Skip to main content

Elephant Agent CLI-first persistent agent runtime.

Project description

Elephant Agent follows a personal path with people, places, risks, rhythms, decisions, and a Personal Model

Elephant Agent

Do more without thinking less.
A Mother Elephant that grows to understand you, then helps shape the paths you are trying to move.

Website · Blog · Paper

What It Is

Elephant Agent starts from the person, not the task.

The mother elephant grows a correctable Personal Model of who you are, what surrounds you, what is alive right now, and what your path has taught you. That understanding keeps deepening through interaction, correction, and gentle questions.

Once Elephant Agent understands enough, it can help design living Paths: work, health, habits, learning, relationships, recovery, research, code, and any other long-running direction you want to move. It can break a Path into Steps, bring in baby elephants when useful, and return to you at Checkpoints where your judgment matters.

Personal Agent Levels

Four levels of personal AI with Elephant Agent positioned at L4

L1
Executes tasks.
Claude Code, Cursor, Devin, and Codex-style agents make execution cheaper and faster.
L2
Carries context.
OpenClaw publicly emphasizes local agents, persistent memory, full system access, skills, plugins, and integrations.
L3
Improves procedures.
Hermes Agent publicly positions itself around a self-improving learning loop, skill creation, recall, and user modeling.
L4
Grows with the person.
Elephant Agent's product position: Mother understands the person, shapes Paths, and keeps judgment, evidence, questions, and learning close to the person.

Personal Model

  • Identity — who you are, your values, boundaries, decision style, and stable preferences.
  • World — the people, projects, tools, places, and relationships around you.
  • Pulse — what is alive right now: focus, pressure, constraints, energy, and priorities.
  • Journey — what your path has taught: lessons, failures, recovery patterns, and long-running growth.

The four Personal Model lenses: Identity, World, Pulse, and Journey

The goal is not to remember everything. The goal is to understand what matters, show why it matters, let you change it, and turn that understanding into better Paths over time.

macOS Desktop App

The macOS app is the recommended product surface. Chat / Wake is where you talk to Mother; Paths are where long-running life and work arcs become visible; the rest of the app keeps the Personal Model, Herd, skills, messaging, calendar, usage, and advanced runtime settings inspectable instead of hidden behind a chat box.

Elephant Agent macOS Home screen with the Personal Model map, current context, and next useful question
Home — start from what Mother understands before shaping the next Path.

Elephant Agent onboarding language screen
Preferences
Choose language, boundaries, model posture, and curiosity effort.
Elephant Agent Wake chat surface
Chat / Wake
Return to Mother and the same path, not a blank prompt.
Elephant Agent Personal Model map
Personal Model
Inspect the understanding that shapes future Paths.
Elephant Agent model provider settings
Providers
Use local or hosted models as advanced posture, not the product center.
Elephant Agent skills screen
Skills
See which skills help Mother and the Herd move a Path.
Elephant Agent tools screen
Tools
Keep browser, filesystem, MCP, and operator actions explicit.
Elephant Agent herd screen
Herd
Coordinate Mother and baby elephants under one understanding.
Elephant Agent messaging integrations
Messaging
Connect WeChat, Feishu, Discord, DingDing, or WeCom when you want it.
Elephant Agent calendar and reminders
Calendar
Keep routines, reminders, and long-running Paths visible.
Elephant Agent token usage screen
Usage
Inspect local token flow and runtime events instead of treating cost as a black box.

Quickstart

Elephant Agent has two supported product shapes.

1. macOS desktop app (recommended)

Use this path for the full local desktop workspace: Chat / Wake, Paths, Personal Model, Herd, skills, messaging, calendar, usage, and settings in one native app.

  1. Download the latest macOS build from GitHub Releases.
  2. Open Elephant Agent.app.
  3. Create your first elephant, choose a provider, and set curiosity effort.
  4. Return through Chat / Wake when you want Mother to continue the same path.

2. CLI + Dashboard (Linux / Cloud)

Use this path for Linux, cloud machines, SSH workflows, and terminal-first operators. The CLI is the daily terminal surface; the Dashboard is the visual inspection surface for Personal Model, evidence, jobs, skills, and runtime state.

Elephant Agent CLI wake session
CLI
Elephant Agent Dashboard Personal Model map
Dashboard

Install:

curl -fsSL https://elephant.agentic-in.ai/install.sh | bash

First run:

elephant init        # choose identity, provider, and curiosity effort
elephant status      # check provider and local runtime readiness
elephant wake        # enter the chat TUI
elephant dashboard   # open Personal Model, questions, evidence, and runtime state

For remote or cloud use, elephant dashboard --no-open prints the local URL so you can attach through your preferred tunnel or browser setup.

Read More

README and the homepage stay product-first. The deeper system story lives here:

Contributors

Agentic Intelligence Lab

Agentic Intelligence Lab

Project details


Release history Release notifications | RSS feed

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

elephant_agent-1.0.0.dev20260529230902.tar.gz (1.7 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

File details

Details for the file elephant_agent-1.0.0.dev20260529230902.tar.gz.

File metadata

File hashes

Hashes for elephant_agent-1.0.0.dev20260529230902.tar.gz
Algorithm Hash digest
SHA256 10d3bfc2f7240d35dceef764d2371a9f70c661a94ff72ccd3c0d30c63afa220c
MD5 93dabe373ef0e2853d5c79d6e8f26720
BLAKE2b-256 fbcedfc6530864929e76e3e1b4c6e988440319609cec47d2875bea7e635d57f5

See more details on using hashes here.

File details

Details for the file elephant_agent-1.0.0.dev20260529230902-py3-none-any.whl.

File metadata

File hashes

Hashes for elephant_agent-1.0.0.dev20260529230902-py3-none-any.whl
Algorithm Hash digest
SHA256 65835b3099e18bb6ae5e44278189b671d9190adb9f0daf06dd038ad048644ed8
MD5 4221cd928d71605f315e778944e031d6
BLAKE2b-256 529c977ed103198759602e39729d0d07b3346b9e9d8add36400d6305758b10c9

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page