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HelloBooks AI Agents MCP Server

by io.github.HelloBooksAIAgents

local_payment_methods

List local bank-rail / wallet payment methods relevant to HelloBooks invoice collection (AR), B2B supplier payments (AP), and contractor payouts (UPI, RuPay, Razorpay, IMPS, NEFT, RTGS, BACS, FPS, CHAPS, Open Banking, Interac e-Transfer, EFT, PayID, PayTo, NPP, BPAY, ACH, Same Day ACH, Fedwire, RTP, Zelle, PayNow, FAST, GIRO, NZ Direct Credit, etc.). Returns rail (instant / same-day / next-day / multi-day), use-cases, issuing authority, HelloBooks support level, and operational notes (per-transaction caps, settlement windows, retirement timelines). Filter by country, useCase, rail, or id.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoReturn a single payment method by id (e.g. "in-upi", "au-payid", "us-rtp").
railNoFilter by settlement rail (instant, same-day, next-day, multi-day).
countryNoFilter to one country (IN, US, CA, GB, AU, AE, SG, NZ).
useCaseNoFilter by payment use-case. Defaults to HelloBooks' invoice-collection + b2b-supplier + contractor-payout scope; pass an explicit value to widen.

TDQS

A4.5/5.0
Behavior4/5

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

No annotations provided, so description bears full burden. It explains the return fields (rail, use-cases, issuing authority, support level, operational notes) and default useCase behavior. It is a read-only listing tool with no side effects mentioned, which is appropriate.

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 informative and front-loaded with purpose and examples. While slightly long, every sentence adds value. It could be tightened by removing redundant examples, but still effective.

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?

With 4 parameters, no output schema, and no annotations, the description is remarkably complete. It explains filter options, default behavior, return fields, and even provides example IDs. Meets the needs for an AI agent to use the tool correctly.

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?

Schema coverage is 100%, but description adds significant value beyond schema: it explains default useCase scope, gives example IDs ('in-upi', 'au-payid', 'us-rtp'), and clarifies the meaning of each parameter in the context of HelloBooks.

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 lists bank-rail/wallet payment methods relevant to HelloBooks use cases (AR, AP, contractor payouts). It specifies the verb 'List' and resource 'local payment methods', with examples. It distinguishes from sibling tools which are mostly analysis and compliance functions.

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 explicitly mentions filtering by country, useCase, rail, or id, and provides default scoping for useCase. However, it does not explicitly state when not to use or mention alternative tools, though the context of sibling tools suggests this is a unique listing function.

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

A3.8/5.0
Disambiguation4/5

Tools are largely distinct, each targeting a specific report type (balance sheet, P&L, trial balance) or functionality. Some overlap exists between QBO and Xero variants, but descriptions clearly differentiate them. Overall, an agent can reliably select the right tool.

Naming Consistency4/5

Most tools follow a consistent snake_case verb_noun pattern (e.g., analyze_balance_sheet, list_articles). A few exceptions like free_tier_eligibility and how_munimji_helps break the pattern but are still readable and predictable.

Tool Count3/5

With 29 tools, the count is on the higher side but justified by the domain's breadth (financial analysis, compliance, migration, pricing, etc.). Some reduction through parameterization (e.g., merging QBO/Xero variants) would improve scope.

Completeness4/5

The tool surface covers key areas: financial statement analysis, compliance, migration estimation, feature/pricing info, and partner programs. Missing are direct data manipulation tools (e.g., create/edit journal entries), which may be intentional for a read-only analysis agent.

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