View or modify model selector settings at runtime. Manage blocked models, license filters, and custom model recommendations.
Part of the Claude Token Saver MCP server. Enforce policies on this tool with Intercept, the open-source MCP proxy.
AI agents use configure_model_selector to create or modify resources in Claude Token Saver. Write operations carry medium risk because an autonomous agent could trigger bulk unintended modifications. Rate limits prevent a single agent session from making hundreds of changes in rapid succession. Argument validation ensures the agent passes expected values.
Without a policy, an AI agent could call configure_model_selector repeatedly, creating or modifying resources faster than any human could review. Intercept's rate limiting ensures write operations happen at a controlled pace, and argument validation catches malformed or unexpected inputs before they reach Claude Token Saver.
Write tools can modify data. A rate limit prevents runaway bulk operations from AI agents.
tools:
configure_model_selector:
rules:
- action: allow
rate_limit:
max: 30
window: 60See the full Claude Token Saver policy for all 11 tools.
Agents calling write-class tools like configure_model_selector have been implicated in these attack patterns. Read the full case and prevention policy for each:
Other tools in the Write risk category across the catalogue. The same policy patterns (rate-limit, validate) apply to each.
View or modify model selector settings at runtime. Manage blocked models, license filters, and custom model recommendations.. It is categorised as a Write tool in the Claude Token Saver MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.
Add a rule in your Intercept YAML policy under the tools section for configure_model_selector. You can allow, deny, rate-limit, or validate arguments. Then run Intercept as a proxy in front of the Claude Token Saver MCP server.
configure_model_selector is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the configure_model_selector rule in your Intercept 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 Intercept policy for configure_model_selector. 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.
configure_model_selector is provided by the Claude Token Saver MCP server (claude-token-saver-mcp). Intercept sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Open source. One binary. Zero dependencies.
npx -y @policylayer/intercept