This record as markdown: /tools/io-github-2s-io-mcp/predict.positions.md
What predict.positions does on Mcp
AI agents call predict.positions 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.positions is rated Low
The tool appears designed to retrieve or query wallet position data, which is a read operation. No description indicates destructive, financial transaction, write, or execute capabilities. However, the severely truncated description ('A wallet\') creates ambiguity; without full details, confidence is reduced.
From the tool's definition Tool name 'predict.positions' and description 'A wallet' suggest querying wallet-related data or positions, with no indication of modification or external execution. The truncated description ('A wallet\') is incomplete and uninformative, lowering confidence.
Attacks that exploit this kind of access
The rule that runs predict.positions 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.positions, this is the rule to start with:
predict.positions 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.positions call is checked against it from then on.
Questions about predict.positions
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.positions: 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.positions 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.positions 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.positions. 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.positions 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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