Pack top-relevant chunks into a markdown context block under a token budget. Returns text + sources + truncated flag.
AI agents call context_for_query to retrieve information from brainMD without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool queries the markdown vault to surface relevant information based on a query, similar to search or retrieval operations. It returns formatted text and metadata without modifying, deleting, or executing anything. The operation is purely informational and safe for an AI agent to invoke.
From the tool's definition The tool 'context_for_query' retrieves and packs relevant chunks into a markdown context block. It returns text + sources + truncated flag, which are read operations with no side effects or data modification.
Documented attack patterns abuse exactly the kind of access context_for_query gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and brainMD, and nothing reaches the server without passing your rules. This is the rule we recommend for context_for_query:
{
"version": "1",
"default": "deny",
"tools": {
"context_for_query": {}
}
}context_for_query is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Pack top-relevant chunks into a markdown context block under a token budget. Returns text + sources + truncated flag. It is categorised as a Read tool in the brainMD MCP Server, which means it retrieves data without modifying state.
Register the brainMD MCP server in PolicyLayer and add a rule for context_for_query: 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 brainMD. Nothing to install.
context_for_query 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 context_for_query 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 context_for_query. 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.
context_for_query is provided by the brainMD MCP server (mi4uu/brain.md). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from brainMD, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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17 brainMD tools catalogued and risk-classified — across an index of 43,000+ MCP servers.