create_agent

Create a new agent in the Lens API. Required: name, type, system_prompt, user_prompt_template. Optional: description, llm_config (JSON string), context_variables (comma-separated), tools (comma-separated), knowledge_bases (comma-separated UUIDs), timeout, retry_attempts, streaming, tags (comma-se...

Server Lens lens-mcp-server
Category Write
Risk class Medium
Parameters 123 required

What create_agent does on Lens

AI agents use create_agent to create or update resources in Lens — usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Lens environment.

ParameterTypeRequiredDescription
name string Yes Agent name
tags string Comma-separated tags
type string Yes Agent type (e.g. reasoning, code, chat)
tools string Comma-separated tool names
timeout number Timeout in seconds (default 300)
streaming boolean Enable streaming (default true)
llm_config string JSON string for LLM config (model, temperature, etc.)
description string Optional description
system_prompt string Yes System prompt for the agent
retry_attempts number Retry attempts (default 3)
knowledge_bases string Comma-separated KB UUIDs
context_variables string Comma-separated context variable names

Parameters from the server's own tool schema.

Why create_agent needs a policy

This tool creates new agents with potentially broad capabilities (tools, knowledge_bases, system_prompt configuration). While creation is reversible (agents can be deleted), the tool enables creating agents that could be configured to perform sensitive operations.

From the tool's definition Tool description states 'Create a new agent' with required parameters like name, type, system_prompt, user_prompt_template. The word 'Create' and the ability to define agents with configurable system prompts, tools, and knowledge bases indicate data creation.

Risk signalsHigh parameter count (13 properties)

Questions about create_agent

What does the create_agent tool do? +

Create a new agent in the Lens API. Required: name, type, system_prompt, user_prompt_template. Optional: description, llm_config (JSON string), context_variables (comma-separated), tools (comma-separated), knowledge_bases (comma-separated UUIDs), timeout, retry_attempts, streaming, tags (comma-separated). Use list_agents to see existing agents. It is categorised as a Write tool in the Lens MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

What parameters does create_agent accept? +

create_agent accepts 12 parameters: name, tags, type, tools, timeout, streaming, llm_config, description, system_prompt, retry_attempts, knowledge_bases, context_variables. Required: name, type, system_prompt. The full parameter table on this page comes from the server's own tool schema.

How do I enforce a policy on create_agent? +

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

What risk level is create_agent? +

create_agent is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.

Can I rate-limit create_agent? +

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

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

create_agent is provided by the Lens MCP server (lens-mcp-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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