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Deploy files, sites, and Dockerfile apps to live URLs + private drives for agent memory.
About
Deploy files, sites, and Dockerfile apps to live URLs + private drives for agent memory.
Remote endpoints: streamable-http: https://dataecho.ai/mcp
Security Report
This MCP server is a lightweight stdio bridge that forwards requests to a remote DataEcho platform endpoint. Authentication is optional and properly handled via environment variables or a credentials file with appropriate permissions. The code is clean with minimal dependencies and no injection vulnerabilities. Minor concerns include broad error handling and lack of explicit input validation on JSON-RPC messages, but these are low-severity for a bridge implementation.
4 files analyzed · 4 issues found
Security scores are indicators to help you make informed decisions, not guarantees. Always review permissions before connecting any MCP server.
Permissions Required
This plugin requests these system permissions. Most are normal for its category.
How to Install & Connect
Available as Local & Remote
This plugin can run on your machine or connect to a hosted endpoint. during install.
Documentation
View on GitHubFrom the project's GitHub README.
DataEcho — agent skills
Two Agent Skills for the DataEcho platform:
| Skill | What it does |
|---|---|
dataecho | Deploy anything to a live URL in seconds — a single file, a static site, or a full server-side app (any stack, via Dockerfile). Anonymous publish with a claim flow, incremental deploys, private Drives with scoped share tokens. |
dataecho-memory | Persistent memory for agents — durable across sessions, machines, sandboxes, and platforms. A ~1 KB index + one fact per file on a private versioned drive; atomic concurrent-safe writes, full history/undo, one-command handoff to another agent. |
Both are plain SKILL.md + self-contained scripts (bash + python3 stdlib, zero dependencies), so they work in any agent that supports the open Agent Skills format — Claude Code, OpenAI Codex, Gemini CLI, Cursor, GitHub Copilot / VS Code, Goose, opencode, Qwen Code, Amp, Cline, Kilo, Hermes, OpenClaw, and more.
Install
# both skills, any supported agent (global; drop -g for project-local)
npx skills add mohocp/dataecho -g
# just one of them
npx skills add mohocp/dataecho --skill dataecho -g
npx skills add mohocp/dataecho --skill dataecho-memory -g
Claude Code plugin route:
/plugin marketplace add mohocp/dataecho
/plugin install dataecho@dataecho
No npm? Install the deploy helper scripts directly:
curl -fsSL https://dataecho.ai/install.sh | bash # macOS / Linux
irm https://dataecho.ai/install.ps1 | iex # Windows PowerShell
What's inside
skills/dataecho/SKILL.md— publish handshake, Dockerfile app contract, claim contract, Drives, API-key flowscripts/publish.sh— 3-call publish (create → upload → finalize), incremental deploys, anonymous-claim handlingscripts/drive.sh— drive CRUD, import/export, scoped share tokens, ETag-safe writesscripts/publish.ps1— Windows PowerShell publisher
skills/dataecho-memory/SKILL.md— the memory discipline (recall-first, update-don't-duplicate, forget-what's-wrong)scripts/memory.sh—recall / remember / forget / reindex / history / restore / handoff; every mutation commits fact + index in one atomic CAS batch
Security & privacy
- Credentials: the API key (obtained via an email one-time code) is stored at
~/.artifact/credentials(chmod 600), or passed via$ARTIFACT_API_KEY. Nothing else is written outside the project. Revoke keys any time from the dashboard. - Network: scripts talk only to
https://dataecho.ai(override:$ARTIFACT_BASE_URL). No telemetry, no third-party calls. - Anonymous publishes need no account; they expire in 24 h unless claimed. Claim tokens are saved locally under
~/.artifact/claims/. - Memory is private storage, scoped to your account; share access is via revocable, prefix/TTL-scoped drive tokens. Don't store secrets in memories — it's not a vault.
- The
curl | bashinstaller above is a convenience mirror ofinstall.sh; the canonical scripts are versioned in this repo.
Links
Docs: https://dataecho.ai/docs · Agent context: https://dataecho.ai/llms.txt · llms-full.txt · OpenAPI: https://dataecho.ai/openapi.json · Discovery: https://dataecho.ai/.well-known/agent.json
License
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