Get relevant codebase context optimized for prompt enhancement. This is the primary tool for understanding code and gathering context before making changes. Returns: - File summaries and relevance scores - Smart-extracted code snippets (most relevant parts) - Related file suggestions for dependen...
AI agents call get_context_for_prompt 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 performs semantic search and context retrieval operations with no side effects. It gathers information to inform decision-making but does not create, modify, delete, or execute any code or commands. The blast radius of misuse is minimal—an agent could retrieve irrelevant context or leak sensitive code patterns, but cannot cause data loss or execute operations.
From the tool's definition Tool retrieves and returns 'file summaries', 'code snippets', 'related file suggestions', and 'memories' with no modification capability.
Documented attack patterns abuse exactly the kind of access get_context_for_prompt 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 get_context_for_prompt:
{
"version": "1",
"default": "deny",
"tools": {
"get_context_for_prompt": {}
}
}get_context_for_prompt is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.
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Get relevant codebase context optimized for prompt enhancement. This is the primary tool for understanding code and gathering context before making changes. Returns: - File summaries and relevance scores - Smart-extracted code snippets (most relevant parts) - Related file suggestions for dependency awareness - Relevant memories from previous sessions (preferences, decisions, facts) - Token-aware output (respects context window limits) Use this tool when you need to: - Understand how a feature is implemented - Find relevant code before making changes - Get context about a specific concept or pattern - Explore unfamiliar parts of the codebase - Recall user preferences and past decisions. 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 get_context_for_prompt: 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.
get_context_for_prompt 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_context_for_prompt 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_context_for_prompt. 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_context_for_prompt 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.
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50 Context Engine MCP Server tools catalogued and risk-classified — across an index of 43,000+ MCP servers.