earnings_reviewer

SERVERMcp Knowledge SOURCEhttps://mcp.gapup.io

Low RISK CLASS

Category Read

Parameters 63 required

Recommended Allowedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-getgapup-mcp-knowledge/earnings-reviewer.md

WHAT IT DOES

What earnings_reviewer does on Mcp Knowledge

AI agents call earnings_reviewer to retrieve information from Mcp Knowledge without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

Parameter	Type	Required	Description
`async`	boolean	—	If true, returns a job_id immediately (<200ms) instead of waiting for the result. Poll the result with job_result(job_id). Use for slow tools to avoid client ti
`company`	object	Yes
`quarter`	object	Yes
`analystFocus`	string	—
`secFilingContext`	string	—
`transcriptExcerpt`	string	Yes

Parameters from the server's own tool schema.

RISK

Why earnings_reviewer is rated Low

The tool appears to analyze earnings-related documents (call transcripts, 10-Q filings, guidance) and return a structured analyst note. This is fundamentally a read/analysis operation that retrieves and processes financial data to produce a report. While it mentions 'agent-payable' and 'FUNDRAISING', there is no clear indication it executes financial transactions — it reads and synthesizes information.

From the tool's definition 'Earnings Reviewer' — 'Returns a structured, audited deliverable' and 'call transcript + 10-Q + guidance → analyst note'

Risk signalsHigh parameter count (12 properties)

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs earnings_reviewer safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Mcp Knowledge, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For earnings_reviewer, this is the rule to start with:

earnings_reviewer Allowed

earnings_reviewer is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "earnings_reviewer": {}
  }
}

ALLOW ONLY THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Mcp Knowledge, apply this rule, and every earnings_reviewer call is checked against it from then on.

FAQ

Questions about earnings_reviewer

What does the earnings_reviewer tool do? +

Earnings Reviewer — Gapup agent-payable C-suite expertise (FUNDRAISING). Returns a structured, audited deliverable. Reference case: Salesforce Q3 FY2026 — call transcript + 10-Q + guidance → analyst note. Inputs are validated server-side — send the documented case fields. It is categorised as a Read tool in the Mcp Knowledge MCP Server, which means it retrieves data without modifying state.

What parameters does earnings_reviewer accept? +

earnings_reviewer accepts 6 parameters: async, company, quarter, analystFocus, secFilingContext, transcriptExcerpt. Required: company, quarter, transcriptExcerpt. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on earnings_reviewer? +

Register the Mcp Knowledge MCP server in PolicyLayer and add a rule for earnings_reviewer: 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 Mcp Knowledge. Nothing to install.

What risk level is earnings_reviewer? +

earnings_reviewer is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit earnings_reviewer? +

Yes. Add a rate_limit block to the earnings_reviewer 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.

How do I block earnings_reviewer completely? +

Set action: deny in the PolicyLayer policy for earnings_reviewer. 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.

What MCP server provides earnings_reviewer? +

earnings_reviewer is provided by the Mcp Knowledge MCP server (https://mcp.gapup.io). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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