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HelloBooks AI Agents MCP Server

by io.github.HelloBooksAIAgents

list_plans

List HelloBooks pricing plans with monthly + annual prices in 8 regional currencies (USD, INR, CAD, GBP, AUD, AED, SGD, NZD). Covers four core tiers — Free / Pro / Business / Partner Program (the cpa plan id) — plus two per-entity stackable add-ons (Warehouse, Manufacturing). Returns AI credit allowance, feature bullets (AI auto-categorization, unlimited users, multi-entity, 3-way matching, API access, etc.), and the public signup URL. Filter by plan (one of free / pro / business / cpa) or country (ISO code). Pricing follows Doc 19 v3 (Web-Fire #514, 2026-06-12): Business re-introduced as a 4th tier sized ~4× Pro to match Partner Points; the retired "$59.99/mo + $4.99/client" CPA SKU is gone and the cpa plan id now resolves to the free Partner Program (call partner_program_info for the status ladder + points math). HelloCPA Practice Management is a separate product on practice.hellobooks.ai — call practice_management_info, NOT this tool.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
planNoRestrict the response to a single plan tier (`cpa` = free Partner Program).
countryNoISO country code. Filters prices to one country. Omit to return all 8 markets.

TDQS

A4.2/5.0
Behavior4/5

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

No annotations are provided, so the description carries full behavioral transparency weight. It discloses the data returned (prices, AI credit allowance, feature bullets, signup URL), the pricing version (Doc 19 v3), and clarifies the status of the CPA plan. It does not contradict any annotations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is thorough but somewhat verbose, including detailed versioning references (Doc 19 v3, Web-Fire #514) that may be extraneous for an agent. It front-loads the main purpose but could be more concise.

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 lack of an output schema, the description effectively explains the return values (AI credit allowance, feature bullets, signup URL) and covers all plan tiers and add-ons. It provides sufficient context for an agent to understand the tool's output.

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?

Schema coverage is 100% with enum descriptions. The description adds significant context beyond the schema, such as mapping plan values to tier names and clarifying that 'cpa' resolves to the free Partner Program. Country parameter is explained as ISO codes for filtering.

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 it lists HelloBooks pricing plans with monthly and annual prices in 8 currencies, covering four core tiers and two add-ons. It explicitly differentiates from sibling tools partner_program_info and practice_management_info by directing agents to use those for related but distinct information.

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 provides explicit guidance on when to use alternative tools (partner_program_info for status ladder and practice_management_info for a separate product). It also explains filtering options but does not explicitly state the primary use case for pricing queries.

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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