Get a second opinion from another AI model, or use a specialized model for a specific task. Notable modes: - mode:
Part of the Blockrun server.
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AI agents call blockrun_chat to retrieve information from Blockrun without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.
Even though blockrun_chat only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.
Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.
{
"version": "1",
"default": "deny",
"tools": {
"blockrun_chat": {}
}
}See the full Blockrun policy for all 16 tools.
These attack patterns abuse exactly the kind of access blockrun_chat gives an agent. Each links to the full case and the policy that stops it:
Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.
Get a second opinion from another AI model, or use a specialized model for a specific task. Notable modes: - mode:. It is categorised as a Read tool in the Blockrun MCP Server, which means it retrieves data without modifying state.
Register the Blockrun MCP server in PolicyLayer and add a rule for blockrun_chat: 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 Blockrun. Nothing to install.
blockrun_chat 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 blockrun_chat 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 blockrun_chat. 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.
blockrun_chat is provided by the Blockrun MCP server (@blockrun/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 16 Blockrun tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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4,600+ MCP servers and 31,000+ tools scanned and risk-classified.