Scan a Xero "Manual Journals" CSV export for anomalies — currently round-number lines (debit or credit amounts that are exact multiples of $1,000, above a $1,000 materiality threshold). Input is raw CSV text from Xero Accounting → Advanced → Manual Journals → Export. Max 5,000 rows; max 5 MB. Ret...
AI agents call analyze_xero_journal_anomalies to retrieve information from HelloBooks AI MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
csvText | string | Yes | Raw CSV text of a Xero "Manual Journals" report. Export from Xero: Accounting → Advanced → Manual Journals → Export. Paste the file contents directly. |
fileName | string | — | Optional original filename, used only as a label on the share page. |
Parameters from the server's own tool schema.
Although this tool operates on financial accounting data within a bookkeeping context, its actual function is read-only analysis: it examines a Xero journal export CSV, identifies anomalies (round-number entries), assigns severity flags, and returns results. No data is created, modified, deleted, or used to execute transactions.
From the tool's definition Tool description states it scans CSV data for anomalies and 'Returns flagged lines with severity...and a shareable URL'. The verbs are 'scan' and 'returns' — no modifications, deletions, financial transactions, or code execution.
Risk signalsAccepts file system path (fileName)
Attacks that exploit this kind of access
Scan a Xero "Manual Journals" CSV export for anomalies — currently round-number lines (debit or credit amounts that are exact multiples of $1,000, above a $1,000 materiality threshold). Input is raw CSV text from Xero Accounting → Advanced → Manual Journals → Export. Max 5,000 rows; max 5 MB. Returns flagged lines with severity ($100K+ high, $10K+ medium, else low) and a shareable URL. Use this when a user pastes Xero data and asks "any anomalies?", "look for round numbers", or "anything suspicious". Same Tier-0 / paid-product split as the QBO variant — history-aware anomaly checks (GL outliers, vendor history, archived-vendor activity, LLM-narrated suspicious) live in the authenticated MCP / paid product. It is categorised as a Read tool in the HelloBooks AI MCP Server MCP Server, which means it retrieves data without modifying state.
analyze_xero_journal_anomalies accepts 2 parameters: csvText, fileName. Required: csvText. The full parameter table on this page comes from the server's own tool schema.
Register the HelloBooks AI MCP Server MCP server in PolicyLayer and add a rule for analyze_xero_journal_anomalies: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches HelloBooks AI MCP Server. Nothing to install.
analyze_xero_journal_anomalies is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the analyze_xero_journal_anomalies rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for analyze_xero_journal_anomalies. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
analyze_xero_journal_anomalies is provided by the HelloBooks AI MCP Server MCP server (Meru-Fin-Tech/HelloBooks-MCP-Public). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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