Neo — AI/ML Engineering MCP Server

AI/ML engineering MCP server for Neo — submit tasks, track execution, and retrieve outputs.

Local serverstdioPython

What is the Neo — AI/ML Engineering MCP server?

AI/ML engineering MCP server for Neo — submit tasks, track execution, and retrieve outputs. That is what the neo — ai/ml engineering mcp server brings to an AI assistant: the same capability, reachable through the Model Context Protocol rather than a separate app or dashboard.

The short version

Neo is built for AI engineering, not general code chat, so it goes deeper on ML, LLM, and data workflows than a typical coding agent.

Getting it running

Installation goes through your MCP client rather than a global install: point it at neo-mcp on PyPI and it is fetched when the client starts. The copy-paste blocks for Claude Desktop, Claude Code and Cursor are further down this page.

The tools it exposes

The server publishes 13 tools. What each one is for:

  • 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
  • neo_list_integrations — List stored third-party API keys (names only, never the value)
  • neo_add_integration — Register a GitHub PAT, HuggingFace token, Anthropic key, or OpenRouter key for Neo tasks
  • neo_test_integration — Call the provider's API to confirm a stored key is still valid
  • neo_remove_integration — Delete a stored key from this machine

What it needs from you

Configuration is passed through the environment: NEO_SECRET_KEY, YOUR_KEY, NEO_DEPLOYMENT_ID. Treat anything key-shaped as a real credential — scope it to the minimum the server needs, and rotate it if it ever lands in a shared config.

Things to watch

  • It runs with your machine's permissions. That is convenient and also the reason to think about what you point it at before you approve a tool call.
  • With 13 tools registered it takes up a noticeable share of the context window; turn it off in projects that never touch Neo — AI/ML Engineering.
  • Missing credentials fail quietly in some clients — if no tools show up, check the environment block first.
  • Keep per-call confirmation enabled while you learn its behaviour; it is the cheapest safeguard you have.

How it compares

Plenty of planning and project tracking servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. Neo — AI/ML Engineering's toolset — neo_submit_task, neo_list_tasks, neo_task_status and 10 more — is a fair guide to whether it matches your workflow. It is maintained by NeoAIResearch; worth a glance at recent repository activity before you build anything load-bearing on it.

SyncDev reviews every entry in this directory against the project's own documentation before publishing, and revisits them as servers change.

Available tools

ToolWhat it does
neo_submit_taskSubmit an AI/ML task. Returns thread_id immediately.
neo_list_tasksList running and recent tasks. Reconnects pollers automatically.
neo_task_statusCheck status: RUNNING / COMPLETED / WAITING_FOR_FEEDBACK / PAUSED / TERMINATED.
neo_get_messagesRead full task output when COMPLETED. Capped at ~20 000 tokens.
neo_send_feedbackReply when Neo asks a question (WAITING_FOR_FEEDBACK).
neo_pause_taskPause a running task.
neo_resume_taskResume a paused task.
neo_stop_taskStop and clean up a task permanently.
neo_list_integrationsList stored third-party API keys (names only, never the value).
neo_add_integrationRegister a GitHub PAT, HuggingFace token, Anthropic key, or OpenRouter key for Neo tasks.
neo_test_integrationCall the provider's API to confirm a stored key is still valid.
neo_remove_integrationDelete a stored key from this machine.
CursorRestart Cursor after editing the file directly. Changes via the GUI apply immediately.

How to install the Neo — AI/ML Engineering MCP server

{
  "mcpServers": {
    "neo": {
      "command": "uvx",
      "args": ["neo-mcp"],
      "env": {
        "NEO_SECRET_KEY": "your-value",
        "YOUR_KEY": "your-value",
        "NEO_DEPLOYMENT_ID": "your-value"
      }
    }
  }
}

Add to claude_desktop_config.json, then restart Claude Desktop.

Configuration

VariableDescriptionRequired
NEO_SECRET_KEYCredential the server authenticates with.Yes
YOUR_KEYCredential the server authenticates with.Yes
NEO_DEPLOYMENT_IDConfiguration value read at startup.Optional

Example prompts to try

  • Use Neo — AI/ML Engineering to neo submit task.
  • Use Neo — AI/ML Engineering to neo list tasks.
  • Use Neo — AI/ML Engineering to neo task status.

Frequently asked questions

It connects Neo — AI/ML Engineering to MCP-compatible AI assistants such as Claude and Cursor, exposing 13 tools (neo_submit_task, neo_list_tasks, neo_task_status, and more) that the assistant can call on your behalf. Instead of copying data back and forth by hand, the assistant works with Neo — AI/ML Engineering directly.