Store a knowledge document in the Cortex knowledge base. Auto-chunks and embeds the content for semantic search. Use this to contribute discovered patterns, resolved issues, architecture decisions, and reusable solutions. Supports MemPalace-inspired memory hierarchy (hallType) and temporal validi...
AI agents use cortex_knowledge_store to create or update resources in Cortex Hub — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Cortex Hub environment.
This tool writes new data (knowledge documents) into the knowledge base by chunking and embedding content. It is a reversible write operation — documents can presumably be deleted or updated later. No code is executed, no money is moved, and nothing is explicitly irreversibly destroyed.
From the tool's definition 'Store a knowledge document in the Cortex knowledge base. Auto-chunks and embeds the content for semantic search.'
Documented attack patterns abuse exactly the kind of access cortex_knowledge_store gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Cortex Hub, and nothing reaches the server without passing your rules. This is the rule we recommend for cortex_knowledge_store:
{
"version": "1",
"default": "deny",
"tools": {
"cortex_knowledge_store": {
"limits": [
{
"counter": "cortex_knowledge_store_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}cortex_knowledge_store stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.
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Store a knowledge document in the Cortex knowledge base. Auto-chunks and embeds the content for semantic search. Use this to contribute discovered patterns, resolved issues, architecture decisions, and reusable solutions. Supports MemPalace-inspired memory hierarchy (hallType) and temporal validity (validFrom). It is categorised as a Write tool in the Cortex Hub MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Cortex Hub MCP server in PolicyLayer and add a rule for cortex_knowledge_store: 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 Cortex Hub. Nothing to install.
cortex_knowledge_store is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the cortex_knowledge_store 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 cortex_knowledge_store. 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.
cortex_knowledge_store is provided by the Cortex Hub MCP server (lktiep/cortex-hub). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Cortex Hub, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
Free to start. No card required.
25 Cortex Hub tools catalogued and risk-classified — across an index of 43,000+ MCP servers.