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deploy_edge_function

Deploys a new Edge Function to a Supabase project. LLMs can use this to deploy new functions or update existing ones.

Part of the Supabase server.

deploy_edge_function can trigger actions in Supabase, with no limits today. PolicyLayer puts allow, deny, and rate-limit rules on every call. Live in minutes.

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AI agents invoke deploy_edge_function to trigger processes or run actions in Supabase. Execute operations can have side effects beyond the immediate call -- triggering builds, sending notifications, or starting workflows. Rate limits and argument validation are essential to prevent runaway execution.

deploy_edge_function can trigger processes with real-world consequences. An uncontrolled agent might start dozens of builds, send mass notifications, or kick off expensive compute jobs. PolicyLayer enforces rate limits and validates arguments to keep execution within safe bounds.

Execute tools trigger processes. Rate-limit and validate arguments to prevent unintended side effects.

policy.json
{
  "version": "1",
  "default": "deny",
  "tools": {
    "deploy_edge_function": {
      "limits": [
        {
          "counter": "deploy_edge_function_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

See the full Supabase policy for all 32 tools.

Get this rule live on your own Supabase server in minutes. PolicyLayer enforces it on every call, before it runs.

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These attack patterns abuse exactly the kind of access deploy_edge_function gives an agent. Each links to the full case and the policy that stops it:

Browse the full MCP Attack Database →

Every attack above starts with a tool call. PolicyLayer checks each one against your policy first, so deploy_edge_function only ever does what you allow.

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Other execute tools across the catalogue. The same approach applies to each: rate-limit and validate the arguments.

What does the deploy_edge_function tool do? +

Deploys a new Edge Function to a Supabase project. LLMs can use this to deploy new functions or update existing ones.. It is categorised as a Execute tool in the Supabase MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on deploy_edge_function? +

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

What risk level is deploy_edge_function? +

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

Can I rate-limit deploy_edge_function? +

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

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

deploy_edge_function is provided by the Supabase MCP server (@modelcontextprotocol/server-supabase). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

Enforce policy on every Supabase tool call.

Deterministic rules across all 32 Supabase tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.

Free to start. No card required.

4,600+ MCP servers and 31,000+ tools scanned and risk-classified.

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