Open Enthrium

Máy chủ MCP dành cho Claude Code, Cursor, Windsurf và các ứng dụng khách MCP khác. Kết nối trợ lý AI với PostgreSQL, hệ thống tệp, GitHub, Slack, SSH, v.v.

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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.

License: Apache 2.0 GitHub Release Windows Linux macOS npm Website


What is OE MCP Server?

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.

  • 45+ connector categories — PostgreSQL, MongoDB, S3, GitHub, Slack, Gmail, SSH, REST API, and more
  • Two transport modes — --stdio for Claude Code / Cursor / Windsurf; --serve for cloud or team deployments
  • Persistent memory — memory_set / memory_get / memory_list / memory_delete survive across sessions
  • Action log — every connector call logged automatically with timestamp, tool, input, and result
  • Run AI agents — run_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.
  • Self-hosted — runs on your own machine, no cloud dependency, no call-home

Quick Start via npm (Recommended)

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.


Download (Standalone Binary)

PlatformBinary
Windowsoe-mcp-win.exe
Linuxoe-mcp-linux
macOSoe-mcp-macos
Sample configsoe-mcp-samples.zip

Built-in Tools

Memory

Persistent memory that survives restarts — stored in oe-mcp-memory.json:

ToolDescription
memory_setStore a key-value pair across sessions
memory_getRetrieve a stored value by key
memory_listList all stored key-value pairs
memory_deleteRemove a stored key

"Remember that our production database is on prod-db.company.com" → Claude calls memory_set

Action Log

Every connector call is logged automatically to oe-mcp-log.json:

ToolDescription
log_listList recent connector calls (newest first, supports limit)
log_clearClear all log entries

Run AI Agents

Execute OE Runtime SKILL.md agents or YAML agents directly from Claude Code, Cursor, or any MCP client — no terminal required:

ToolDescription
run_agentRun an agent by file path. Auto skills execute immediately; manual skills pause and return pending_skill_chain.
list_pending_skillsList all manual skills currently paused and waiting for approval
approve_chainApprove, skip, or abort a paused manual skill by chain_id

run_agent parameters:

ParameterRequiredDescription
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:

ParameterRequiredDescription
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.

Agent Skill Approval Flow

When an agent's skill pipeline includes manual skills, Claude handles the approval loop automatically:

  1. Claude calls run_agent → response shows ⏸ Skill awaiting approval with chain_id and skill_name
  2. Claude decides — based on your instructions — whether to approve, skip, or abort
  3. Claude calls approve_chain → next skill runs or the next manual skill pauses again
  4. Repeat until Pipeline complete or Claude aborts

Example 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."


Transport Modes

ModeFlagBest for
stdio--stdioClaude Code, Cursor, Windsurf, Codex, Claude Desktop — launched as child process
HTTP--serve --port 4040Cloud 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
# → http://your-server.com:4040/mcp

Sample Configs

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


Part of Open Enthrium

⚡ Agent Runtimeopen-enthrium-ai-agent-runtime — run SKILL.md agents as CLI or HTTP server
🖥️ Platformopen-enthrium-ai-platform — full web app with workspaces, RAG, Agent Builder
🌐 Websiteopenenthrium.com

Contributing

→ See CONTRIBUTING.md for how to add sample configs and connector adapters.


License

Apache-2.0 — free to use, modify, and deploy for any purpose, including commercial use. No usage limits. No telemetry. No call-home.