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HelloBooks AI Agents MCP Server

by io.github.HelloBooksAIAgents

list_articles

List published articles on hellobooks.ai — head-to-head compare pages and curated flagship blog posts. Filter by country, tag or free-text query. Use this when a user asks "do you have a blog/article about X?".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tagNoSingle tag to filter on (case-insensitive substring match against the article tag list). e.g. "gst", "1099", "tally".
limitNoMax articles to return (default 20).
queryNoFree-text query — substring-matched against the title, excerpt and tags of each article. e.g. "QuickBooks alternative" or "audit trail".
countryNoISO country code or "global". Returns articles whose countryRelevance matches OR is "global". Omit to return everything.

TDQS

A3.9/5.0
Behavior3/5

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

No annotations are provided, so the description must carry behavioral transparency. It states the tool lists published articles with filtering, but does not disclose traits like read-only nature, pagination, or any limits beyond the schema's maxLength.

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: two sentences plus a usage example. Every sentence provides essential information without redundancy, front-loading the tool's purpose.

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?

Given no output schema, the description does not explain return format or structure. While the tool is simple, a brief mention of what the response contains (e.g., list of article details) would improve completeness.

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% with detailed parameter descriptions (e.g., case-insensitive substring match, enum values). The tool description merely restates 'Filter by country, tag or free-text query' without adding new meaning.

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 published articles on hellobooks.ai, specifying the types (head-to-head compare pages and curated flagship blog posts). It distinguishes well from sibling tools which are focused on financial analysis.

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?

It explicitly says 'Use this when a user asks do you have a blog/article about X?' providing clear context. While it doesn't list when not to use it, the sibling tools are sufficiently different to imply alternatives.

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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