Archive context messages for a conversation with tags and metadata
AI agents use archive-context to create or update resources in Memory MCP — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Memory MCP environment.
Archiving is a reversible write operation that creates or modifies data records (context messages with metadata) without deletion or destruction. While it affects stored state, users can typically retrieve or restore archived data. This is less severe than destructive operations and does not execute arbitrary code or move funds.
From the tool's definition Tool performs archival operation which involves storing/modifying data in MongoDB persistence layer. The description indicates it 'archive[s] context messages' with 'tags and metadata', which modifies the state of stored conversations.
Documented attack patterns abuse exactly the kind of access archive-context gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Memory MCP, and nothing reaches the server without passing your rules. This is the rule we recommend for archive-context:
{
"version": "1",
"default": "deny",
"tools": {
"archive-context": {
"limits": [
{
"counter": "archive-context_rate",
"window": "minute",
"max": 30,
"scope": "grant"
}
]
}
}
}archive-context 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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Archive context messages for a conversation with tags and metadata. It is categorised as a Write tool in the Memory MCP MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Register the Memory MCP server in PolicyLayer and add a rule for archive-context: 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 Memory MCP. Nothing to install.
archive-context 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 archive-context 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 archive-context. 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.
archive-context is provided by the Memory MCP server (jamesanz/memory-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Memory MCP, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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10 Memory MCP tools catalogued and risk-classified — across an index of 43,000+ MCP servers.