This record as markdown: /tools/karbassi-slack-mcp/users-conversations.md
What users_conversations does on Slack
AI agents call users_conversations to retrieve information from Slack without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
Why users_conversations is rated Low
Based on the tool name, this tool likely retrieves or lists conversations associated with a user, which is a read operation. However, the empty description lowers confidence. Given the Slack API context, 'users.conversations' is a known Slack API method that lists channels/conversations a user is a member of — a read-only operation.
From the tool's definition Tool name 'users_conversations' suggests listing or retrieving conversations for a user; description is empty and uninformative.
Attacks that exploit this kind of access
The rule that runs users_conversations safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Slack, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For users_conversations, this is the rule to start with:
users_conversations 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 Slack, apply this rule, and every users_conversations call is checked against it from then on.
Questions about users_conversations
users_conversations is a read tool on the Slack MCP server. It is categorised as a Read tool in the Slack MCP Server, which means it retrieves data without modifying state.
Register the Slack MCP server in PolicyLayer and add a rule for users_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 Slack. Nothing to install.
users_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 users_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 users_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.
users_conversations is provided by the Slack MCP server (karbassi/slack-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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