agentcard

approve_request

Resolve a pending approval request (approve or deny) once the USER has decided. Use this after get_card_details or create_card returns a 202 requiring approval, or for a row from list_pending_approvals. For card_details and transaction, approval automatically completes the follow-up action and returns the result. For cross_app actions (asks from another app: close/pause/resume a card, change a limit, view details), approval records the user's consent and the REQUESTING app completes the action from its side when it retries with the approval id.

Input Schema

TableJSON Schema

Name	Required	Description
`action`	Yes	The original action type from the approval prompt (list_pending_approvals rows carry it as action).
`decision`	Yes	Whether to approve or deny the request
`approval_id`	Yes	The approval request ID
`resource_id`	Yes	Card ID (for card_details and cross_app actions) or approval ID (for transaction)

Output Schema

TableJSON Schema

Name	Required	Description
`card`	No	The card resource returned by the approved follow-up action, when applicable.
`action`	No	The original action type from the approval prompt: 'card_details' or 'transaction'.
`status`	No	Outcome of the request: 'denied', 'card_details', 'card_created', 'resolved' (cross_app approvals: consent recorded, the requesting app completes the action), 'personal_surface_only' (company-connected session; the user resolves personally), or 'unknown_action'.
`message`	Yes	Human-readable summary of the approval outcome and any follow-up action.
`decision`	No	The decision that was applied: 'approved' or 'denied'.

Schema Changelog

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

First observedJul 28, 2026

TDQS

A5/5.0

Behavior5/5

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

Describes the two different outcomes: for card_details/transaction, approval completes the action and returns result; for cross_app, it records consent and the requesting app retries. This goes beyond annotations (readOnlyHint=false, destructiveHint=false) and fully discloses the behavior.

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 concise yet comprehensive, using a few well-structured sentences. Front-loaded with purpose, followed by usage contexts, and ends with specific behavior details. Every sentence adds value without redundancy.

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?

Given the tool's complexity (multiple action types with different outcomes), the description covers all necessary aspects: when to use, how each action type behaves, and parameter hints. The existence of an output schema means return details are covered elsewhere, so the description is complete.

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

Parameters5/5

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

Adds meaning beyond the 100% schema coverage: explains that resource_id is card ID for most actions but approval ID for transaction, and that list_pending_approvals rows carry the action field. This enhances understanding of parameter usage.

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 resolves pending approval requests (approve or deny) and specifies the contexts (202 responses, list_pending_approvals). It distinguishes between card_details/transaction and cross_app actions, which differentiates it from sibling tools like close_card or pause_card.

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?

Explicitly tells when to use this tool: after get_card_details or create_card returns a 202, or for rows from list_pending_approvals. It also contrasts the behavior for card_details/transaction (auto-complete) vs cross_app (record consent), providing clear usage guidance.

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

A3.9/5.0

Disambiguation4/5

Most tools have clearly distinct purposes, especially in areas like card management and shopping. However, the KYC flow has multiple overlapping tools (start_kyc, get_kyc_status, check_kyc_document, submit_kyc_document, submit_kyc_fields) that could confuse an agent despite detailed descriptions.

Naming Consistency4/5

Tool names consistently use snake_case with a verb_noun pattern (e.g., add_funds, create_card, list_cards). A few exceptions like surprise_me and whoami break the pattern but are still intuitive overall.

Tool Count3/5

50 tools is on the high side for a single server, but the broad domain (cards, shopping, KYC, support, settings) partially justifies it. Some tools could be merged (e.g., KYC flow tools) without losing clarity.

Completeness4/5

The tool surface covers core workflows: CRUD for cards, transactions, KYC, support, shopping, and account management. Minor gaps exist (e.g., no update_card general, no cancel order in shopping), but overall the set is comprehensive for the stated purpose.

Resources

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