python_project_info

THE RISK

Low Risk

Why python_project_info needs a policy

This tool performs static analysis of project metadata files to gather information about Python project configuration and dependencies. It retrieves and queries data with no side effects, making it a Read operation. The caching mechanism and detection of standard Python config files confirms it is informational only.

From the tool's definition Tool description states it 'Analyze[s] Python project configuration, dependencies, and structure' by detecting and reading files (pyproject.toml, setup.py, requirements.txt). No modification, deletion, or execution of commands is mentioned.

Documented attack patterns abuse exactly the kind of access python_project_info gives an agent:

POLICY

How to control python_project_info

PolicyLayer is an MCP gateway — it sits between your AI agents and MCP DevTools Server, and nothing reaches the server without passing your rules. This is the rule we recommend for python_project_info:

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "python_project_info": {}
  }
}

python_project_info is read-only, so it stays allowed — but everything else on the server is denied unless you say otherwise.

Create a free account and register MCP DevTools Server — nothing to install.
Add this policy — paste it, or build it visually.
Point your MCP client (Claude, Cursor, anything) at your gateway URL.

CAP THIS TOOL →

Free to start. No card required.

EXPLORE

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Go deeper

The MCP Attack Database → Documented attack patterns against MCP deployments — and the policies that stop them.
Data exfiltration → How read access becomes an exfiltration channel when chained with untrusted content.
MCP token cost → What connecting this server costs in context-window tokens on every request.
Rate Limiting MCP Tool Calls: A Practical Guide →
MCP Security: Why Prompt Guardrails Aren't Enough →

FAQ

Questions about python_project_info

What does the python_project_info tool do? +

Analyze Python project configuration, dependencies, and structure (pyproject.toml, setup.py, requirements.txt detection with caching). It is categorised as a Read tool in the MCP DevTools Server MCP Server, which means it retrieves data without modifying state.

How do I enforce a policy on python_project_info? +

Register the MCP DevTools Server MCP server in PolicyLayer and add a rule for python_project_info: 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 MCP DevTools Server. Nothing to install.

What risk level is python_project_info? +

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

Can I rate-limit python_project_info? +

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

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

python_project_info is provided by the MCP DevTools Server MCP server (rshade/mcp-devtools-server). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every MCP DevTools Server tool call.

Start from MCP DevTools Server, add the rest of your stack, and see everything your agents can call. Then put policy on all of it.

CHECK YOUR STACK →