jev-agent-quality
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@jev-agent-qualityRun a Jev quality review on my latest diff"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Jev Agent Quality
给任何代码 Agent 使用的 Jev 质量检查工具。项目只有两部分:一个标准 MCP 服务和一份可复制的 Skill。它不绑定 Codex、Claude Code、CodeBuddy 或 DeepSeek Harness。
三步使用
1. 下载
git clone --depth 1 https://github.com/diegozhou114-cloud/jev-agent-quality.git
cd jev-agent-quality仓库已经提交可直接运行的 dist/server.js,无需安装 Node 依赖。开发或需要重新构建时使用 npm ci && npm run build。
2. 配置 key
在启动 Agent 的环境中设置:
export JEV_API_KEY="your-typesafe-key"不要把 key 写进配置文件、仓库或规则文本。
3. 配置 MCP 和 Skill
把下面的 MCP 配置复制到 Agent 的 MCP 设置中,把路径改成实际目录:
{
"mcpServers": {
"jev-agent-quality": {
"type": "stdio",
"command": "node",
"args": ["/absolute/path/to/jev-agent-quality/dist/server.js"],
"env": {"JEV_API_KEY": "${JEV_API_KEY}"}
}
}
}完整模板见 mcp.json。将 skills/jev-review/SKILL.md 复制到 Agent 的 Skill 目录,或把它的内容加入 Agent 的全局规则。这样用户不需要每次输入“使用 Jev”。
不同 Agent 的配置文件位置不同,但 MCP 都只需要这三个值:command=node、args=dist/server.js、环境变量 JEV_API_KEY。如果 Agent 支持 MCP,就可以直接使用;如果只支持规则文件,就复制 Skill 并让它调用自己的 MCP 客户端。
Related MCP server: gitl
它什么时候调用
Skill 会自动判断风险:跨文件、公共 API、状态/控制流、错误处理、安全、并发、测试和重构默认检查;格式、文档、拼写、依赖安装和一行机械修复默认跳过。检查只发送聚焦 diff 和必要上下文,不会自动读取或上传整个仓库。
Jev 返回结构化分数、置信度和弱项提示。Agent 负责解释、修改和测试;Jev 不改代码,也不替代测试、静态分析或人工审查。
MCP 工具
服务只提供一个只读工具:jev_review。
{
"task": "需求和验收条件",
"diff": "当前聚焦 diff",
"files": [{"path": "src/example.ts", "content": "必要的当前内容"}],
"repositoryContext": "必要的架构、约定和测试结果",
"previousEvaluation": {}
}本地开发
npm ci
npm run validate源码在 src/,构建产物在 dist/server.js。MCP 使用 stdio,适用于支持 MCP 的桌面 Agent、CLI Agent 和自建 Harness。
隐私和成本
只有明确传入 jev_review 的 task、diff、文件和上下文会发送到 TypeSafe Jev API。不要发送密钥、.env、证书、生成文件、vendor 目录或无关专有代码。按风险触发可以减少延迟和 API 成本。
License
MIT,见 LICENSE。
This server cannot be deployed
Maintenance
Related MCP Connectors
Security reviews for coding agents: diffs checked against your org policy and live infrastructure.
Read-only AI coding tools for change verification, release readiness, capacity, and guidance.
Risk-scan a diff, flag AI-generated-code tells, find secrets. 5 of 7 tools need no account.
Hosted code graph over MCP: exact callers, dependencies, and cross-repo blast radius for AI agents.
Related MCP Servers
- AlicenseAqualityCmaintenanceExposes the squad-dev workflow as deterministic MCP tools, enabling task classification, risk scoring, specialist reviewer selection, and advisory verdict consolidation for code changes.2743 npm4Apache 2.0
- AlicenseNot gradedqualityAmaintenanceAI code reviews and git activity digests with machine-readable risk scoring, available as an MCP server for use within an agent session.1MIT
- FlicenseNot gradedqualityCmaintenanceRuns a multi-agent code review pipeline via MCP, analyzing git diffs for security, quality, and logic issues and returning a pass/fail verdict.-
- AlicenseAqualityAmaintenanceSelf-hosted MCP engine for private code reviews, providing deterministic static analysis and AST-level search over diffs, with findings passed to a review agent of your choice.52AGPL 3.0