List conversations assigned to a teammate
AI agents call list_teammate_conversations to retrieve information from Frontapp MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool queries and returns existing conversation data assigned to a specific teammate. It performs a simple read operation without creating, modifying, deleting, or executing any actions. The 'list' verb is a clear indicator of a Read category operation.
From the tool's definition Tool name 'list_teammate_conversations' and description 'List conversations assigned to a teammate' indicate a retrieval operation with no data modification or side effects.
Documented attack patterns abuse exactly the kind of access list_teammate_conversations gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Frontapp MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for list_teammate_conversations:
{
"version": "1",
"default": "deny",
"tools": {
"list_teammate_conversations": {}
}
}list_teammate_conversations is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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List conversations assigned to a teammate. It is categorised as a Read tool in the Frontapp MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Frontapp MCP Server MCP server in PolicyLayer and add a rule for list_teammate_conversations: 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 Frontapp MCP Server. Nothing to install.
list_teammate_conversations 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 list_teammate_conversations 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 list_teammate_conversations. 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.
list_teammate_conversations is provided by the Frontapp MCP Server MCP server (zqushair/frontapp-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Frontapp MCP Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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151 Frontapp MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.