Store a memory for future sessions. Memories are persisted as markdown files and automatically retrieved via semantic search when relevant. Categories: - \
AI agents use add_memory to create or update resources in Context Engine MCP Server — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Context Engine MCP Server environment.
The tool creates or modifies persistent data (markdown files) in a reversible manner. Users can store memories that are later retrieved, and these files can be updated or deleted. This is a Write operation with low severity because the blast radius is limited to local memory storage with no external side effects, financial impact, or data destruction.
From the tool's definition "Store a memory for future sessions. Memories are persisted as markdown files" — this tool creates and persists new data (markdown files) in a local storage system.
Documented attack patterns abuse exactly the kind of access add_memory gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Context Engine MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for add_memory:
{
"version": "1",
"default": "deny",
"tools": {
"add_memory": {
"limits": [
{
"counter": "add_memory_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}add_memory 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 memory for future sessions. Memories are persisted as markdown files and automatically retrieved via semantic search when relevant. Categories: - \. It is categorised as a Write tool in the Context Engine MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Context Engine MCP Server MCP server in PolicyLayer and add a rule for add_memory: 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 Context Engine MCP Server. Nothing to install.
add_memory 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 add_memory 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 add_memory. 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.
add_memory is provided by the Context Engine MCP Server MCP server (kirachon/context-engine). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Context Engine MCP Server, 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.
50 Context Engine MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.