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MCP server for the Neo AI/ML backend — submit tasks, poll status, read output

Project description

neo-mcp (pip)

Python MCP server for Neo — submit AI/ML tasks, poll status, read output, and control task lifecycle from any AI editor.

Install it, set your API key, register with your editor — that's it. Everything else is handled automatically.

Get your API key at app.heyneo.so → Settings → API Keys.


Install

pip install neo-mcp

Requires Python 3.11+.

Tip: use pipx install neo-mcp to install in an isolated environment and avoid conflicts with your project's virtualenv.


Connecting to editors

Replace sk-v1-YOUR_KEY with your actual key.


Claude Code

claude mcp add --scope user neo \
  -e NEO_SECRET_KEY=sk-v1-YOUR_KEY \
  -- neo-mcp

Open a new Claude Code session after running this. Neo tools load at session start.

Scope options: --scope user (global, recommended) · --scope project (writes .mcp.json in current repo) · --scope local (this machine only)

Verify it registered:

claude mcp list

Cursor

~/.cursor/mcp.json:

{
  "mcpServers": {
    "neo": {
      "command": "neo-mcp",
      "env": {
        "NEO_SECRET_KEY": "sk-v1-YOUR_KEY"
      }
    }
  }
}

Restart Cursor after editing.


Windsurf

~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "neo": {
      "command": "neo-mcp",
      "env": {
        "NEO_SECRET_KEY": "sk-v1-YOUR_KEY"
      }
    }
  }
}

Restart Windsurf after editing.


VS Code (GitHub Copilot)

.vscode/mcp.json in your workspace root (requires VS Code 1.99+):

{
  "servers": {
    "neo": {
      "type": "stdio",
      "command": "neo-mcp",
      "env": {
        "NEO_SECRET_KEY": "sk-v1-YOUR_KEY"
      }
    }
  }
}

Zed

~/.config/zed/settings.json:

{
  "context_servers": {
    "neo": {
      "source": "custom",
      "command": {
        "path": "neo-mcp",
        "args": [],
        "env": {
          "NEO_SECRET_KEY": "sk-v1-YOUR_KEY"
        }
      }
    }
  }
}

Continue.dev

~/.continue/config.json:

{
  "mcpServers": [
    {
      "name": "neo",
      "transport": {
        "type": "stdio",
        "command": "neo-mcp",
        "env": {
          "NEO_SECRET_KEY": "sk-v1-YOUR_KEY"
        }
      }
    }
  ]
}

OpenAI Codex CLI

~/.codex/config.json:

{
  "mcpServers": {
    "neo": {
      "command": "neo-mcp",
      "env": {
        "NEO_SECRET_KEY": "sk-v1-YOUR_KEY"
      }
    }
  }
}

Tools

Tool Description
neo_submit_task Submit an AI/ML task. Returns thread_id immediately.
neo_list_tasks List running and recent tasks — reconnects pollers automatically.
neo_task_status Check status: RUNNING / COMPLETED / WAITING_FOR_FEEDBACK / PAUSED / TERMINATED.
neo_get_messages Read full task output when COMPLETED. Capped at ~20 000 tokens.
neo_send_feedback Reply when Neo asks a question (WAITING_FOR_FEEDBACK).
neo_pause_task Pause a running task.
neo_resume_task Resume a paused task.
neo_stop_task Stop and clean up a task permanently.

Environment variables

Variable Required Description
NEO_SECRET_KEY Yes Your Neo API key (sk-v1-...) from app.heyneo.so
NEO_DEPLOYMENT_ID No Pin a specific deployment UUID (auto-generated and persisted by default)
NEO_WORKSPACE_DIR No Override working directory (useful in Docker)
NEO_READ_ONLY No true — expose only status/message tools, disable submit/stop/pause

Troubleshooting

Symptom Fix
neo-mcp: command not found Re-run pip install neo-mcp and verify your PATH with which neo-mcp
Tools don't appear after registering Open a new session — MCP tools load at session start, not mid-session
Invalid API key (401) Re-check your key at app.heyneo.so → Settings → API Keys
Trial or quota ended (403) Top up at the Neo dashboard
Task submitted but no files written Daemon failed to start — run neo-mcp doctor to diagnose
Status stuck on RUNNING Call neo_task_status to check; run neo-mcp status to inspect the daemon

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