ContextOS — Claude Code MCP server: what it does, how to install
A local MCP server that keeps evidence, command logs and plans out of the main chat and hands the agent only what the next step needs.
claude mcp add --env CONTEXTOS_PROJECT_ROOT=<CONTEXTOS_PROJECT_ROOT> --transport stdio contextos-powered-exoskeleton-for-ai-coding -- docker run -i --rm -e CONTEXTOS_PROJECT_ROOT ghcr.io/yubinbin32-ops/contextos:3.0.3What ContextOS — Powered Exoskeleton for AI Coding does
ContextOS sits between your coding agent and the repository. File reads, command output, plans, architecture notes and verification reports stay on disk; the main conversation receives just the fragments required for the current decision. Long sessions stop filling up with logs and repeated reads of the same files.
The toolset covers several jobs. ask reads exact paths, line ranges and AST symbols. command runs something once and keeps stdout, stderr and exit status for later lookup. pipeline groups steps. micro delegates small retrieval or edits to a configured API model, and agent runs implementation in an isolated workspace through a CLI adapter. Architecture is described with Block and Chain, while change and integrate move edits through the server. Plans and receipts survive a restart, so a new session can pick up where the last one stopped.
Everything runs in Docker, so the image ghcr.io/yubinbin32-ops/contextos:3.0.3 has to be reachable and CONTEXTOS_PROJECT_ROOT must point at your project root. Skip that variable and the server has no idea which repository to serve. The micro and agent modes need their own API keys and CLI adapters configured beforehand.
What it helps with
- read one function instead of loading a whole file
- keep failed test output and come back to it later
- batch independent checks into a single call
- route an edit through verification and get a receipt
- restore the plan in a fresh session
Example prompts for the agent
- Use
askto read only theparseConfigfunction fromsrc/config.ts - Run the tests with
commandand show me just the failing lines - Group reads of
package.jsonandtsconfig.jsoninto onepipelinecall
How to install ContextOS — Powered Exoskeleton for AI Coding
Platform CLI
claude mcp add --env CONTEXTOS_PROJECT_ROOT=<CONTEXTOS_PROJECT_ROOT> --transport stdio contextos-powered-exoskeleton-for-ai-coding -- docker run -i --rm -e CONTEXTOS_PROJECT_ROOT ghcr.io/yubinbin32-ops/contextos:3.0.3Replace <…> with your own values
Platform CLI
codex mcp add contextos-powered-exoskeleton-for-ai-coding --env CONTEXTOS_PROJECT_ROOT=<CONTEXTOS_PROJECT_ROOT> -- docker run -i --rm -e CONTEXTOS_PROJECT_ROOT ghcr.io/yubinbin32-ops/contextos:3.0.3Replace <…> with your own values
Config file
{
"mcpServers": {
"contextos-powered-exoskeleton-for-ai-coding": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"CONTEXTOS_PROJECT_ROOT",
"ghcr.io/yubinbin32-ops/contextos:3.0.3"
],
"env": {
"CONTEXTOS_PROJECT_ROOT": "<CONTEXTOS_PROJECT_ROOT>"
}
}
}
}Replace <…> with your own values
Config file
{
"servers": {
"contextos-powered-exoskeleton-for-ai-coding": {
"type": "stdio",
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"-e",
"CONTEXTOS_PROJECT_ROOT",
"ghcr.io/yubinbin32-ops/contextos:3.0.3"
],
"env": {
"CONTEXTOS_PROJECT_ROOT": "<CONTEXTOS_PROJECT_ROOT>"
}
}
}
}Replace <…> with your own values
Platform CLI
gemini mcp add -e CONTEXTOS_PROJECT_ROOT=<CONTEXTOS_PROJECT_ROOT> contextos-powered-exoskeleton-for-ai-coding docker run -i --rm -e CONTEXTOS_PROJECT_ROOT ghcr.io/yubinbin32-ops/contextos:3.0.3Replace <…> with your own values
Step by step, with commands for each platform: How to add an MCP server to Claude Code, Codex, Cursor, VS Code, Gemini CLI and more
Questions about ContextOS — Powered Exoskeleton for AI Coding
How do I install ContextOS in Claude Code?
Run `claude mcp add --env CONTEXTOS_PROJECT_ROOT=<CONTEXTOS_PROJECT_ROOT> --transport stdio contextos-powered-exoskeleton-for-ai-coding -- docker run -i --rm -e CONTEXTOS_PROJECT_ROOT ghcr.io/yubinbin32-ops/contextos:3.0.3`. Replace the placeholder with your project root path.
What does ContextOS do?
It stores code evidence, command logs, plans and verification receipts outside the main conversation and returns only the pieces the agent needs. That cuts token use and context occupancy.
What do I need before running it?
Docker with access to the ghcr.io/yubinbin32-ops/contextos:3.0.3 image, plus CONTEXTOS_PROJECT_ROOT set to your project path. The micro and agent modes need a configured API model and CLI adapter.
