothing to explain. Schema coverage is 100% and the description adds no parameter-related information, which is acceptable for a parameterless tool.
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 the specific verb 'Controlla' (checks) and clearly states the resource 'profilo browser isolato' and target 'autenticato su Amazon'. This distinguishes it from sibling tools such as amazon_open_login or amazon_product_details, which have different actions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies this tool is for verifying authentication before performing other Amazon operations, but it does not explicitly state when to use it versus alternatives like amazon_open_login. No when-not-to-use or alternative guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral disclosure. It reveals that the browser is visible and that the user must manually enter password, MFA, and CAPTCHA, which is important context. However, it does not disclose what happens after login or whether the tool returns any status.
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 concise sentences with no unnecessary words. Every element adds value: the visible browser, manual input, and specific credential types.
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 simple purpose (open a browser for login), the description covers the essential behavior and user interaction. However, it omits any mention of return values, completion signals, or follow-up steps like checking session status, which would improve completeness.
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 an empty schema, so there is nothing to explain. The baseline for 0 parameters is 4, and the description appropriately avoids inventing parameter details.
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 function: it opens Amazon in a visible browser for manual login. The title 'Apri login Amazon' further specifies the login context, and the mention of password, MFA, and CAPTCHA distinguishes it from sibling tools like cart or search operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies use when a manual login is needed (user personally enters credentials), but it does not provide explicit when-to-use or when-not-to-use guidance, nor does it mention alternatives like checking amazon_session_status first. The context is clear but without exclusions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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