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Meru-Fin-Tech

HelloBooks AI MCP Server

how_munimji_helps

Explains how HelloBooks AI and Munimji automate bookkeeping for your business: maps your operations to tasks you can delegate, approve, or do manually.

Instructions

Explain how HelloBooks and Munimji (the in-app AI assistant) help a specific business — given a free-text description of the user's own operations. Returns a curated capability knowledge base: business-operation areas (sales, purchases, banking, tax, reports, inventory, payroll, multi-entity, setup), and for each AI capability WHO does the work — autonomous (Munimji does it on its own, e.g. OCR extraction, running reports), approval (Munimji prepares the entry and you one-click approve before it posts to the ledger, e.g. AI categorization, find-and-match, creating invoices/bills by chat), assist (co-pilot, e.g. guided onboarding, voice), or manual (a software feature you run yourself). Each capability links to the backing software features. Use this when a user describes their business and asks "how can HelloBooks help me?", "what can the AI do for my shop/practice/agency?", or "what can Munimji do on its own vs what do I approve?". Pass their description in businessDescription; optionally filter by area or autonomy. The AI never posts to a ledger without approval. For the full software catalog call list_features; for pricing call list_plans.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
businessDescriptionNoOptional. The user describes their business and operations in their own words (industry, what they sell, how they get paid, who they pay, tax regime, pain points). It is echoed back as context — the calling assistant maps it to the returned areas + capabilities. No keyword scoring is done here; the LLM does the matching.
areaNoOptional. Narrow to one business-operation area.
autonomyNoOptional. Filter Munimji capabilities by who does the work: `autonomous` (Munimji does it alone), `approval` (Munimji prepares, you approve before it posts), `assist` (co-pilot), `manual` (software feature you run yourself).
Behavior5/5

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

Discloses key behaviors: the AI never posts to ledger without approval, businessDescription is echoed as context, no keyword scoring is performed, and output includes autonomy levels. Since no annotations are provided, the description carries full burden and does so thoroughly.

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 long but well-structured: purpose, output explanation, example queries, parameter guidance, cross-references. It is front-loaded with the most important information. Slightly repetitive with schema details but earns its length.

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?

Despite no output schema, the description thoroughly explains the output structure (areas, autonomy levels, capabilities). It covers the tool's function, parameters, and usage context comprehensively.

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 coverage is 100% with rich parameter descriptions already. The tool description adds context on usage but does not significantly extend meaning beyond what is in the schema. Baseline 3 is appropriate.

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's purpose: explaining how HelloBooks and Munimji help a business given a free-text description of operations. It distinguishes from sibling tools like list_features and feature_search by providing cross-references.

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 provides example queries that trigger use of this tool (e.g., 'how can HelloBooks help me?'), explains when to use it vs alternatives, and suggests calling list_features for full catalog or list_plans for pricing.

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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