get_product_context

THE RISK

Low Risk

Why get_product_context needs a policy

This tool performs a query operation that fetches stored project metadata without side effects. It retrieves read-only information (goals, features, architecture) in a single JSON object. No data is created, modified, deleted, or executed—only queried. This is a classic Read category tool with low severity since it has minimal blast radius if misused by an AI agent.

From the tool's definition Tool name 'get_product_context' and description 'Retrieves the stored high-level product context' indicates a retrieval operation with no modification or destructive capability.

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

POLICY

How to control get_product_context

PolicyLayer is an MCP gateway — it sits between your AI agents and Engrams, and nothing reaches the server without passing your rules. This is the rule we recommend for get_product_context:

policy.json

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

get_product_context 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 Engrams — nothing to install.
Add this policy — paste it, or build it visually.
Point your MCP client (Claude, Cursor, anything) at your gateway URL.

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EXPLORE

Related tools and policies

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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 get_product_context

What does the get_product_context tool do? +

Retrieves the stored high-level product context (project goals, features, architecture) as a single JSON object. Use this for the persistent. It is categorised as a Read tool in the Engrams MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on get_product_context? +

Register the Engrams MCP server in PolicyLayer and add a rule for get_product_context: 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 Engrams. Nothing to install.

What risk level is get_product_context? +

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

Can I rate-limit get_product_context? +

Yes. Add a rate_limit block to the get_product_context 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 get_product_context completely? +

Set action: deny in the PolicyLayer policy for get_product_context. 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 get_product_context? +

get_product_context is provided by the Engrams MCP server (stevebrownlee/engrams). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Engrams tool call.

Start from Engrams, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

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