getEffectivePermission
Compute a user's effective permission level on a resource (taking team grants, inheritance, and 3-state overrides into account) and the source. Asking about another user requires can_manage_perms on the org. Use when the user asks 'can X access this', 'what level of access does X have', 'why can ...
This record as markdown: /tools/io-stablebaseline-sb/geteffectivepermission.md
What getEffectivePermission does on Stable Baseline
AI agents call getEffectivePermission to retrieve information from Stable Baseline without modifying anything. It is typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
user_id | string | Yes | UUID of the user to check |
table_id | string | — | db_row only: the table the row is in. |
database_id | string | — | db_table and db_row only: the database the table or row belongs to. |
resource_id | string | Yes | |
resource_type | string | Yes |
Parameters from the server's own tool schema.
Why getEffectivePermission is rated Low
Even though getEffectivePermission only reads data, uncontrolled read access leaks sensitive information and racks up API costs: an agent caught in a retry loop can make thousands of calls a minute without anyone noticing.
Attacks that exploit this kind of access
The rule that runs getEffectivePermission safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Stable Baseline, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For getEffectivePermission, this is the rule to start with:
getEffectivePermission is read-only, so it stays allowed. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Stable Baseline, apply this rule, and every getEffectivePermission call is checked against it from then on.
Questions about getEffectivePermission
Compute a user's effective permission level on a resource (taking team grants, inheritance, and 3-state overrides into account) and the source. Asking about another user requires can_manage_perms on the org. Use when the user asks 'can X access this', 'what level of access does X have', 'why can X see this', or to debug an unexpected permission outcome. Works for a database, one of its tables (db_table, with database_id) and a single row (db_row, with database_id and table_id) too. It is categorised as a Read tool in the Stable Baseline MCP Server, which means it retrieves data without modifying state.
getEffectivePermission accepts 5 parameters: user_id, table_id, database_id, resource_id, resource_type. Required: user_id, resource_id, resource_type. The full parameter table on this page comes from the server's own tool schema.
Register the Stable Baseline MCP server in PolicyLayer and add a rule for getEffectivePermission: 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 Stable Baseline. Nothing to install.
getEffectivePermission 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 getEffectivePermission 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 getEffectivePermission. 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.
getEffectivePermission is provided by the Stable Baseline MCP server (https://api.stablebaseline.io/functions/v1/cloud-serve/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
More on Stable Baseline, and thousands of servers like it.
This server
Across the catalogue