save_job · AI Research Assistant MCP Server MCP

WHAT IT DOES

What save_job does on AI Research Assistant MCP Server

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

WHY IT NEEDS A POLICY

Why save_job needs a policy

Based on the name alone, 'save_job' appears to create or persist data (Write category). Without a description, confidence is moderate. The tool likely stores job metadata, parameters, or results in the system's database or state. Severity is medium because unintended job saves could clutter the system or create unwanted records, but reversibility via deletion (sibling tools like 'clear_db' exist) mitigates impact.

From the tool's definition Tool name 'save_job' suggests creating or storing a job record or configuration. No description provided to clarify exact behavior.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

save_job Rate-limited

save_job stays usable, but capped — an agent stuck in a loop can't make hundreds of changes a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "save_job": {
      "limits": [
        {
          "counter": "save_job_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL →

Instant setup, no code required.

PolicyLayer is an MCP gateway: every tool call is checked against your rule before it reaches AI Research Assistant MCP Server, so you can run agents against it safely.

FAQ

Questions about save_job

What does the save_job tool do? +

save_job. It is categorised as a Write tool in the AI Research Assistant MCP Server MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on save_job? +

Register the AI Research Assistant MCP Server MCP server in PolicyLayer and add a rule for save_job: 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 AI Research Assistant MCP Server. Nothing to install.

What risk level is save_job? +

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

Can I rate-limit save_job? +

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

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

save_job is provided by the AI Research Assistant MCP Server MCP server (sagarkpoojary/sagar-mcp-project). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.