sympy_complement

Compute complement of set1 in set2.

SERVERPypi:mcp Sympy SOURCEpypi:mcp-sympy

Medium RISK CLASS

Category Write

Parameters 00 required

Recommended Rate-limitedsee the rule below

Registry record Grade F, identity unverified Pull the record →

This record as markdown: /tools/io-github-daedalus-mcp-sympy/sympy-complement.md

WHAT IT DOES

What sympy_complement does on Pypi:mcp Sympy

AI agents use sympy_complement to create or update resources in Pypi:mcp Sympy, usually the action step of a workflow, after the agent has gathered context. Every call changes real data in your Pypi:mcp Sympy environment.

RISK

Why sympy_complement is rated Medium

An AI agent can call sympy_complement faster than any human can review: one bad instruction and it creates or modifies resources in Pypi:mcp Sympy by the hundred, each call as confident as the last.

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs sympy_complement safely

PolicyLayer is an MCP gateway: it sits between your AI agents and Pypi:mcp Sympy, and checks every tool call against a rule you set before the call runs. Nothing changes on the server itself. For sympy_complement, this is the rule to start with:

sympy_complement Rate-limited

sympy_complement 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": {
    "sympy_complement": {
      "limits": [
        {
          "counter": "sympy_complement_rate",
          "window": "minute",
          "max": 30,
          "scope": "grant"
        }
      ]
    }
  }
}

LIMIT THIS TOOL → Instant setup, no code required.

The button opens the PolicyLayer dashboard: create your workspace, connect Pypi:mcp Sympy, apply this rule, and every sympy_complement call is checked against it from then on.

FAQ

Questions about sympy_complement

What does the sympy_complement tool do? +

Compute complement of set1 in set2. It is categorised as a Write tool in the Pypi:mcp Sympy MCP Server, which means it can create or modify data. Consider rate limits to prevent runaway writes.

How do I enforce a policy on sympy_complement? +

Register the Pypi:mcp Sympy MCP server in PolicyLayer and add a rule for sympy_complement: 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 Pypi:mcp Sympy. Nothing to install.

What risk level is sympy_complement? +

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

Can I rate-limit sympy_complement? +

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

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

sympy_complement is provided by the Pypi:mcp Sympy MCP server (pypi:mcp-sympy). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.

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