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ComplyEaze

ComplyEaze Bridge: TallyPrime MCP server for Claude Desktop

Official

cash_flow

Read-only

Retrieve TallyPrime's month-wise cash and bank ledger movement for up to twelve whole months, verified against the trial balance before results are returned.

Instructions

Return Tally's own Cash Flow for whole months: its month-wise movement of the cash and bank ledgers, not a cash flow statement under AS 3. The months are returned only after the net total of the whole period has been compared with the trial balance, over the ledgers this check counts as cash and bank (those under Cash-in-Hand and Bank Accounts, a group inside them included; a ledger under a group a user made inside one was not measured), and found equal; otherwise the result is not_established and no month is shown (cash_flow_differs_from_trial_balance; cash_flow_money_group_unmeasured when a Bank OD A/c or Bank OCC A/c ledger has movement; cash_flow_nothing_to_compare when neither the cash and bank ledgers nor Tally's Cash Flow carry an amount for the period). Each month's closing is Tally's closing column for it, not checked month by month, and Tally's debit and credit columns are not returned. A month Tally printed with no amount is returned with an empty closing, which is not zero and does not say the month had no entries. A negative amount is a debit: cash and bank grew. The result's unmeasured_in_this_answer names any credit amount, positive closing or window from March into April it contains (a credit amount was seen tied to the trial balance in live runs on one synthetic book (two windows, one of them with a positive closing), and a window from March into April was not run; no month was compared with Tally's own Cash Flow screen: compare such months with it); two zero nets are not a tie (cash_flow_nothing_to_compare). The window must be whole months, at most twelve, and not start before the book (cash_flow_window_not_month_start, cash_flow_window_not_month_end, cash_flow_window_too_many_months, trial_balance_before_books). A book with several currency masters and Education mode are refused. The report's cost on a large book with cash activity is not known (one year of empty months on a large book answered at once): ask for one month first, and if a call times out do not repeat it. 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
toYesThe last day of the last month, which must be a month's last day, so that from to to holds at most twelve whole months (YYYYMMDD or YYYY-MM-DD).
fromYesThe first day of the first month, which must be the 1st (YYYYMMDD or YYYY-MM-DD).
company_guidYesThe company's company_guid, as list_companies returns it.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv0.4.3

TDQS

A4.5/5.0
Behavior5/5

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

Annotations declare read-only/non-destructive, and the description goes well beyond them: it enumerates the failure modes and their codes, states that no month is shown when the check fails, explains that `closing` is Tally's closing column unchecked month-by-month, that an empty closing is not zero, that a negative amount is a debit, and that each call appends metadata-only receipt lines to a local log while writing nothing to Tally.

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 purpose is front-loaded, but the rest is a single dense paragraph with deep parenthetical nesting and long error-code lists, which makes it hard to parse. Most content is relevant, yet details about live runs on a synthetic book and an unrun March-into-April window add bulk with limited decision value.

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 three-parameter read tool with no output schema, the description covers return semantics (per-month closing, not_established, empty closing), sign convention, validation conditions, refusal cases, performance caveats, and side effects, leaving little an agent would need to infer.

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%, so `from`/`to`/`company_guid` are already documented, but the description adds real constraints beyond the schema: whole months only, at most twelve, must not start before the book's start, plus the specific error codes for violating each rule.

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 first sentence states a specific verb+resource and scope: Tally's own Cash Flow for whole months, the month-wise movement of cash and bank ledgers, explicitly distinguished from an AS 3 cash flow statement. An agent can separate this from siblings like trial_balance or ledger_movement without opening a schema.

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 gives rich context on when the result is usable (only after the net total ties to the trial balance), when it is refused (multiple currency masters, Education mode), and practical sequencing ('ask for one month first, and if a call times out do not repeat it'). What it lacks is explicit routing to a named alternative tool for the cases where this one fails.

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