Oe Mcp

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)

Built-in Tools

Memory

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

"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:

Run AI Agents

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

run_agent parameters:

approve_chain parameters:

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

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

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.