经 AI Skill Hub 精选评估,EDDI 获评「强烈推荐」。这款MCP工具在功能完整性、社区活跃度和易用性方面表现出色,AI 评分 8.0 分,适合有一定技术背景的用户使用。
EDDI 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
EDDI 是一款遵循 MCP(Model Context Protocol)标准协议的 AI 工具扩展。通过 MCP 协议,它可以让 Claude、Cursor 等主流 AI 客户端直接访问和操作外部工具、数据源和服务,实现 AI 能力的无缝扩展。无论是文件操作、数据库查询还是 API 调用,都可以通过自然语言在 AI 对话中直接触发,极大提升生产效率。
# 方式一:通过 Claude Code CLI 一键安装
claude skill install https://github.com/labsai/EDDI
# 方式二:手动配置 claude_desktop_config.json
{
"mcpServers": {
"eddi": {
"command": "npx",
"args": ["-y", "eddi"]
}
}
}
# 配置文件位置
# macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
# Windows: %APPDATA%/Claude/claude_desktop_config.json
# 安装后在 Claude 对话中直接使用 # 示例: 用户: 请帮我用 EDDI 执行以下任务... Claude: [自动调用 EDDI MCP 工具处理请求] # 查看可用工具列表 # 在 Claude 中输入:"列出所有可用的 MCP 工具"
// claude_desktop_config.json 配置示例
{
"mcpServers": {
"eddi": {
"command": "npx",
"args": ["-y", "eddi"],
"env": {
// "API_KEY": "your-api-key-here"
}
}
}
}
// 保存后重启 Claude Desktop 生效
E.D.D.I (Enhanced Dialog Driven Interface) is a production-grade, config-driven multi-agent orchestration middleware for conversational AI. It coordinates users, AI agents, and business systems through intelligent routing, persistent memory, and API orchestration — without writing code.
Built with Java 25 and Quarkus. Ships as a Red Hat-certified Docker image. Native support for MCP (Model Context Protocol), A2A (Agent-to-Agent), Slack, OpenAPI, and OAuth 2.0.
Latest version: 6.1.0 · Website · Documentation · License: Apache 2.0
---
| Tool | Version | Notes |
|---|---|---|
| **Java (JDK)** | 25 | [Eclipse Temurin](https://adoptium.net/) recommended |
| **Maven** | 3.9+ | Bundled via mvnw / mvnw.cmd wrapper — no install needed |
| **MongoDB** | 6.0+ | Local instance or Docker (docker run -d -p 27017:27017 mongo:7) |
| **Docker** | Latest | For integration tests and container builds |
Windows users: Replace./mvnwwith.\mvnw.cmdin all commands below.
If you prefer manual control over Docker Compose:
```bash
```bash
./mvnw clean package '-Dquarkus.container-image.build=true'
./mvnw package -DskipTests
kubectl apply -f https://raw.githubusercontent.com/labsai/EDDI/main/k8s/quickstart.yaml
The fastest way to get EDDI running is the one-command installer. It sets up EDDI + your choice of database via Docker Compose, deploys the Agent Father starter agent, and walks you through creating your first AI agent.
Linux / macOS / WSL2:
curl -fsSL https://raw.githubusercontent.com/labsai/EDDI/main/install.sh | bash
Windows (PowerShell):
Invoke-WebRequest -UseBasicParsing -Uri "https://raw.githubusercontent.com/labsai/EDDI/main/install.ps1" -OutFile "install.ps1"
Unblock-File .\install.ps1
.\install.ps1
Requires Docker. The wizard auto-generates a unique vault encryption key for secret management.
<details> <summary><strong>🔧 Installer options</strong></summary>
bash install.sh --defaults # All defaults, no prompts
bash install.sh --db=postgres --with-auth # PostgreSQL + Keycloak
bash install.sh --full # Everything enabled (DB + auth + monitoring)
bash install.sh --local # Build Docker image from local source
The --local flag is for contributors testing pre-release builds:
./mvnw package -DskipTests # Build the Java app
bash install.sh --local # Build Docker image + start containers
</details>
{{snippets.safety_rules}}Building a Quarkus app that talks to EDDI? Use the quarkus-eddi extension:
<dependency>
<groupId>io.quarkiverse.eddi</groupId>
<artifactId>quarkus-eddi</artifactId>
<version>6.1.0</version>
</dependency>
@Inject EddiClient eddi;
String answer = eddi.chat("my-agent", "Hello!");
Features: Dev Services (auto-starts EDDI in dev mode), fluent API, SSE streaming, @EddiAgent endpoint wiring, @EddiTool MCP bridge. See the quarkus-eddi README for full docs.
---
| Command | What It Does |
|---|---|
./mvnw compile quarkus:dev | **Start dev mode** with live reload (port 7070) |
./mvnw compile | Compile sources only (fast feedback) |
./mvnw clean compile | Clean build — delete target/ and recompile from scratch |
./mvnw test | Run **unit tests** (excludes *IT.java integration tests) |
./mvnw verify -DskipITs | Compile + unit tests + package (no integration tests) |
./mvnw verify | **Full build** — compile + unit tests + integration tests (requires Docker) |
./mvnw validate | Run **Checkstyle** code style checks |
./mvnw formatter:format | **Auto-format** Java sources using the project Eclipse formatter |
./mvnw package -DskipTests | Build the JAR without running tests (for install.sh --local) |
./mvnw clean package '-Dquarkus.container-image.build=true' | Build the app **+ Docker image** |
./mvnw package -Plicense-gen -DskipTests | Generate **third-party licenses** (Red Hat certification) |
./mvnw quarkus:dev -Dsuspend | Start dev mode and **wait for debugger** on port 5005 |
./mvnw quarkus:dev -Ddebug=false | Start dev mode **without** the debug agent |
<details> <summary><strong>Code coverage</strong></summary>
JaCoCo is configured to run automatically during ./mvnw test. After tests complete, find the coverage report at:
target/site/jacoco/index.html
</details>
<details> <summary><strong>Useful system properties</strong></summary>
| Property | Default | Description |
|---|---|---|
-Dquarkus.http.port=<port> | 7070 | Override the HTTP port |
-Dquarkus.mongodb.connection-string=<uri> | mongodb://localhost:27017 | MongoDB connection |
-Dquarkus.profile=<profile> | dev | Active Quarkus profile (dev, test, prod) |
-DskipTests | false | Skip all tests |
-DskipITs | true | Skip integration tests only |
</details>
高质量的开源MCP工具,易于使用
AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。
建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。
✅ Apache 2.0 — 宽松开源协议,可商用,需保留版权声明和 NOTICE 文件,含专利授权条款。
AI Skill Hub 点评:EDDI 的核心功能完整,质量优秀。对于Claude Desktop / Claude Code 用户来说,这是一个值得纳入个人工具库的选择。建议先在非生产环境试用,再逐步推广。
| 原始名称 | EDDI |
| Topics | ai-agentsai-orchestrationchatbotjava |
| GitHub | https://github.com/labsai/EDDI |
| License | Apache-2.0 |
| 语言 | Java |
收录时间:2026-06-03 · 更新时间:2026-06-03 · License:Apache-2.0 · AI Skill Hub 不对第三方内容的准确性作法律背书。
选择 Agent 类型,复制安装指令后粘贴到对应客户端