Skip to main content
Glama
ComplyEaze

ComplyEaze Bridge: TallyPrime MCP server for Claude Desktop

Official

ledger_movement

Read-only

Retrieve ledger opening, debit/credit movement, closing balance, and touched-voucher count for a date window from TallyPrime; use narrow dates to avoid source limits.

Instructions

Return literal-window ledger opening, exact debit/credit movement, closing, and touched-voucher count with a freshly observed supported product/mode and an operation-valid opening boundary. Reads the full voucher window before filtering or pagination; use narrow dates. Dense windows can fail source limits. Requires one observed INR currency master: a book with several Currency masters, none, or one that is not INR is refused before any ledger read. A ledger name resolves only when spelled as in the book or differing from it only in ASCII case and spaces; ledger_match names the ledger read, how (matched: exact, or case_or_spacing, which the answer should mention by naming the ledger read) and any similar_ledgers that differ from it only in case or whitespace. Each call appends metadata-only receipt lines (tool, company, counts, request and response fingerprints; no book content) to ComplyEaze Bridge's local log on this computer; it writes nothing to Tally.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
toYes
fromYes
limitNo
ledgerNo
offsetNo
company_guidYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.4.1

TDQS

A4.1/5.0
Behavior5/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, and the description adds substantial behavior beyond them: INR currency-master requirement (refuses multi/none/non-INR books), full-window read before pagination, source-limit failure mode, ledger-name matching semantics, and the fact that it appends metadata-only receipt lines to a local log while writing nothing to Tally. This is unusually rich disclosure.

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?

Front-loaded with the deliverable, and nearly every clause carries operational information (currency precondition, date-window behavior, logging side effect). It is a single dense block that would read better as short sentences, but little of it is wasted.

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?

For a six-parameter read tool with no output schema, the description describes the return shape (opening, movement, closing, voucher count, ledger_match with match mode, similar_ledgers), preconditions, failure modes, and side effects. An agent has what it needs to invoke it correctly.

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 0%, so the description must carry parameter meaning. It explains the ledger name resolution rules and the from/to window behavior, but says nothing about limit, offset, or company_guid semantics, leaving half the parameters undocumented. It partially compensates but leaves clear gaps.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb-and-resource: returns literal-window ledger opening, debit/credit movement, closing, and touched-voucher count. It is clearly a ledger-movement read, distinguishable from sibling list/aggregate tools like trial_balance or vouchers, though the phrasing is dense enough that the core purpose is buried in the first clause.

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?

Gives concrete usage guidance: reads the full voucher window before filtering or pagination, so 'use narrow dates', and warns dense windows can fail source limits. It does not name alternative sibling tools for related queries, so it stops short of explicit routing.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.