Score the relevance of archived context against current conversation context
AI agents call score-relevance to retrieve information from Memory MCP without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool reads and evaluates existing archived context against current conversation data to produce a relevance score. It performs a read/query operation with no side effects — it does not create, modify, delete, or execute anything. Severity is low as misuse would only surface existing stored data in scored form.
From the tool's definition Score the relevance of archived context against current conversation context
Documented attack patterns abuse exactly the kind of access score-relevance 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 score-relevance:
{
"version": "1",
"default": "deny",
"tools": {
"score-relevance": {}
}
}score-relevance is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Score the relevance of archived context against current conversation context. It is categorised as a Read tool in the Memory MCP MCP Server, which means it retrieves data without modifying state.
Register the Memory MCP server in PolicyLayer and add a rule for score-relevance: 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.
score-relevance 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 score-relevance 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 score-relevance. 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.
score-relevance 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.