Return competitor positioning entries (QuickBooks, Xero, FreshBooks, Wave, Zoho Books, Tally) with where HelloBooks wins, where the competitor wins, and pricing notes. Optional country, tier (primary / secondary), and id filters.
AI agents call list_competitors 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 |
|---|---|---|---|
id | string | — | Return a single competitor by id (e.g. "quickbooks", "xero", "tally"). |
tier | string | — | Filter to head-on rivals (primary) or adjacent / segment-specific overlaps (secondary). |
country | string | — | Only return competitors whose primary market is this country, or who are also evaluated in this market. |
Parameters from the server's own tool schema.
This tool retrieves and queries static competitor positioning data (where HelloBooks wins/loses vs competitors, pricing notes). It has no side effects, does not modify any data, and does not execute external operations. It is a straightforward read/query operation returning reference information.
From the tool's definition Tool name 'list_competitors' and description state it 'Return[s] competitor positioning entries' with optional filters. No modifications, deletions, or external operations are performed.
Attacks that exploit this kind of access
Return competitor positioning entries (QuickBooks, Xero, FreshBooks, Wave, Zoho Books, Tally) with where HelloBooks wins, where the competitor wins, and pricing notes. Optional country, tier (primary / secondary), and id filters. It is categorised as a Read tool in the HelloBooks AI MCP Server MCP Server, which means it retrieves data without modifying state.
list_competitors accepts 3 parameters: id, tier, country. 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 list_competitors: 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.
list_competitors 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 list_competitors 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 list_competitors. 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.
list_competitors 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.
Every MCP server has a record like this.
Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.
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