Open Enterprise AI MCP Server
OfficialEnables interaction with Elasticsearch for searching and analyzing data.
Adds tools for managing GitHub repositories, issues, pull requests, and code search.
Provides access to Gmail for reading and sending email through OAuth.
Adds tools for managing files and folders on Google Drive, including listing, reading, creating, and searching.
Provides access to HubSpot CRM to manage contacts and other CRM data.
Provides tools for interacting with Jira issues and projects.
Provides a query tool for running MongoDB queries and aggregations.
Provides a tool to run SQL queries against a MySQL database, allowing interaction with tables and data.
Provides a tool to run SQL queries against a PostgreSQL database, allowing interaction with tables and data.
Enables interaction with Redis for data retrieval and management.
Adds tools for Slack channel management, message posting, and reading conversations.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Open Enterprise AI MCP ServerQuery the postgres connector for the top 10 customers by revenue."
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Connect any AI coding assistant to your enterprise data — databases, files, APIs, and more — via a single binary.
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 —
--stdiofor Claude Code / Cursor / Windsurf;--servefor cloud or team deploymentsPersistent memory —
memory_set / memory_get / memory_list / memory_deletesurvive across sessionsAction log — every connector call logged automatically with timestamp, tool, input, and result
Run AI agents —
run_agentexecutes any OE Runtime SKILL.md agent directly from Claude Code, Cursor, or any MCP client. Manual skills pause for approval viaapprove_chain.Self-hosted — runs on your own machine, no cloud dependency, no call-home
Related MCP server: ContextStream MCP Server
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"]
}
}
}
-yis 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 | |
Linux | |
macOS | |
Sample configs |
Built-in Tools
Memory
Persistent memory that survives restarts — stored in oe-mcp-memory.json:
Tool | Description |
| Store a key-value pair across sessions |
| Retrieve a stored value by key |
| List all stored key-value pairs |
| 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 |
| List recent connector calls (newest first, supports |
| 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 an agent by file path. Auto skills execute immediately; manual skills pause and return |
| List all manual skills currently paused and waiting for approval |
| Approve, skip, or abort a paused manual skill by |
run_agent parameters:
Parameter | Required | Description |
| ✅ | Absolute path to |
| ❌ | Key-value pairs substituted via |
| ❌ | Optional initial message passed to the agent |
approve_chain parameters:
Parameter | Required | Description |
| ✅ | From |
| ❌ |
|
| ❌ |
|
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:
Claude calls
run_agent→ response shows⏸ Skill awaiting approvalwithchain_idandskill_nameClaude decides — based on your instructions — whether to approve, skip, or abort
Claude calls
approve_chain→ next skill runs or the next manual skill pauses againRepeat until
Pipeline completeor 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 |
| Claude Code, Cursor, Windsurf, Codex, Claude Desktop — launched as child process |
HTTP |
| 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/mcpSample 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 |
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
Tool Schema Changelog
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No tool schema history has been recorded yet.
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If you are the server author, to access and configure the admin panel.
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