Render a prompt by substituting variables and returning the final messages without calling the model. Use this to verify template output before a completion; run_prompt_completion is the tool that actually invokes the model.
AI agents call render_prompt to retrieve information from Portkey Admin without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.
| Parameter | Type | Required | Description |
|---|---|---|---|
prompt_id | string | Yes | Prompt ID or slug to render |
variables | object | Yes | Variable values to substitute into the template |
hyperparameters | object | — | Override default hyperparameters |
Parameters from the server's own tool schema.
Even though render_prompt 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.
Risk signalsHigh parameter count (10 properties)
Attacks that exploit this kind of access
Render a prompt by substituting variables and returning the final messages without calling the model. Use this to verify template output before a completion; run_prompt_completion is the tool that actually invokes the model. It is categorised as a Read tool in the Portkey Admin MCP Server, which means it retrieves data without modifying state.
render_prompt accepts 3 parameters: prompt_id, variables, hyperparameters. Required: prompt_id, variables. The full parameter table on this page comes from the server's own tool schema.
Register the Portkey Admin MCP server in PolicyLayer and add a rule for render_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 Portkey Admin. Nothing to install.
render_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 render_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 render_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.
render_prompt is provided by the Portkey Admin MCP server (CodesWhat/portkey-admin-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.