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CLIO Agent — Autonomous AI agent framework for scientific data management. Part of the IOWarp platform.

Project description

CLIO Agent — Cognitive Layer for Adaptive Universal Data & Intelligent Operations

Python 3.12+ UV FastMCP IOWarp


What is CLIO Agent?

An autonomous agent for scientific data management — HDF5, Parquet, and CSV inspection through a FastMCP tool gateway, with a Bubbletea terminal UI (gact) for interactive work. CLIO is the Intelligence Layer (CEI) of the IOWarp platform.

The agent runs in three tiers: a main orchestrator (planner loop over registered tools and experts), domain experts (data / analysis / visualization), and ephemeral nanoagents for parallel sub-tasks. State lives in a local-first memory layer (ARC) that all tiers read and write.

  • Multi-expert orchestration with capability-based routing
  • FastMCP tool gateway, HDF5 + Parquet servers out of the box
  • ARC memory with O(log N) context retrieval
  • Optimizer layer for offline tuning + online learning
  • Runtime doctor for LM / gateway / file-policy health
  • Works with LM Studio, Ollama, OpenAI, Anthropic, OpenRouter, OpenAI Codex subscriptions, and the Argonne ALCF inference gateway

Quick Start

One line installs clio-agent from PyPI, downloads the matching CLIO-branded TUI binary for your platform, and drops a clio command on your PATH.

Linux / macOS

curl -fsSL https://raw.githubusercontent.com/iowarp/clio-agent/main/install/install.sh | bash
clio

Windows (PowerShell)

irm https://raw.githubusercontent.com/iowarp/clio-agent/main/install/install.ps1 | iex
clio

clio boots the server (if it isn't already up) and attaches the TUI. On first connect, pick an LM provider in the modal and you're chatting.

Prerequisites for the default release install: uv or Python 3.12+ with pip. git and Go are only needed when you opt into source-build mode with CLIO_REF or GACT_REF.


Using the clio command

clio with no arguments is the one-command UX. The subcommands manage the backing server without hunting PIDs:

Command What it does
clio ensure the server is up, then attach the TUI
clio start / stop / restart server lifecycle (process-tree kill on stop)
clio status / ps PID, port, health
clio logs [N] tail server + TUI stderr logs
clio doctor check prerequisites and install layout
clio report diagnostics bundle for filing GitHub issues
clio completion <shell> tab-completion (bash / zsh / powershell)
clio uninstall remove CLIO (--purge / -Purge to drop config too)

Override paths with CLIO_PREFIX / CLIO_BIN_DIR and the server port with CLIO_PORT. Full install + uninstall reference: install/README.md.


Architecture

CLIO Agent architecture: user interfaces, the Intelligence Layer (CEI) with the orchestrator and tier-2 experts, tier-3 nanoagents, ARC memory, the optimizer layer, and CTE multi-tier storage

For the design rationale (three-tier hierarchy, ARC memory, optimizer layer, IOWarp integration), see docs/CLIO_AGENT_ARCHITECTURE.md.


Documentation

Doc What's in it
docs/CLIO_AGENT_ARCHITECTURE.md Three-tier design, ARC memory, optimizer layer
docs/SYSTEM_IDENTITY.md What the agent is, design principles
docs/SETUP.md Release install, source-build install, and smoke test
docs/CONTRIBUTOR_QUICKSTART.md Dev environment, quality checks, where to put code
docs/MCP_TOOL_INTEGRATION.md Adding tools via FastMCP
docs/EXPERT_SYSTEM_DESIGN.md Adding new experts
docs/ARC_MEMORY_LAYER.md Memory model and storage
docs/SELF_IMPROVEMENT.md Optimizer layer
docs/PERMISSIONS.md Tool permission system
docs/providers/ LM provider configuration
docs/CAPABILITIES_MATRIX.md Feature matrix
PLAN.md Roadmap

Contributing

Start with docs/CONTRIBUTOR_QUICKSTART.md. For guidance specific to AI agents working on the codebase, see AGENTS.md.


License + Citation

BSD-3-Clause.

@software{clioagent2026,
  title  = {CLIO Agent: Autonomous Agent for Scientific Data Management},
  author = {IOWarp Team},
  year   = {2026},
  url    = {https://github.com/iowarp/clio-agent},
}

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