context_semantic_search

THE RISK

Low Risk

Why context_semantic_search needs a policy

This tool queries stored conversation context using natural language to retrieve relevant information. It retrieves or filters data without creating, modifying, deleting, or executing any operations. The blast radius of misuse is minimal: an agent could retrieve sensitive conversation history it shouldn't access, but cannot modify data, execute code, or cause destructive effects.

From the tool's definition Tool name includes 'search' and description states 'Search context using natural language queries' — a retrieval operation with no modification or execution of external systems.

Documented attack patterns abuse exactly the kind of access context_semantic_search gives an agent:

POLICY

How to control context_semantic_search

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_semantic_search:

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "context_semantic_search": {}
  }
}

context_semantic_search is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.

Create a free account and register MCP Memory Keeper — nothing to install.
Add this policy — paste it, or build it visually.
Point your MCP client (Claude, Cursor, anything) at your gateway URL.

CAP THIS TOOL →

Free to start. No card required.

EXPLORE

Related tools and policies

More MCP Memory Keeper tools

Destructive context_batch_delete Delete multiple context items by keys or pattern in a single atomic operation Execute context_delegate Delegate complex analysis tasks to specialized agents Execute context_watch Create and manage watchers for real-time context change monitoring Execute context_git_commit Create git commit with automatic context save Write context_session_start Start a new context session with optional project directory for git tracking Write context_cache_file Cache file content with hash for change detection Write context_integrate_tool Track events from other MCP tools Write context_reassign_channel Move context items between channels based on keys, patterns, or entire channel

All 40 MCP Memory Keeper tools →

Read tools on other servers

M-Team MCP Server get_torrent_detail YouTube MCP Server search_channel Android Forensics ADB MCP Server parse_browser_history 0xarchive web3_challenge

Go deeper

The MCP Attack Database → Documented attack patterns against MCP deployments — and the policies that stop them.
Data exfiltration → How read access becomes an exfiltration channel when chained with untrusted content.
MCP token cost → What connecting this server costs in context-window tokens on every request.
Rate Limiting MCP Tool Calls: A Practical Guide →
MCP Security: Why Prompt Guardrails Aren't Enough →

FAQ

Questions about context_semantic_search

What does the context_semantic_search tool do? +

Search context using natural language queries. It is categorised as a Read tool in the MCP Memory Keeper MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on context_semantic_search? +

Register the MCP Memory Keeper MCP server in PolicyLayer and add a rule for context_semantic_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.

What risk level is context_semantic_search? +

context_semantic_search is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit context_semantic_search? +

Yes. Add a rate_limit block to the context_semantic_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.

How do I block context_semantic_search completely? +

Set action: deny in the PolicyLayer policy for context_semantic_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.

What MCP server provides context_semantic_search? +

context_semantic_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.

Enforce policy on every MCP Memory Keeper tool call.

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.

CHECK YOUR STACK →