Select app for subsequent operations
AI agents call select_app to retrieve information from Pulse Workflow MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool selects/sets a target app context for subsequent operations. It is a state-selection operation with no data modification, deletion, or execution implied. It functions like a 'use' or 'focus' command, similar to selecting a database before querying. No destructive or write side effects are described.
From the tool's definition Select app for subsequent operations
Attacks that exploit this kind of access
Select app for subsequent operations. It is categorised as a Read tool in the Pulse Workflow MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Pulse Workflow MCP Server MCP server in PolicyLayer and add a rule for select_app: 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 Pulse Workflow MCP Server. Nothing to install.
select_app 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 select_app 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 select_app. 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.
select_app is provided by the Pulse Workflow MCP Server MCP server (pulse-intelligence/pulse-workflow-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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