This record as markdown: /tools/karbassi-slack-mcp/chat-command.md
What chat_command does on Slack
AI agents invoke chat_command to trigger actions in Slack. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
Why chat_command is rated High
This tool runs slash commands in Slack, which can execute arbitrary operations depending on what commands are configured in the workspace. The actual effects depend on which slash commands exist and what they do, making this an Execute category tool rather than a simple Read or Write operation. The 'legacy undocumented' qualifier suggests limited visibility into its behavior, which increases risk.
From the tool's definition Tool name 'chat_command' combined with description 'Execute a slash command (legacy undocumented)'. The word 'Execute' directly indicates code/command execution capability.
Attacks that exploit this kind of access
The rule that runs chat_command 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 chat_command, this is the rule to start with:
chat_command stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. 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 chat_command call is checked against it from then on.
Questions about chat_command
Execute a slash command (legacy undocumented). It is categorised as a Execute tool in the Slack MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
Register the Slack MCP server in PolicyLayer and add a rule for chat_command: 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.
chat_command is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the chat_command 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 chat_command. 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.
chat_command 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.
More on Slack, and thousands of servers like it.
Across the catalogue