thinking_reports

List or retrieve deep analysis reports

Server ML Lab MCP pushpullcommitpush/ml-mcp
Category Read
Risk class Low
Parameters 00 required

What thinking_reports does on ML Lab MCP

AI agents call thinking_reports to retrieve information from ML Lab MCP without modifying anything — typically the context-gathering step in research, monitoring, and reporting workflows, before the agent takes action elsewhere.

Why thinking_reports needs a policy

This tool performs query and retrieval operations on existing analysis reports without modifying, deleting, or executing any code or operations. It poses minimal risk as it only accesses data. The low severity reflects the non-destructive nature of information retrieval in an ML engineering context.

From the tool's definition Tool name 'thinking_reports' combined with description 'List or retrieve deep analysis reports' indicates data retrieval operations only. The verbs 'list' and 'retrieve' are characteristic of Read category tools with no side effects.

Questions about thinking_reports

What does the thinking_reports tool do? +

List or retrieve deep analysis reports. It is categorised as a Read tool in the ML Lab MCP MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on thinking_reports? +

Register the ML Lab MCP server in PolicyLayer and add a rule for thinking_reports: 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 ML Lab MCP. Nothing to install.

What risk level is thinking_reports? +

thinking_reports is a Read tool with low risk. Read-only tools are generally safe to allow by default.

Can I rate-limit thinking_reports? +

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

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

thinking_reports is provided by the ML Lab MCP server (pushpullcommitpush/ml-mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

// LOOK UP ANOTHER SERVER

Every MCP server has a record like this.

Type a name, get the same breakdown: verified identity, auth posture, risk grade, capabilities, recommended policy.

Teams ship this data inside their own products. See what a licence covers →

// GET IN TOUCH

Have a question or want to learn more? Send us a message.

Message sent.

We'll get back to you soon.