textgen
Repository: textgen
Author: oobabooga · Source status: Clear source
The original local LLM interface.
Score basis:Clear source · Risk needs review · Universal
Repository: mcp-ui
Author: machaojin1917939763·Source status: Clear source
基于MCP(Model Context Protocol)的智能聊天应用,支持Web和桌面环境。集成OpenAI/Anthropic API,提供MCP服务器的所有工具能力。简洁现代的UI设计,支持跨平台部署。
Score basis:Clear source · Risk needs review · Universal
Trust level
83 · High trust
Strong recovered source and maintenance signals.
Risk decision
Review required
metadata-only
Install readiness
script-backed · copy-only command
SkillTrust only shows install guidance and copy actions; it never executes installs.
Before you install
Review source, permissions, and execution risk first, then alternatives. Scores prioritize review; they do not replace manual judgment.
Review weakest dimensions and next actions before copying commands.
Evidence or risk signals are incomplete; compare alternatives first.
Audit grade
C · Review first
Execution risk
High
Evidence confidence
67%
SAS-v2.1 radar
SAS-v2.1
Audit grade
C · Review first
Execution risk
High
Top threats
unexpected code execution, data exfiltration
Control gaps
missing license, broad permissions
Evidence confidence
67%
Repository
machaojin1917939763/mcp-ui
Author
machaojin1917939763
Community signal
88 stars · 17 forks
Last updated
2025-04-10
Primary source
machaojin1917939763/mcp-ui
Source status
Clear source
Install method
script-backed
Command & code execution
34Focus: Whether it runs commands or scripts
Next action: Manually confirm command-running skills in an isolated directory.
High-risk action confirmation
38Focus: Whether destructive or external actions require confirmation
Next action: Avoid directly installing high-risk skills without confirmation controls.
Network & data egress
43Focus: Whether it may send data out
Next action: If unsure, restrict network access or allow only known domains.
Supported tools can change install steps; Universal entries need source review.
Explicitly supported
Candidate support (inferred)
Candidate tools are inferred signals, not official compatibility certifications.
git clone https://github.com/machaojin1917939763/mcp-ui.gitmetadata-only
Review source and permissions before copying install commands.
Evidence or risk signals are incomplete; compare alternatives first.
Focus: Who published it and whether it is traceable
Next action: Review repository, author, and README first; do not install directly when source is pending.
Focus: Whether install steps can be reviewed
Next action: Prefer candidates with install docs and repository evidence.
Focus: Whether tool descriptions may hide instructions
Next action: Read README, rules, and tool descriptions before install.
Focus: What it can access
Next action: Grant only task-required permissions and prefer Ask/manual confirmation.
Focus: Whether it runs commands or scripts
Next action: Manually confirm command-running skills in an isolated directory.
Focus: Whether file reads/writes can escape scope
Next action: Check working directory and file access scope before running.
Focus: Whether it may send data out
Next action: If unsure, restrict network access or allow only known domains.
Focus: Whether it handles tokens, private keys, or agent identity
Next action: Do not provide long-lived tokens or private keys to source-pending skills.
Focus: Whether external content can steer behavior
Next action: For browser/RAG/rules skills, review permissions and confirmation controls first.
Focus: Whether memory or retrieved context can be poisoned
Next action: Try RAG/memory skills in a low-privilege environment first.
Focus: Whether external tools and MCP access are clearly bounded
Next action: Confirm which external tools it will connect to before install, and start with the smallest possible set.
Focus: Whether destructive or external actions require confirmation
Next action: Avoid directly installing high-risk skills without confirmation controls.
Focus: How far impact can spread when something goes wrong
Next action: If unsure, test in an isolated project first.
Focus: Whether actions can be traced
Next action: Prefer candidates with logs or previews.
Focus: Whether it is maintained and reusable
Next action: Check license and maintenance before organizational use.
Strong recovered source and maintenance signals.
Phase 1 only shows installation-aware, source-backed signals. SkillTrust does not execute install scripts for users.
Risk factors
metadata-only
Permission hints
repository clone
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Author: badlogic · Source status: Clear source
AI agent toolkit: coding agent CLI, unified LLM API, TUI & web UI libraries, Slack bot, vLLM pods
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RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Agent capabilities to create a superior context layer for LLMs
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Repository: Dify-WebUI
Author: machaojin1917939763 · Source status: Clear source
由 Dify API 驱动的前沿桌面智能对话应用,具备企业级人工智能对话能力。这款应用拥有主题定制、知识库管理以及多场景应用等显著功能。 如今,我们进行了重大升级,新增对 OpenAI 格式输出的支持。这意味着,它能够与市面上所有遵循 OpenAI 格式的人工智能模型无缝对接。不管您使用的是知名供应商的模型,比如提供可靠且可扩展云端解决方案的 Azure OpenAI,还是以先进自然语言处理能力闻名的 Cohere,又或是专注于人工…
Score basis:Clear source · Risk needs review · Universal