Search through saved context items with advanced filtering
AI agents call context_search to retrieve information from MCP Memory Keeper without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves or queries stored context data based on filter criteria. It performs no modifications, deletions, or external operations. The blast radius of misuse is minimal — an agent could retrieve information it shouldn't see, but cannot alter or delete anything. This is a pure Read operation.
From the tool's definition Tool is described as "Search through saved context items with advanced filtering" — a query operation with no side effects. The name "context_search" and action verb "search" indicate data retrieval only.
Documented attack patterns abuse exactly the kind of access context_search gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and MCP Memory Keeper, and nothing reaches the server without passing your rules. This is the rule we recommend for context_search:
{
"version": "1",
"default": "deny",
"tools": {
"context_search": {}
}
} context_search is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Search through saved context items with advanced filtering. It is categorised as a Read tool in the MCP Memory Keeper MCP Server, which means it retrieves data without modifying state.
Register the MCP Memory Keeper MCP server in PolicyLayer and add a rule for context_search: 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 MCP Memory Keeper. Nothing to install.
context_search 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 context_search 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 context_search. 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.
context_search is provided by the MCP Memory Keeper MCP server (mkreyman/mcp-memory-keeper). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from MCP Memory Keeper, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.
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40 MCP Memory Keeper tools catalogued and risk-classified — across an index of 43,000+ MCP servers.