trackmcp
Back to directory
enthrium

open-enthrium-ai-mcp-server

View on GitHub

MCP server exposing a rich enterprise connector catalog for Claude Code, Cursor, Windsurf, and any MCP client

1 stars JavaScriptOthers Updated Sep 3, 2026
binaryclaude-codeclaude-code-pluginclaude-desktopclaude-plugincursormcpmodel-context-protocolopen-sourcewindsurfwindsurf-extensionyamlmcp-tools

Documentation


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

1. Create `oe-mcp.json`:

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:

json
{
  "mcpServers": {
    "oe-mcp": {
      "type": "stdio",
      "command": "npx",
      "args": ["-y", "@openenthrium/oe-mcp", "--stdio", "/path/to/oe-mcp.json"]
    }
  }
}

Windows:

json
{
  "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_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`:

ToolDescription
`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:

ToolDescription
`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:

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`--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:

bash
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.


Frequently asked questions

What is open-enthrium-ai-mcp-server?

open-enthrium-ai-mcp-server is MCP server exposing a rich enterprise connector catalog for Claude Code, Cursor, Windsurf, and any MCP client

How do I install open-enthrium-ai-mcp-server?

Open the GitHub repository and follow its README. Most MCP servers are added to your client's MCP config, then called by your agent.

Is open-enthrium-ai-mcp-server open source?

Yes — it is hosted on GitHub at https://github.com/enthrium/open-enthrium-ai-mcp-server and has 1 stars.

Related MCP tools

IvanMurzakUnity-MCP

AI Skills, MCP Tools, and CLI for Unity Engine. Full AI develop and test loop. Use cli for quick setup. Efficient token usage, advanced tools. Any C# method may be turned into a tool by a single line. Works with Claude Code, Gemini, Copilot, Cursor and any other absolutely for free.

4,137 C#
aiai-integrationgame-development+16
jgravellejcodemunch-mcp

Cut AI token costs 95%+ on code exploration. The leading MCP server for precise, symbol-level GitHub code retrieval via tree-sitter AST. Works with Claude Code, Cursor & any MCP client. 313B+ tokens saved.

2,651 Python
claudeclaude-codeai-coding+17
AVIDS2memorix

Open-source cross-agent memory layer for coding agents via MCP. Compatible with Claude Code, Codex, Cursor, Windsurf, Gemini CLI, Antigravity, OpenClaw, Hermes Agent, Oh-my-Pi, Pi, Copilot, Kiro, OpenCode, and Trae.

721 TypeScript
ai-codingclaude-codecopilot+17
atlassianatlassian-mcp-server

Official remote MCP server for Atlassian. Securely connect Jira, Confluence, Jira Service Management, Bitbucket, and Compass to Claude, ChatGPT, Cursor, VS Code, and other AI tools using OAuth 2.1 or API tokens.

1,015 JavaScript
aiai-agentsatlassian+17
riponcmprojectmem

Open-source coding agent memory. Records issues, attempts, fixes and decisions, then warns your agent before it repeats an approach that already failed. Native MCP server for Claude Code, Cursor, Antigravity and Codex. 100% local, no cloud, no telemetry. MIT.

796 Python
ai-agentsai-memoryai-tools+17
firecrawlfirecrawl-mcp-server

🔥 Official Firecrawl MCP Server - Adds powerful web scraping and search to Cursor, Claude and any other LLM clients.

7,393 JavaScript
batch-processingclaudecontent-extraction+11

Run your own MCP server? See who uses it and what to fix.

Measure it with TrackMCP