The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.
Termcp
让 AI 进入你的诸多终端 —— Let AI into your terminals.
Install
git clone https://github.com/open-mcp-ai/TermcpInstall command taken from the project's README or registry entry. Always review code before running it.
README excerpt
Read full README on GitHub →⚡ Termcp
English | 中文
Let AI into your terminals
Lightweight AI-native secure terminal: visual multi-surface, MCP + SKILLS + API
- Human and agent, equal — both write to the same terminal, and you see every screenful as it happens; take over, switch, collaborate.
- Fine-grained session control — file management, port forwarding, multi-terminal multiplexing, terminal read/write access.
- Dependency-free install — a single ~10 MB file, multi-platform, with npx integration.
Install
1 · One command per agent
| Agent | Command |
|---|---|
| Claude Code | claude mcp add termcp -- npx -y @open-mcp-ai/termcp daemon stdio |
| Codex | codex mcp add termcp -- npx -y @open-mcp-ai/termcp daemon stdio |
| Gemini CLI | gemini mcp add termcp npx -- -y @open-mcp-ai/termcp daemon stdio |
| Crush | add to ~/.config/crush/crushrc: mcp add termcp --command npx --args -y --args @open-mcp-ai/termcp --args daemon --args stdio |
2 · Or this config file
{
"mcpServers": {
"termcp": {
"command": "npx",
"args": ["-y", "@open-mcp-ai/termcp", "daemon", "stdio"]
}
}
}
That command is the whole server: it starts the background instance on first use, relays MCP over stdin/stdout, and the instance exits on its own once idle. Ready to go as-is.
Other install methods — npm / Go / Docker / prebuilt binary
| Command | |
|---|---|
| npm | npm i -g @open-mcp-ai/termcp — installs a termcp command; with it, drop npx -y @open-mcp-ai/termcp from every snippet above and use termcp. Wrapper: open-mcp-ai/Termcp-npm. |
| Go | go install github.com/open-mcp-ai/termcp@latest — GOPROXY=https://goproxy.cn,direct in mainland China; also usable as a module (go get github.com/open-mcp-ai/termcp). |
| Docker | docker run -d --name termcp -p 18765:18765 -v termcp-data:/home/termcp -e TERMCP_AUTH_TOKEN=change-me-to-a-long-random-secret ghcr.io/open-mcp-ai/termcp:latest termcp --no-internal --host 0.0.0.0 --port 18765 |
| Binary | Prebuilt releases — linux / darwin / windows on amd64 / arm64, one static file each. |
The npm wrapper downloads the matching prebuilt binary (override with TERMCP_VERSION, TERMCP_MIRROR,
TERMCP_BIN, TERMCP_SKIP_DOWNLOAD). Flags: docs/cli.md. Docker recipes, Compose and a
token-free loopback setup: docs/deploy.md.
HTTP transport, when an instance is already answering somewhere (npx -y @open-mcp-ai/termcp):
{
"mcpServers": {
"termcp": {
"type": "http",
"url": "http://localhost:18765/stream"
}
}
}
Reachable from a client in Docker as http://host.docker.internal:18765/stream (macOS/Windows) or the host's
LAN IP; from another container on the same network as http://termcp:18765/stream. Legacy SSE uses
http://localhost:18765/sse — only /sse, JSON-RPC goes to /message by itself. With
--auth-token, add a bearer header: "headers": {"Authorization": "Bearer <token>"}.
Preview
Open http://127.0.0.1:18765 — every agent session appears here.
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