update_project · Langfuse Mcp Python MCP: Risk & Policy

WHAT IT DOES

What update_project does on Langfuse Mcp Python

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

WHY IT NEEDS A POLICY

Why update_project needs a policy

The tool modifies project configuration or metadata reversibly (update operation). While it affects organizational state, it is not destructive (reversible) and not financial. The high severity reflects that unauthorized project modifications could impact system monitoring, observability settings, or team configurations, depending on what project attributes are mutable.

From the tool's definition Tool name 'update_project' and description 'Update a project by ID' indicate modification of existing project data. The requirement for 'organization-scoped API key' suggests this is a privileged operation affecting organizational resources.

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

update_project Rate-limited

update_project 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_project": {
      "limits": [
        {
          "counter": "update_project_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 Langfuse Mcp Python, so you can run agents against it safely.

FAQ

Questions about update_project

What does the update_project tool do? +

Update a project by ID (requires organization-scoped API key). It is categorised as a Write tool in the Langfuse Mcp Python 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_project? +

Register the Langfuse Mcp Python MCP server in PolicyLayer and add a rule for update_project: 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 Langfuse Mcp Python. Nothing to install.

What risk level is update_project? +

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

Can I rate-limit update_project? +

Yes. Add a rate_limit block to the update_project 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_project completely? +

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

update_project is provided by the Langfuse Mcp Python MCP server (log-logn/langfuse-mcp-python). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.