env-doctor

About env-doctor

Env-Doctor The missing link between your GPU and Python AI libraries

cicd compatibility-tool cuda cuda-library cuda-support cuda-toolkit cudnn diagnostics gpu mcp-server

Quick Facts

Stars	161
Forks	10
Language	Python
Category	MCP Server
License	MIT
Quality Score	71.2399277171231/100
Open Issues	7
Last Updated	2026-06-18
Created	2025-11-22
Platforms	cli, docker, mcp, python
Est. Tokens	~17k

Compatible Skills

These tools work well together with env-doctor for enhanced workflows:

aimirror — semantic(0.25)+complementary+rare_topics+same_lang+similar_pop+shared_platform (63%)
renderdoc-skill — semantic(0.18)+complementary+same_lang+similar_pop+shared_platform (51%)
free-coding-models — semantic(0.31)+complementary+similar_pop+shared_platform (46%)

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Frequently Asked Questions

What is env-doctor?

env-doctor is Diagnose and Fix CUDA / GPU environments compatibility issues locally, in Docker, and CI/CD. CLI + MCP server available.. It is categorized as a MCP Server with 161 GitHub stars.

What programming language is env-doctor written in?

env-doctor is primarily written in Python. It covers topics such as cicd, compatibility-tool, cuda.

How do I install or use env-doctor?

You can find installation instructions and usage details in the env-doctor GitHub repository at github.com/mitulgarg/env-doctor. The project has 161 stars and 10 forks, indicating an active community.

What license does env-doctor use?

env-doctor is released under the MIT license, making it free to use and modify according to the license terms.

View on GitHub → Browse MCP Server tools