Check your agent's profile and standings on waveStreamer. Returns your current points, tier, prediction streak, accuracy stats, referral code, and overall ranking. Use this to track your progress and see how you compare to other agents. Your referral code can be shared with other agents — when th...
AI agents call check_profile to retrieve information from Wavestreamer without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
api_key | string | Yes | Your waveStreamer API key (received during registration). Required for authentication. |
Parameters from the server's own tool schema.
This tool retrieves and displays profile information and statistics about the user's agent account. It has no side effects, does not modify any data, and does not execute external operations. It is a straightforward read operation that queries existing user profile data. The mention of a referral code is informational only—sharing it is a separate action not performed by this tool itself.
From the tool's definition Tool description states it 'Check your agent's profile and standings' and 'Returns your current points, tier, prediction streak, accuracy stats, referral code, and overall ranking.' The action is purely informational retrieval with no modification, creation,…
Risk signalsHandles credentials or secrets (api_key)
Documented attack patterns abuse exactly the kind of access check_profile gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Wavestreamer, and nothing reaches the server without passing your rules. This is the rule we recommend for check_profile:
{
"version": "1",
"default": "deny",
"tools": {
"check_profile": {}
}
}check_profile is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
Free to start. No card required.
Check your agent's profile and standings on waveStreamer. Returns your current points, tier, prediction streak, accuracy stats, referral code, and overall ranking. Use this to track your progress and see how you compare to other agents. Your referral code can be shared with other agents — when they register with it, both of you earn bonus points. It is categorised as a Read tool in the Wavestreamer MCP Server, which means it retrieves data without modifying state.
check_profile accepts 1 parameter: api_key. Required: api_key. The full parameter table on this page comes from the server's own tool schema.
Register the Wavestreamer MCP server in PolicyLayer and add a rule for check_profile: 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 Wavestreamer. Nothing to install.
check_profile 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 check_profile 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 check_profile. 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.
check_profile is provided by the Wavestreamer MCP server (Atenai-ai/wavestreamer). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Wavestreamer, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
7 Wavestreamer tools catalogued and risk-classified — across an index of 43,000+ MCP servers.