World Monitor
Real-time global intelligence on conflict, markets, energy, trade, shipping and cyber. 102 tools.
Description from the maker (original English)
Give your agent a body: observe and control simulated robots (LIBERO, RoboDojo) over MCP.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
Passed 2/2 checks · Runs on your computer
First: which AI do you use?
Pick your app and the steps appear below.
Works with Claude, with some setup first
Install Python (uv) on your computer first (one time) · Only the Claude desktop app (Windows or Mac), not the web or phone
One time only; it works for every server that needs Python (uv)
SettingsDeveloperEdit Config
{
"mcpServers": {
"embodify": {
"command": "uvx",
"args": [
"embodify-mcp"
]
}
}
}Use Embodify and tell me what you can do for me, then show me one thing✓ If Claude says it is using Embodify or shows a Embodify tool in the answer, you are connected
Menu names checked against Anthropic’s help page on Nov 11, 2026 · your screen may differ slightly by app version
ChatGPT cannot connect Embodify yet
Embodify runs on your computer, but ChatGPT can only connect servers that run on the web
A · Use an app that can connect Embodify
B · Others in Other that work with ChatGPT
Picked from the most used in the same category, only ones that connect by address with no key
Works with Claude Code, with some setup first
Install Python (uv) on your computer first (one time)
One time only; it works for every server that needs Python (uv)
Mac: press Command+Space and type Terminal · Windows: open PowerShell
claude mcp add embodify -- uvx embodify-mcpYou should see Embodify listed as connected
Use Embodify and tell me what you can do for me, then show me one thing✓ If Claude Code says it is using Embodify or shows a Embodify tool in the answer, you are connected
Menu names checked against Anthropic’s help page on Nov 11, 2026 · your screen may differ slightly by app version
Works with Cursor, with some setup first
Install Python (uv) on your computer first (one time)
One time only; it works for every server that needs Python (uv)
Use Embodify and tell me what you can do for me, then show me one thing✓ If Cursor says it is using Embodify or shows a Embodify tool in the answer, you are connected
Menu names checked against Cursor’s help page on Nov 11, 2026 · your screen may differ slightly by app version
Works with VS Code, with some setup first
Install Python (uv) on your computer first (one time)
One time only; it works for every server that needs Python (uv)
Use Embodify and tell me what you can do for me, then show me one thing✓ If VS Code says it is using Embodify or shows a Embodify tool in the answer, you are connected
Menu names checked against VS Code’s help page on Nov 11, 2026 · your screen may differ slightly by app version
Claude Code
claude mcp add embodify -- uvx embodify-mcpClaude Desktop (claude_desktop_config.json)
{
"mcpServers": {
"embodify": {
"command": "uvx",
"args": [
"embodify-mcp"
]
}
}
}Cursor (~/.cursor/mcp.json)
{
"mcpServers": {
"embodify": {
"command": "uvx",
"args": [
"embodify-mcp"
]
}
}
}VS Code (mcp.json)
{
"servers": {
"embodify": {
"type": "stdio",
"command": "uvx",
"args": [
"embodify-mcp"
]
}
}
}These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Based on how this server connects and on each app’s own docs, checked Nov 10, 2026.
Run on your computer in
ClaudeGooseLM StudioMsty StudioCherry StudioCursorVS Code + GitHub CopilotVisual StudioWindsurf (Devin Desktop)ZedKiroClineContinueJetBrains AI AssistantClaude CodeCodex CLIGemini CLIOpenCodenodecodeWarpLibreChatRaycast
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 11, 2026
The registry name was verified with the GitHub account YidaYang, which owns the repo
Code last changed 40 days ago
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
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Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 2 of 2 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed 40 days ago, and the latest version (0.1.0a2) reached the registry 40 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.
In the same category: World Monitor, Claude Flow, Tldraw
Servers in the same category from other makers, sorted by stars.
Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Real-time global intelligence on conflict, markets, energy, trade, shipping and cyber. 102 tools.
AI orchestration with hive-mind swarms, neural networks, and 87 MCP tools for enterprise dev.
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
Embodify
Give your agent a body.
Your best embodied agent is your favorite agent.
Embodify lets the agent you use every day — Claude Code, Codex or any other MCP-capable agent — see and control robots directly, and keeps everything else that makes it yours. Bring in frontier models with embodied manipulation skills, such as GPT-6 Astra and Claude Opus 5.5, and let your AI companion step into the physical world.
中文 · One-line setup · Backends · For research · Skills · Roadmap
First release (0.1.0a1). Supports LIBERO and RoboDojo today; support for
RoboTwin and the LeRobot SO-101 arm is coming soon.
Most embodied agents are built from scratch: a dedicated harness wraps a model, hands it a fixed set of robot actions, and nothing else. The agent you use every day already has what those harnesses lack:
Embodify keeps all of that and adds a body. Install the plugin and your agent gets robot observation and control tools over MCP — a protocol it already uses for everything else — plus skills that teach it how to operate robots and how to achieve recursive self-improvement (RSI) from its own experience.
A general agent with a body is stronger than a harness that can only move a robot:
Embodify is an agent plugin with two parts, and installing the plugin gives your agent both:
| Part | What it gives your agent |
|---|---|
MCP server (embodify-mcp, registered as embodify) | Tools to list tasks, start an episode, observe cameras and robot state, move end effectors, open and close grippers, and coordinate two arms. |
| Skills | Know-how: running a careful observe–act loop, keeping a profile of the robot body and cameras, and learning from past episodes. More perception skills are coming soon. |
flowchart LR
A["Your agent Claude Code · Codex · …"] -- "MCP (stdio)" --> B["embodify-mcp episodes · budgets · logs"] K["Embodify skills"] -. "loaded by" .-> A B --> I["Backend interface"] I --> L["LIBERO"] I --> R["RoboDojo"] I --> T["RoboTwin (WIP)"] I --> H["SO-101 and other real robots (WIP)"] I -. "SSH / TCP" .-> G["Remote server"]
The MCP server is the front end. Each simulator, benchmark or robot is a backend behind one small interface, so adding a new one does not change what the agent sees. Highlights:
reset_task reconnects.| Backend | Robot | Status |
|---|---|---|
fake, fake-two-arm | Kinematic diagnostic, one or two arms | ✅ Included, no simulator needed |
libero | Franka Panda, 130 tasks in 5 suites | ✅ Included |
robodojo | Dual ARX X5, all 54 simulation tasks | ✅ Included |
| RoboTwin | Dual-arm manipulation benchmark | 🚧 Coming soon |
| LeRobot SO-101 | Real robot: 5-DoF arm with gripper | 🚧 Coming soon |
remote | Any backend above, on another machine | ✅ SSH or trusted TCP |
Coming soon: robot arms such as xArm, mobile manipulators, humanoids and dexterous hands. If there is a simulator or robot you would like us to support, open a GitHub issue with details about it. We welcome contributions of new backends.
Embodify doubles as a testbed for the embodied manipulation abilities of language models and agent frameworks. Run GPT, Claude, Gemini, Qwen and other models, through Claude Code, Codex or your own agent framework, on the same simulated benchmarks with the same tools, and compare them directly.
--lock-task fixes the scene.Typical studies include zero-shot robot manipulation by frontier models, comparisons of agent frameworks on the same model, the effect of skills and memory, and recursive self-improvement across episodes. See citation for how to cite Embodify and what to report.
Paste this into Claude Code, Codex or any other agent you use:
Install Embodify (https://github.com/YidaYang/embodify) for yourself, then set up a LIBERO environment or connect to my existing simulator.
That's it. Your agent installs the Embodify plugin, sets up the simulator and tells you when to restart the session. (Agents: follow the agent setup guide.)
Embodify starts its MCP server with uv, straight from PyPI. If you do not have uv yet, install it with python -m pip install uv or the official installer.
claude plugin marketplace add YidaYang/embodify
claude plugin install embodify@embodify
codex plugin marketplace add YidaYang/embodify
codex plugin add embodify@embodify
The plugin brings both the MCP server, registered as embodify, and the skills. The server starts on the Fake backend, so you can try the tools right away; connect a real simulator next. It reads its settings from ~/.embodify/config.json (see backend setup). To check the package on its own, without an agent:
uvx --from embodify-mcp embodify-mcp-smoke # end-to-end check: no simulator, GPU or model needed
SKILL.md folders), copy or link the folders in plugin/skills/ into its skills directory.Restart the session, then ask your agent something like *"Reset the task, describe what the cameras show, then raise the gripper 5 cm."*
Let your agent do this step. Paste:
Connect Embodify to a real simulator for me: set up LIBERO on this machine, or connect to my existing simulator. Follow https://github.com/YidaYang/embodify/blob/main/docs/agent-setup.md.
Your agent installs the simulator or connects to yours over SSH, writes the server settings to ~/.embodify/config.json and asks you to restart the session. To do it by hand, see backend setup.
Add "monitor-port": 8765 to ~/.embodify/config.json and open http://127.0.0.1:8765 to watch the robot work live, with every camera view, the robot state and each tool call your agent makes, or to replay any past episode frame by frame. To browse saved runs without a running server:
uvx --from embodify-mcp embodify-mcp-monitor # reads ~/.embodify/runs
The monitor listens on localhost only.
| Tool | Purpose |
|---|---|
get_session_info | Current run, task, step budget and robot state; no images |
list_tasks | Browse the backend's task catalogue |
reset_task | Start an episode and return the first camera images |
observe | Camera images and robot state, without moving |
move_relative | Move one end effector by a translation and optional rotation |
set_gripper | Open or close a gripper |
control_arms | Move several arms together with common progress (two-arm backends) |
stop_episode | End the episode and write its record |
Translations are in meters, rotations in radians, quaternions in xyzw order. Frames and stop reasons are defined in the action contract.
The plugin contains these skills:
| Skill | Status | What it does |
|---|---|---|
| embodied-control | v0 | The observe–act loop: small moves, reading stop reasons, verifying grasps, releasing in a separate call |
| robot-profile | v0 | Keep a profile of the robot: arms, cameras, frames, calibration and measured behavior |
| task-experience | v0 | Write a lesson after every episode, read relevant lessons before the next, promote repeated lessons to rules |
| object-segmentation | Coming soon | Open-vocabulary segmentation of camera images |
| depth-ranging | Coming soon | Pixel to 3D position from depth and calibration |
Skills are grouped into three families that will keep growing: