get_user_context

Get relevant context about the user (facts, patterns, preferences).

SERVERCoach AI SOURCE94aharris/coach-ai

Low RISK CLASS

Category Read

Parameters 00 required

Recommended Allowedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/94aharris-coach-ai/get-user-context.md

WHAT IT DOES

What get_user_context does on Coach AI

AI agents call get_user_context to retrieve information from Coach AI without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

RISK

Why get_user_context is rated Low

This tool retrieves or queries stored user information (facts, patterns, preferences) for context-aware suggestions. It performs no write, delete, execute, or financial operations. The data returned is used to inform coaching recommendations but does not modify state. The low severity reflects that misuse would expose personal productivity data rather than cause operational harm.

From the tool's definition Tool name 'get_user_context' and description 'Get relevant context about the user (facts, patterns, preferences)' indicate retrieval of stored user data with no modification or side effects.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs get_user_context safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Coach AI, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For get_user_context, this is the rule to start with:

get_user_context Allowed

get_user_context is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

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

ALLOW ONLY THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Coach AI, apply this rule, and every get_user_context call is checked against it from then on.

FAQ

Questions about get_user_context

What does the get_user_context tool do? +

Get relevant context about the user (facts, patterns, preferences). It is categorised as a Read tool in the Coach AI MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on get_user_context? +

Register the Coach AI MCP server in PolicyLayer and add a rule for get_user_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 Coach AI. Nothing to install.

What risk level is get_user_context? +

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

Can I rate-limit get_user_context? +

Yes. Add a rate_limit block to the get_user_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_user_context completely? +

Set action: deny in the PolicyLayer policy for get_user_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_user_context? +

get_user_context is provided by the Coach AI MCP server (94aharris/coach-ai). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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