Low Risk

get_earnings_calendar

Upcoming earnings dates for stocks in the Stocklake universe. - days: look-ahead window in days (default 7, max 30) - Returns: { window_days, from_date, to_date, count, results[] } - Each result: symbol, name, sector, market_cap, price, rsi, earnings_date (ISO UTC), is_estimate, eps_trailing, eps...

Part of the Stocklake — AI Stock Intelligence server.

get_earnings_calendar is read-only, but an agent in a loop can still rack up calls and cost. PolicyLayer caps every call before it runs. Live in minutes.

SECURE STOCKLAKE — AI STOCK INTELLIGENCE →

Free to start. No card required.

AI agents call get_earnings_calendar to retrieve information from Stocklake — AI Stock Intelligence without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.

Even though get_earnings_calendar only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.

Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "get_earnings_calendar": {}
  }
}

See the full Stocklake — AI Stock Intelligence policy for all 20 tools.

Get this rule live on your own Stocklake — AI Stock Intelligence server in minutes. PolicyLayer enforces it on every call, before it runs.

ENFORCE ON MY STOCKLAKE — AI STOCK INTELLIGENCE →

View all 20 tools →

These attack patterns abuse exactly the kind of access get_earnings_calendar gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so get_earnings_calendar only ever does what you allow.

SECURE STOCKLAKE — AI STOCK INTELLIGENCE →

Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.

What does the get_earnings_calendar tool do? +

Upcoming earnings dates for stocks in the Stocklake universe. - days: look-ahead window in days (default 7, max 30) - Returns: { window_days, from_date, to_date, count, results[] } - Each result: symbol, name, sector, market_cap, price, rsi, earnings_date (ISO UTC), is_estimate, eps_trailing, eps_forward - Sorted by earnings_date ascending. - Dates sourced from market data — treat is_estimate=true dates as approximate. Available to all tiers.. It is categorised as a Read tool in the Stocklake — AI Stock Intelligence MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on get_earnings_calendar? +

Register the Stocklake — AI Stock Intelligence MCP server in PolicyLayer and add a rule for get_earnings_calendar: 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 Stocklake — AI Stock Intelligence. Nothing to install.

What risk level is get_earnings_calendar? +

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

Can I rate-limit get_earnings_calendar? +

Yes. Add a rate_limit block to the get_earnings_calendar 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 get_earnings_calendar completely? +

Set action: deny in the PolicyLayer policy for get_earnings_calendar. 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 get_earnings_calendar? +

get_earnings_calendar is provided by the Stocklake — AI Stock Intelligence MCP server (https://api.stocklake.dev/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Stocklake — AI Stock Intelligence tool call.

Deterministic rules across all 20 Stocklake — AI Stock Intelligence tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

Free to start. No card required.

4,600+ MCP servers and 31,000+ tools scanned and risk-classified.

// GET IN TOUCH

Have a question or want to learn more? Send us a message.

Message sent.

We'll get back to you soon.