GotCashback MCP

Search portals by name

get_portals_by_name

Read-onlyIdempotent

Searches cashback portals by name (e.g. 'Rakuten', 'TopCashback', 'Honey') and returns each match with its payout terms, one entry per country the portal operates in. Use it when the user asks about a named portal: its sign-up bonus, minimum payout, how often it pays, or which payout methods it offers. For a store's cashback rate at that portal, call get_cashback_rates_by_store_name and read the 'portal' field of each rate instead. Each portal includes its payout terms for that country: 'sign_up_bonus' (amount and the url that grants it, null when none), 'minimum_payout' with 'minimum_payout_currency' (smallest balance paid out, null when not published, 0 means no minimum), 'payment_frequency' (how often it pays, e.g. 'On demand', 'Weekly', 'Monthly'), and 'payment_methods' (payout options, e.g. 'PayPal', 'Direct deposit', 'Check', 'Gift card'). Use these to answer questions about a portal's sign-up bonus, payout threshold, payment schedule and payment options. When mentioning a sign-up bonus, show its 'url' as a clickable link — the bonus is only credited when the user signs up through it.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`portal_name`	Yes	The cashback portal name as users say it, e.g. 'Rakuten', 'TopCashback', 'Honey', 'Quidco'. Case-insensitive substring match, best match first.
`country_code`	No	Optional. Lowercase ISO 3166-1 alpha-2 country code that limits results to one country, e.g. 'us' (United States), 'ca' (Canada), 'gb' (United Kingdom — use 'gb', not 'uk'), 'de' (Germany), 'au' (Australia), 'fr' (France). Pass it when the user names a country ('in Canada', 'UK cashback'); omit it to search all supported countries.

Output Schema

TableJSON Schema

Name	Required	Description	Default
`portals`	No

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

First observedSep 4, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Annotations already mark the tool as read-only, idempotent, and non-destructive, and the description enriches that with meaningful behavior: results are country-specific entries, sign_up_bonus can be null, minimum_payout distinguishes null from 0, and payment_frequency/method examples clarify the domain. No contradiction with annotations exists.

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 front-loaded with purpose and usage, then provides a clear alternative, then gives field-level output detail. It is longer than strictly necessary, especially given an output schema exists, but every section serves a purpose and the structure is logical and scannable.

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 read-only search tool with two fully documented parameters and an output schema, the description is complete. It covers what the tool does, when to use it, when not to use it, what alternative to call, and the meaning of key output fields. Nothing essential for correct invocation is missing.

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 100%, so the input schema already fully documents portal_name and country_code. The description reinforces the portal-name use case and country-per-entry output, but it does not add new parameter-specific semantics beyond what the schema already provides. Baseline 3 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 states a specific verb and resource: 'Searches cashback portals by name' and says it returns payout terms, one entry per country. It also clearly distinguishes itself from the sibling get_cashback_rates_by_store_name by explicitly calling out what this tool is not for. An agent can easily tell when to choose this tool over the sibling.

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

Usage Guidelines5/5

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

It gives explicit when-to-use guidance: 'Use it when the user asks about a named portal: its sign-up bonus, minimum payout, how often it pays, or which payout methods it offers.' It also gives an explicit alternative: 'For a store's cashback rate at that portal, call get_cashback_rates_by_store_name.' This is model-friendly routing behavior.

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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TDQS

A4.6/5.0

Disambiguation5/5

Each tool targets a clearly distinct lookup or action: store names versus store ids, cashback versus gift cards, brand versus category versus store, and portals versus stores versus user account data. The descriptions also include explicit cross-references telling an agent which tool to prefer, so misselection is unlikely.

Naming Consistency5/5

Tool names follow a consistent get_/set_/remove_/toggle_ verb pattern with resource and qualifier suffixes like by_store_name, by_store_id, and by_country. Singular and plural resource names are used naturally and do not break the overall predictable convention.

Tool Count4/5

18 tools is slightly above the typical well-scoped range, mainly because of parallel by_name and by_id variants for stores, gift cards, and portals. However, each variant serves a distinct workflow and the overall count is coherent for a cashback-comparison and account-management server.

Completeness5/5

The surface covers the full range of the domain: cashback rate lookups, gift card comparisons, brand/category deals, store and portal browsing, payout term checks, and user favorites/alerts with create, update, and delete operations. There are no obvious dead ends, and the cross-references between tools make workflows like finding a store_id and then setting an alert seamless.

Resources

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