MCP server powered by the Nodus orchestration runtime
Project description
nodus-mcp-server
An MCP server that connects AI assistants to the Nodus language runtime — giving them persistent memory, sandboxed code execution, and checkpoint/resume orchestration workflows, all powered by .nd scripts running on the Nodus VM.
Supports Claude Desktop (stdio) and ChatGPT Desktop (HTTP/SSE).
Tools
| Tool | What it does |
|---|---|
nodus_remember |
Store a fact in persistent memory with optional tags |
nodus_recall |
Search memory by free-text query and/or tags |
nodus_forget |
Delete a memory entry by ID |
nodus_run_goal |
Run a built-in Nodus goal (structured multi-step result) |
nodus_run_workflow |
Run a built-in Nodus workflow (returns a graph_id for resuming) |
nodus_resume_workflow |
Resume a workflow from a checkpoint using its graph_id |
nodus_exec |
Execute arbitrary Nodus code in a sandbox (no file I/O, no network, no subprocess, 10 s timeout) |
Requirements
- Python ≥ 3.10
- pipx (recommended — keeps the server in its own isolated environment)
- Claude Desktop or ChatGPT Desktop (the downloadable apps, not browser versions)
Install
pipx install nodus-mcp-server
Claude Desktop setup
1. Find your config file
| Setup | Config path |
|---|---|
| Standard install | %APPDATA%\Claude\claude_desktop_config.json |
| Windows Store app | %LOCALAPPDATA%\Packages\Claude_pzs8sxrjxfjjc\LocalCache\Roaming\Claude\claude_desktop_config.json |
| macOS | ~/Library/Application Support/Claude/claude_desktop_config.json |
2. Add the server
{
"mcpServers": {
"nodus": {
"command": "nodus-mcp-server",
"args": ["--stdio"]
}
}
}
If nodus-mcp-server isn't on your PATH, use the full path to the executable. On Windows with pipx that's typically C:\Users\<you>\.local\bin\nodus-mcp-server.exe.
3. Restart Claude Desktop
The seven nodus_* tools will appear when you click the tools icon (the + button or tool picker) in a new conversation.
How to use
Memory
Store anything you want Claude to remember across conversations:
Use nodus_remember to store: "Project deadline is 2026-07-01" with tags ["project", "deadlines"]
Retrieve it later:
Use nodus_recall to find memories tagged "deadlines"
Or search by content:
Use nodus_recall to find memories about "deadline"
Memory is stored in a local SQLite database at ~/.nodus-mcp-server/data/memory.db and persists across upgrades.
Sandboxed code execution
Run Nodus (.nd) code in a fully sandboxed runtime:
Use nodus_exec to run: print("Hello from Nodus!")
The sandbox enforces: no file I/O, no network, no subprocess. Use print() to surface results — top-level return values are not captured.
Goals (structured multi-step tasks)
Goals run a fixed sequence of named steps and return each step's result:
Use nodus_run_goal with name "summarize" and params {"text": "your text here"}
Built-in goals:
| Goal | Params | What it does |
|---|---|---|
summarize |
{text} |
Counts characters, classifies size (short/medium/long) |
pipeline |
{items, label} |
Validates a list and produces a labelled report |
Workflows (checkpoint/resume orchestration)
Workflows are like goals but support checkpoints — they can be paused and resumed from a saved state:
Use nodus_run_workflow with name "research" and params {"topic": "LLM context windows"}
The response includes a graph_id. Use it to resume the workflow later:
Use nodus_resume_workflow with graph_id "g_abc123" (and optionally a checkpoint label)
Built-in workflows:
| Workflow | Params | What it does |
|---|---|---|
research |
{topic} |
Two-step plan + execute workflow with checkpoints at each step |
Adding your own goals and workflows
Goals and workflows are .nd files (Nodus source) placed in the goals/ or workflows/ directory of the installed package. The file should only define the goal or workflow — the server calls it for you.
// goals/my_goal.nd
goal my_goal {
step process {
if (input_text == nil) { throw "missing required param: input_text" }
let result = len(input_text)
return {"length": result, "has_content": result > 0i}
}
}
Then call it:
{"name": "my_goal", "params": {"input_text": "hello"}}
Input params are injected as top-level variables in the .nd execution context. Check nil before using them — missing params surface as nil, not an error, unless you throw explicitly.
See the Nodus language guide for the full .nd syntax reference.
About Nodus
The goals, workflows, and nodus_exec sandbox all run on the Nodus VM — a lightweight, embeddable language runtime designed for AI-native orchestration. Nodus scripts (.nd files) define the step logic; the MCP server wires them to Claude over the Model Context Protocol.
Architecture
server.py — MCP tool definitions, NodusRuntime setup, request dispatch
runner.py — goal/workflow execution via ModuleLoader + VM
memory_store.py — SQLite-backed thread-safe memory store
goals/ — .nd goal definitions (bundled + custom)
workflows/ — .nd workflow definitions (bundled + custom)
~/.nodus-mcp-server/data/memory.db — SQLite DB (persists across upgrades)
ChatGPT Desktop setup
ChatGPT requires a public HTTPS URL (not localhost). Use ngrok to expose the server.
1. Start the HTTP server
nodus-mcp-server --http --port 8765
This prints:
[nodus-mcp-server] HTTP listening on http://127.0.0.1:8765/mcp
[nodus-mcp-server] Point ChatGPT / your MCP client at: http://127.0.0.1:8765/mcp
2. Expose via ngrok
ngrok http --url=<your-static-domain>.ngrok.io 8765
Keep both terminals open while using ChatGPT.
3. Connect in ChatGPT Desktop
- Click your profile icon → Settings → Apps
- Go to Advanced Settings → enable Developer Mode
- Click Create App (or Connect more)
- Enter a name (e.g.
Nodus), description, and base URL:https://<your-static-domain>.ngrok.io/mcp
4. Use in a chat
Open a new chat → click + → More → Developer Mode → enable your Nodus app. The seven nodus_* tools are now available.
Note: Memory is shared with the Claude Desktop instance (same SQLite database at
~/.nodus-mcp-server/data/memory.db).
Upgrading
Stop-Process -Name "nodus-mcp-server" -Force # Windows — close before reinstalling
pipx install nodus-mcp-server --force
Then restart Claude Desktop / ChatGPT Desktop.
License
MIT
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