Returns the OPTIMAL subset of ALL Engrams entities (decisions, patterns, progress, custom data) that fit within a token budget, scored by 7 relevance factors. This is the highest-level retrieval tool — use it when you need task-relevant context but don
AI agents call get_relevant_context to retrieve information from Engrams without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This is a pure read operation that queries and filters persistent memory data to return context. It has no capability to create, modify, delete, or execute operations. The relevance scoring is internal to the retrieval logic. Blast radius is minimal—worst case an agent receives contextual information that informs a later action, but the tool itself performs no destructive, financial, or irreversible operations.
From the tool's definition Tool returns a subset of engrams entities scored by relevance factors; 'Returns' and 'retrieval tool' indicate read-only data retrieval with no side effects. No mutations, deletions, or external operations are described.
Documented attack patterns abuse exactly the kind of access get_relevant_context gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Engrams, and nothing reaches the server without passing your rules. This is the rule we recommend for get_relevant_context:
{
"version": "1",
"default": "deny",
"tools": {
"get_relevant_context": {}
}
}get_relevant_context is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Returns the OPTIMAL subset of ALL Engrams entities (decisions, patterns, progress, custom data) that fit within a token budget, scored by 7 relevance factors. This is the highest-level retrieval tool — use it when you need task-relevant context but don. It is categorised as a Read tool in the Engrams MCP Server, which means it retrieves data without modifying state.
Register the Engrams MCP server in PolicyLayer and add a rule for get_relevant_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 Engrams. Nothing to install.
get_relevant_context 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 get_relevant_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 get_relevant_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.
get_relevant_context is provided by the Engrams MCP server (stevebrownlee/engrams). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Engrams, 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.
42 Engrams tools catalogued and risk-classified — across an index of 43,000+ MCP servers.