runner_auth_setup
High-level runner bootstrap for a local or remote Yaver machine: install the runner if missing, report whether subscription OAuth is still pending, and register Yaver as an MCP server inside the runner when supported. For Claude Code/Codex, finish auth with runner_auth_browser_start or runner_aut...
This record as markdown: /tools/io-github-kivanccakmak-yaver/runner-auth-setup.md
What runner_auth_setup does on Yaver
AI agents invoke runner_auth_setup to trigger actions in Yaver. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call: builds kicked off, notifications sent, workflows started.
| Parameter | Type | Required | Description |
|---|---|---|---|
notes | string | — | |
runner | string | Yes | |
device_id | string | — | Optional remote device ID |
setup_mcp | boolean | — | Default true. Registers Yaver as an MCP server inside the runner when supported. |
codex_login | boolean | — | Default true for Codex; use browser auth for ChatGPT Plus/Pro OAuth. |
glm_api_key | string | — | OpenCode/GLM provider credential. |
zai_api_key | string | — | OpenCode/GLM provider credential. |
openai_api_key | string | — | OpenCode provider credential only. |
anthropic_api_key | string | — | OpenCode provider credential only. |
allow_install_only | boolean | — | Return a soft success when the CLI is installed but auth is still pending. |
install_if_missing | boolean | — | Default true. |
Parameters from the server's own tool schema.
Why runner_auth_setup is rated High
This tool performs multi-step setup operations: installing software if absent, registering Yaver as an MCP server, and bootstrapping authentication flows. These are external system operations (install, register, configure) that go beyond simple writes — they execute processes and modify system configuration in ways that depend on runtime state and arguments.
From the tool's definition install the runner if missing ... register Yaver as an MCP server inside the runner ... runner bootstrap for a local or remote Yaver machine
Risk signalsHigh parameter count (11 properties)
Attacks that exploit this kind of access
The rule that runs runner_auth_setup safely
PolicyLayer is an MCP gateway: it sits between your AI agents and Yaver, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For runner_auth_setup, this is the rule to start with:
runner_auth_setup stays usable, but rate-capped: a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.
The button opens the PolicyLayer dashboard: create your workspace, connect Yaver, apply this rule, and every runner_auth_setup call is checked against it from then on.
Questions about runner_auth_setup
High-level runner bootstrap for a local or remote Yaver machine: install the runner if missing, report whether subscription OAuth is still pending, and register Yaver as an MCP server inside the runner when supported. For Claude Code/Codex, finish auth with runner_auth_browser_start or runner_auth_credentials_import. Provider credentials here are for OpenCode/GLM only. It is categorised as a Execute tool in the Yaver MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.
runner_auth_setup accepts 11 parameters: notes, runner, device_id, setup_mcp, codex_login, glm_api_key, zai_api_key, openai_api_key, anthropic_api_key, allow_install_only, install_if_missing. Required: runner. The full parameter table on this page comes from the server's own tool schema.
Register the Yaver MCP server in PolicyLayer and add a rule for runner_auth_setup: 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 Yaver. Nothing to install.
runner_auth_setup is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.
Yes. Add a rate_limit block to the runner_auth_setup 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 runner_auth_setup. 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.
runner_auth_setup is provided by the Yaver MCP server (yaver-cli). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
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