This record as markdown: /tools/io-github-2s-io-mcp/predict.activity.md
What predict.activity does on Mcp
AI agents call predict.activity to retrieve information from Mcp without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Why predict.activity is rated Low
Based on the available evidence, 'predict.activity' appears to be a read-only tool that likely queries or retrieves prediction data related to wallet activity. The incomplete description prevents higher confidence, but the nature of predictions (forecasting based on data) suggests data retrieval rather than modification, execution, or financial action.
From the tool's definition Tool name 'predict.activity' and description 'A wallet' provide minimal information. The description appears incomplete or truncated.
Attacks that exploit this kind of access
The rule that runs predict.activity safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Mcp, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For predict.activity, this is the rule to start with:
predict.activity is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Mcp, apply this rule, and every predict.activity call is checked against it from then on.
Questions about predict.activity
A wallet\. It is categorised as a Read tool in the Mcp MCP Server, which means it retrieves data without modifying state.
Register the MCP server in PolicyLayer and add a rule for predict.activity: 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. Nothing to install.
predict.activity 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 predict.activity 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 predict.activity. 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.
predict.activity is provided by the MCP server (@2sio/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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