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enthrium

Open Enterprise AI MCP Server

Official
by enthrium

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 memorymemory_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 agentsrun_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


Related MCP server: ContextStream MCP Server

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)

Platform

Binary

Windows

oe-mcp-win.exe

Linux

oe-mcp-linux

macOS

oe-mcp-macos

Sample configs

oe-mcp-samples.zip


Built-in Tools

Memory

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

Action Log

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

Run AI Agents

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.

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

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
# → 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 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


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.


⭐ Star this repo  ·  🌐 Website  ·  ⚡ Agent Runtime

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