This record as markdown: /tools/io-github-daedalus-mcp-sympy/sympy-acos.md
What sympy_acos does on Pypi:mcp Sympy
AI agents use sympy_acos 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.
Why sympy_acos is rated Medium
An AI agent can call sympy_acos 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
The rule that runs sympy_acos 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_acos, this is the rule to start with:
sympy_acos 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.
The button opens the PolicyLayer dashboard: create your workspace, connect Pypi:mcp Sympy, apply this rule, and every sympy_acos call is checked against it from then on.
Questions about sympy_acos
Arc cosine. 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.
Register the Pypi:mcp Sympy MCP server in PolicyLayer and add a rule for sympy_acos: 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.
sympy_acos is a Write tool with medium risk. Write tools should be rate-limited to prevent accidental bulk modifications.
Yes. Add a rate_limit block to the sympy_acos 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.
Set action: deny in the PolicyLayer policy for sympy_acos. 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.
sympy_acos 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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