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HelloBooks AI Agents MCP Server

by io.github.HelloBooksAIAgents

estimate_migration_effort

Take a QBO or Xero journal-entry CSV (source auto-detected) and return a structured migration-effort estimate — row counts, unique-account count, period span, complexity classification (low / medium / high), human-hours estimate, assisted-hours estimate, and an indicative price quote in USD. Heuristic-based — refined against the live entity once the user signs up. Accepts larger files than the other analytical tools (up to 50,000 rows / 20 MB) because no detection runs here, just sizing. Use this when a user is weighing the cost of moving books to HelloBooks, pastes data and asks "how long will migration take?", "what would this cost?", or "is it worth migrating?". The funnel CTA points at /migrate/?ref= to start the assisted flow with the parsed sizing pre-populated.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
csvTextYesRaw CSV text of a journal-entry export from QBO ("Journal Entries") or Xero ("Manual Journals"). Source is auto-detected from headers.
fileNameNo

TDQS

A4.3/5.0
Behavior4/5

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

No annotations provided, so description carries full burden. It discloses heuristic-based nature, refinement after sign-up, file size limits (50k rows/20 MB), and funnel CTA. No destructive side effects mentioned, but adequate for a sizing tool.

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?

Somewhat long but every sentence adds value: outputs, behavior, usage, limits. Front-loaded with purpose and results. No waste.

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 no output schema, description fully details return fields. Parameter info is sufficient. No missing critical context for a migration estimation tool.

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 50%. Description adds meaning for csvText: source auto-detected, up to 50k rows/20 MB (schema only gives maxLength). For fileName, no extra detail, but overall improves understanding beyond schema.

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?

Description clearly states the tool takes a QBO or Xero journal-entry CSV and returns a structured migration-effort estimate with specific outputs (row counts, account count, complexity, hours, price). It distinguishes from siblings by noting it accepts larger files because no detection runs, just sizing.

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?

Explicit usage context: when user is weighing migration cost, pastes data, or asks specific questions. Highlights comparison with other analytical tools (larger files). Does not explicitly state when NOT to use, but the intent is clear.

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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