What is PyCopilot?
68/100
Trust Score (C)
⚠️ Use Caution
PyCopilot is a coding that 一个基于 MCP 的 Python 服务端项目，支持多个工具。. It has a Nerq Trust Score of 68/100 (C). 1 GitHub stars. Published by qilincoder. Last analyzed November 2026.
Why This Score
- ⚠️ Security: 0/100 — Some security concerns
- ⚠️ Maintenance: 1/100 — Maintenance activity is low
- ⚠️ Community: 1 stars, 0 downloads — Growing community
- ✅ Transparency: License: Apache-2.0 — Clear licensing
Trust & Safety Overview
68
TRUST SCORE
C
GRADE
1
STARS
0
DOWNLOADS
What PyCopilot Does
PyCopilot is a mcp_server in the coding category. 一个基于 MCP 的 Python 服务端项目，支持多个工具。. It is published by qilincoder and is open source. With 1 GitHub stars and 0 downloads, it has a small community of users and contributors.
Who Should Use PyCopilot
PyCopilot is suitable for evaluation and non-critical use. Review the trust score breakdown before using in production.
Details
| Author | qilincoder |
|---|---|
| Category | coding |
| License | Apache-2.0 |
| Type | mcp_server |
| Source | View on GitHub |
| Security Score | 0/100 |
| Activity Score | 1/100 |
How to Get Started
Check the trust score before installing:
curl nerq.ai/v1/preflight?target=pycopilot
Setup guide · Full safety report · Production review · Is it safe?
Safer Alternatives
| Tool | Trust | Stars |
|---|---|---|
| AutoGPT | 65 | 181.9K |
| ollama | 64 | 163.0K |
| langchain | 77 | 127.8K |
| system-prompts-and-models-of-ai-tools | 64 | 115.3K |
| opencode | 78 | 108.1K |
Frequently Asked Questions
What is PyCopilot used for?
PyCopilot is a coding tool. 一个基于 MCP 的 Python 服务端项目，支持多个工具。.
Is PyCopilot free?
License: Apache-2.0. PyCopilot has 1 GitHub stars.
Is PyCopilot safe?
PyCopilot has a Nerq Trust Score of 68/100 (C). Use with caution.
What are alternatives to PyCopilot?
Top alternatives: AutoGPT, ollama, langchain. See full comparison.
Safety Report Is It Safe?
Alternatives Prediction
Trending Leaderboard
Discover MCP Servers
Packages Models
Stats API
Last updated November 2026. Trust scores based on automated analysis of public data.