update_data · PySqlit MCP: Risk & Policy

WHAT IT DOES

What update_data does on PySqlitMCP

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

WHY IT NEEDS A POLICY

Why update_data needs a policy

The tool modifies existing data within database tables through update operations. This is Write category (reversible data modification) rather than Destructive because updates can be undone with subsequent updates or rollbacks. Severity is medium because misuse could corrupt or alter important data, but the operation is confined to table updates without deletion or financial impact.

From the tool's definition Tool name 'update_data' and description '更新表中的数据' (updates data in table) indicate a data modification operation. The context of PySqlitMCP with CRUD operations confirms this is a reversible write operation on SQLite tables.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

update_data Rate-limited

update_data 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": {
    "update_data": {
      "limits": [
        {
          "counter": "update_data_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 PySqlitMCP, so you can run agents against it safely.

FAQ

Questions about update_data

What does the update_data tool do? +

更新表中的数据. It is categorised as a Write tool in the PySqlitMCP MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on update_data? +

Register the PySqlit MCP server in PolicyLayer and add a rule for update_data: 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 PySqlitMCP. Nothing to install.

What risk level is update_data? +

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

Can I rate-limit update_data? +

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

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

update_data is provided by the PySqlit MCP server (python51888/pysqlitmcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.