Compute Bollinger Bands (SMA + population stdev). Inputs: values:number[] (oldest→newest), period?:number(20), mult?:number(2).
AI agents use ta_bollinger to create or update resources in CG Alpha MCP — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your CG Alpha MCP environment.
An AI agent can call ta_bollinger faster than any human can review — one bad instruction and it creates or modifies resources in CG Alpha MCP by the hundred, each call as confident as the last.
Attacks that exploit this kind of access
Compute Bollinger Bands (SMA + population stdev). Inputs: values:number[] (oldest→newest), period?:number(20), mult?:number(2). It is categorised as a Write tool in the CG Alpha MCP MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the CG Alpha MCP server in PolicyLayer and add a rule for ta_bollinger: 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 CG Alpha MCP. Nothing to install.
ta_bollinger is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the ta_bollinger 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 ta_bollinger. 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.
ta_bollinger is provided by the CG Alpha MCP server (jcf0/cg-alpha-mcp). 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.
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