push · Python MCP: Risk & Policy

WHAT IT DOES

What push does on Python

AI agents invoke push to trigger actions in Python. What it does depends on the arguments the agent supplies, and its effects often reach beyond the immediate call — builds kicked off, notifications sent, workflows started.

WHY IT NEEDS A POLICY

Why push needs a policy

This tool triggers an external git push operation, which sends commits to a remote repository. While it can create new branches, a regular push is not inherently destructive (no deletion/overwrite of history unless force-push is implied). However, it executes an external operation with side effects that depend on arguments and affects remote state.

From the tool's definition Pushes commits to a remote repository... whether the remote branch was newly created

Attacks that exploit this kind of access

Recommended rule Ready

Verdict

push Rate-limited

push stays usable, but rate-capped — a runaway agent can't fire it dozens of times a minute. Everything else on the server is denied unless you say otherwise.

View as policy code

policy.json

{
  "version": "1",
  "default": "deny",
  "tools": {
    "push": {
      "limits": [
        {
          "counter": "push_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-LIMIT THIS TOOL →

Instant setup, no code required.

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

FAQ

Questions about push

What does the push tool do? +

Pushes commits to a remote repository. Returns structured data with success status, remote, branch, summary, and whether the remote branch was newly created. It is categorised as a Execute tool in the Python MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on push? +

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

What risk level is push? +

push is a Execute tool with high risk. Execute tools should be rate-limited and have argument validation enabled.

Can I rate-limit push? +

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

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

push is provided by the Python MCP server (Dave-London/Pare). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

// THE FULL RECORD

push is one line of Python's registry record.

The record carries the whole server: verified identity, auth posture, risk grade, every tool classified, recommended policy — re-checked continuously.

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