Perform semantic search across the codebase to find relevant code snippets. Use this tool when you need to: - Find specific functions, classes, or implementations - Locate code that handles a particular concept - Quickly explore what exists in the codebase For comprehensive context with file summ...
AI agents call semantic_search to retrieve information from Context Engine MCP Server without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
This tool retrieves and queries data from the codebase without creating, modifying, deleting, or executing anything. It is purely informational and follows the 'Read' category definition of retrieving or querying data with no side effects. The blast radius of misuse is minimal since an agent cannot cause harm by searching for code.
From the tool's definition Tool performs 'semantic search across the codebase to find relevant code snippets' and is used to 'Find specific functions, classes, or implementations' and 'Locate code that handles a particular concept'.
Documented attack patterns abuse exactly the kind of access semantic_search gives an agent:
PolicyLayer is an MCP gateway — it sits between your AI agents and Context Engine MCP Server, and nothing reaches the server without passing your rules. This is the rule we recommend for semantic_search:
{
"version": "1",
"default": "deny",
"tools": {
"semantic_search": {}
}
}semantic_search 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.
Perform semantic search across the codebase to find relevant code snippets. Use this tool when you need to: - Find specific functions, classes, or implementations - Locate code that handles a particular concept - Quickly explore what exists in the codebase For comprehensive context with file summaries and related files, use get_context_for_prompt instead. It is categorised as a Read tool in the Context Engine MCP Server MCP Server, which means it retrieves data without modifying state.
Register the Context Engine MCP Server MCP server in PolicyLayer and add a rule for 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 Context Engine MCP Server. Nothing to install.
semantic_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 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.
Set action: deny in the PolicyLayer policy for 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.
semantic_search is provided by the Context Engine MCP Server MCP server (kirachon/context-engine). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Start from Context Engine MCP Server, 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.
50 Context Engine MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.