GitHub
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
作者提供的说明(英文原文)
Connect Claude Code, Cursor & Windsurf to 2,600+ enterprise data sources with one binary.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
OE_MCP_CONFIG_PATH你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"oe": {
"command": "npx",
"args": [
"-y",
"@openenterprise/oe-mcp",
"--stdio",
"${OE_MCP_CONFIG_PATH}"
],
"env": {
"OE_MCP_CONFIG_PATH": "your-value"
}
}
}
}在终端中运行这条命令
claude mcp add oe --env OE_MCP_CONFIG_PATH=your-value -- npx -y @openenterprise/oe-mcp --stdio '${OE_MCP_CONFIG_PATH}'运行前请先填写空着的值。
粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"oe": {
"command": "npx",
"args": [
"-y",
"@openenterprise/oe-mcp",
"--stdio",
"${OE_MCP_CONFIG_PATH}"
],
"env": {
"OE_MCP_CONFIG_PATH": "your-value"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"oe": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@openenterprise/oe-mcp",
"--stdio",
"${OE_MCP_CONFIG_PATH}"
],
"env": {
"OE_MCP_CONFIG_PATH": "your-value"
}
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月9日
注册名称已通过 GitHub 账户 openenterprise-info 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
你需要填写:OE_MCP_CONFIG_PATH
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(1.4.4)于3个月前进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Node.js。
同一分类中有:GitHub, Desktop Commander, Cloudflare MCP
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:↓ 每周下载量i★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
Connect AI assistants to GitHub - manage repos, issues, PRs, and workflows through natural language.
MCP server for terminal commands, file operations, and process management
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
Open Enthrium AI MCP Server Enterprise MCP Server · Apache-2.0 · Claude Code · Cursor · Windsurf · Codex · Claude Desktop · VS Code
Connect any AI coding assistant to your enterprise data — databases, files, APIs, and more — via a single binary.
A standalone binary that implements the Model Context Protocol (MCP) and exposes your enterprise data sources as tools that AI apps can use directly. No code. Define connectors in a single JSON file.
--stdio for Claude Code / Cursor / Windsurf; --serve for cloud or team deploymentsmemory_set / memory_get / memory_list / memory_delete survive across sessionsrun_agent executes any OE Runtime SKILL.md agent directly from Claude Code, Cursor, or any MCP client. Manual skills pause for approval via approve_chain.1. Create `oe-mcp.json`:
{
"connectors": [ { "name": "my-postgres", "type": "postgresql", "host": "localhost", "port": 5432, "database": "mydb", "user": "postgres", "password": "secret" }, { "name": "my-codebase", "type": "filesystem", "basePath": "/home/user/projects/myapp" } ], "memory": [ { "key": "project_context", "value": "This is our main application." } ] }
2. Add to your AI app's MCP config:
macOS / Linux:
{
"mcpServers": { "oe-mcp": { "type": "stdio", "command": "npx", "args": ["-y", "@openenthrium/oe-mcp", "--stdio", "/path/to/oe-mcp.json"] } } }
Windows:
{
"mcpServers": { "oe-mcp": { "type": "stdio", "command": "npx.cmd", "args": ["-y", "@openenthrium/oe-mcp", "--stdio", "C:\\path\\to\\oe-mcp.json"] } } }
`-y` is required — without it npx blocks waiting for keyboard input and the MCP connection never opens.
3. Reload your AI app — connectors appear as tools automatically.
Ask Claude: _"What connectors do you have access to?"_ to verify.
| Platform | Binary |
|---|---|
| Windows | oe-mcp-win.exe |
| Linux | oe-mcp-linux |
| macOS | oe-mcp-macos |
| Sample configs | oe-mcp-samples.zip |
Persistent memory that survives restarts — stored in oe-mcp-memory.json:
| Tool | Description |
|---|---|
memory_set | Store a key-value pair across sessions |
memory_get | Retrieve a stored value by key |
memory_list | List all stored key-value pairs |
memory_delete | Remove a stored key |
_"Remember that our production database is on prod-db.company.com"_ → Claude calls
memory_set
Every connector call is logged automatically to oe-mcp-log.json:
| Tool | Description |
|---|---|
log_list | List recent connector calls (newest first, supports limit) |
log_clear | Clear all log entries |
Execute OE Runtime SKILL.md agents or YAML agents directly from Claude Code, Cursor, or any MCP client — no terminal required:
| Tool | Description |
|---|---|
run_agent | Run an agent by file path. Auto skills execute immediately; manual skills pause and return pending_skill_chain. |
list_pending_skills | List all manual skills currently paused and waiting for approval |
approve_chain | Approve, skip, or abort a paused manual skill by chain_id |
`run_agent` parameters:
| Parameter | Required | Description |
|---|---|---|
file | ✅ | Absolute path to agent.yaml |
params | ❌ | Key-value pairs substituted via {{key}} in the agent |
input | ❌ | Optional initial message passed to the agent |
`approve_chain` parameters:
| Parameter | Required | Description |
|---|---|---|
chain_id | ✅ | From pending_skill_chain.chain_id in a run_agent response |
approved | ❌ | true to run the skill (default), false to skip it and continue |
abort | ❌ | true to stop the entire pipeline immediately |
OE MCP looks for oe-config.json in the agent's directory first, then falls back to oe-mcp.json.
When an agent's skill pipeline includes manual skills, Claude handles the approval loop automatically:
run_agent → response shows ⏸ Skill awaiting approval with chain_id and skill_nameapprove_chain → next skill runs or the next manual skill pauses againPipeline complete or Claude abortsExample instruction to Claude Code: _"Run the OE Skills orchestrator and send a Slack message — skip anything you can't do, abort if it asks for credentials."_
| Mode | Flag | Best for |
|---|---|---|
| stdio | --stdio | Claude Code, Cursor, Windsurf, Codex, Claude Desktop — launched as child process |
| HTTP | --serve --port 4040 | Cloud deployments, sharing one server across a team |
HTTP mode — start the server, then add the URL to Cursor / Windsurf / Claude Desktop:
oe-mcp-linux --serve --port 4040 /path/to/oe-mcp.json
Download oe-mcp-samples.zip — ready-to-use oe-mcp.json for common connectors:
postgres · mysql · mongodb · github · slack · gdrive · ssh · filesystem · oracle · salesforce · servicenow · telegram · notion · confluence · graphql · zoho-mail · sftp · dropbox · multi-connector
| ⚡ Agent Runtime | open-enthrium-ai-agent-runtime — run SKILL.md agents as CLI or HTTP server |
| 🖥️ Platform | open-enthrium-ai-platform — full web app with workspaces, RAG, Agent Builder |
| 🌐 Website | openenthrium.com |
→ See [CONTRIBUTING.md](CONTRIBUTING.md) for how to add sample configs and connector adapters.
Apache-2.0 — free to use, modify, and deploy for any purpose, including commercial use. No usage limits. No telemetry. No call-home.
[⭐ Star this repo](https://github.com/enthrium/open-enthrium-ai-mcp-server) · [🌐 Website](https://www.openenthrium.com) · [⚡ Agent Runtime](https://github.com/enthrium/open-enthrium-ai-agent-runtime)