Retrieve saved context by key, category, or session with enhanced filtering. Returns all accessible items (public items + own private items)
AI agents call context_get 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 performs a read-only retrieval operation on saved context data. It queries and returns information without creating, modifying, deleting, executing code, or committing financial actions. The filtering and retrieval mechanism poses minimal risk since it respects access control (public items + own private items).
From the tool's definition Tool description states 'Retrieve saved context by key, category, or session' and 'Returns all accessible items'. The verb 'Retrieve' and 'Returns' indicate data querying with no modification or side effects.
Documented attack patterns abuse exactly the kind of access context_get 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_get:
{
"version": "1",
"default": "deny",
"tools": {
"context_get": {}
}
}context_get is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
Free to start. No card required.
Retrieve saved context by key, category, or session with enhanced filtering. Returns all accessible items (public items + own private items). 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_get: 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_get 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_get 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_get. 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_get 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.
Free to start. No card required.
40 MCP Memory Keeper tools catalogued and risk-classified — across an index of 43,000+ MCP servers.