Skip to main content
Glama
Sign In
Windows Developer MCP Server

Windows Developer MCP Server

by peeyushcodes
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Local

python_info

Get comprehensive Python environment details: version, executable path, platform, prefix, and active virtual environment.

Instructions

Return comprehensive Python environment information.

Includes version, executable path, platform, prefix, and active virtual environment (if any).

Returns: A dict with keys: status, data (detailed env info).

Examples: python_info()

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "python_info"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does well by specifying the return dict with 'status' and 'data' keys and listing included fields. It lacks details on failure modes or status values but is transparent for a read-only info tool.

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?

The description is front-loaded with the purpose, then provides return details and an example. Every sentence adds value, and there is no fluff.

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

Completeness5/5

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

For a tool with no params and an output schema, the description thoroughly explains what the result contains and provides an example call. It is sufficiently complete for an agent to invoke and understand the output.

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

Parameters4/5

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

There are no parameters, so the baseline of 4 applies. The description provides an example call with no arguments, confirming the tool takes none. No additional parameter semantics needed.

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 'Return comprehensive Python environment information' and lists specific details (version, executable path, platform, prefix, venv), distinguishing it from siblings like python_version or pip_version.

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?

Clear context that this is for a full environment snapshot, but it does not explicitly mention alternatives like python_version for only the version or run_python_script for executing code. Implied usage is clear enough.

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

Deploy Server

Other Tools