Look up a speedrunner by username. Returns matching users with their ID, display name, and profile weblink. Example: find_user({ name: "cheese05" })
AI agents call find_user to retrieve information from Mcp Speedrun without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
name | string | Yes | Speedrunner username to look up, e.g. "cheese05" |
_apiKey | string | — | Optional speedrun.com API key for authenticated access; omit to use the shared platform key |
Parameters from the server's own tool schema.
This tool queries the Speedrun.com API to retrieve user profile data (ID, display name, weblink). It is purely a data retrieval operation with no side effects. No data is modified, deleted, or executed. The information returned is public speedrunner profile metadata. This clearly fits the Read category with low severity since misuse would only expose already-public information.
From the tool's definition Tool 'Look up a speedrunner by username. Returns matching users with their ID, display name, and profile weblink.' — retrieves publicly available profile information with no ability to modify, delete, or execute actions.
Attacks that exploit this kind of access
Look up a speedrunner by username. Returns matching users with their ID, display name, and profile weblink. Example: find_user({ name: "cheese05" }). It is categorised as a Read tool in the Mcp Speedrun MCP Server, which means it retrieves data without modifying state.
find_user accepts 2 parameters: name, _apiKey. Required: name. The full parameter table on this page comes from the server's own tool schema.
Register the Mcp Speedrun MCP server in PolicyLayer and add a rule for find_user: 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 Speedrun. Nothing to install.
find_user 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 find_user 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 find_user. 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.
find_user is provided by the Mcp Speedrun MCP server (pipeworx-io/mcp-speedrun). 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.
Teams ship this data inside their own products. See what a licence covers →