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QWED-MCP

QWED-MCP

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by QWED-AI
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Python
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execute_python_code

Execute Python code in a restricted subprocess to deterministically verify math, logic, and code analysis tasks using symbolic engines.

Instructions

Executes Python code in a subprocess with restricted environment variables. Note: This runs with server privileges; ensure inputs are trusted.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "code": "<code>"
    },
    "name": "execute_python_code"
  }
}

Input Schema

NameRequiredDescriptionDefault
codeYesThe Python code to execute.
backgroundNoExecute asynchronously in the background and return a tracking job_id. Set to True for heavy logic verifications.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A3.8/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses restricted environment and server privileges, which are important for safety. However, without annotations, it lacks details on specific restrictions, side effects, or error handling.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences: one for core action, one for important caution. No extraneous information.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Lacks description of return values or output format, especially important since no output schema is provided. Does not explain error behavior or what happens in synchronous vs asynchronous execution.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Both parameters are fully described in the schema (100% coverage). The tool description does not add much beyond the schema, but it reinforces the background parameter's purpose for async tasks.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool executes Python code in a subprocess with restricted environment variables. It distinguishes itself from the sibling tool 'verification_status' by implying that background execution returns a job_id for status checking.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides a security caution about server privileges and trusted inputs. The background parameter description advises using it for heavy logic verifications, linking to the sibling tool for status checks.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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