sympy_matrix_eigenvects

Compute eigenvectors of a matrix.

SERVERPypi:mcp Sympy SOURCEpypi:mcp-sympy

High RISK CLASS

Category Execute

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-matrix-eigenvects.md

WHAT IT DOES

What sympy_matrix_eigenvects does on Pypi:mcp Sympy

AI agents invoke sympy_matrix_eigenvects to trigger actions in Pypi:mcp Sympy. 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.

RISK

Why sympy_matrix_eigenvects is rated High

This tool performs symbolic mathematical computation (eigenvalue/eigenvector decomposition) via SymPy, which involves executing computational logic on input data. It has no side effects on external systems, but it runs non-trivial computation that could be resource-intensive for large or adversarial inputs. Categorized as Execute because it triggers a computational operation rather than simply reading stored data.

From the tool's definition Compute eigenvectors of a matrix

Attacks that exploit this kind of access

RECOMMENDED RULE

The rule that runs sympy_matrix_eigenvects 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_matrix_eigenvects, this is the rule to start with:

sympy_matrix_eigenvects Rate-limited

sympy_matrix_eigenvects 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": {
    "sympy_matrix_eigenvects": {
      "limits": [
        {
          "counter": "sympy_matrix_eigenvects_rate",
          "window": "minute",
          "max": 10,
          "scope": "grant"
        }
      ]
    }
  }
}

RATE-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_matrix_eigenvects call is checked against it from then on.

FAQ

Questions about sympy_matrix_eigenvects

What does the sympy_matrix_eigenvects tool do? +

Compute eigenvectors of a matrix. It is categorised as a Execute tool in the Pypi:mcp Sympy MCP Server, which means it can trigger actions or run processes. Use rate limits and argument validation.

How do I enforce a policy on sympy_matrix_eigenvects? +

Register the Pypi:mcp Sympy MCP server in PolicyLayer and add a rule for sympy_matrix_eigenvects: 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_matrix_eigenvects? +

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

Can I rate-limit sympy_matrix_eigenvects? +

Yes. Add a rate_limit block to the sympy_matrix_eigenvects 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_matrix_eigenvects completely? +

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

sympy_matrix_eigenvects 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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