OmniArchive-MCP
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@OmniArchive-MCParchive https://example.com/article"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
OmniArchive-MCP
A local daemon that lets AI agents archive web pages to the Wayback Machine in the background, so they don't block on Internet Archive's slow/rate-limited API.
Works with any MCP-compatible client (Kiro, Cursor, Claude Desktop, etc).
Why?
When AI agents do deep research, they read a lot of web pages. Those pages disappear all the time (link rot). Archiving them to the Internet Archive is the obvious fix — but IA's API is slow and rate-limited. If your agent calls it synchronously, it blocks for seconds or gets 429'd.
This tool solves that. The agent calls archive_url, gets a task ID back in milliseconds, and moves on. A background worker handles the actual archiving with proper retry logic.
What it does
Exposes
archive_urlandget_archive_statusas MCP toolsQueues requests in local SQLite (survives restarts, no Redis needed)
Background worker retries with exponential backoff on 429/5xx
Deduplicates — same URL within 24h won't be re-archived
Binds to localhost only, no telemetry, nothing phones home
Architecture
AI Client (Kiro/Cursor)
│ stdio (MCP JSON-RPC)
▼
┌─────────────────────┐
│ MCP Server │ ← Separate process
│ (archive_url, │
│ get_archive_status)│
└────────┬────────────┘
│ httpx (localhost:19210)
┌────────▼────────────────────────┐
│ FastAPI Service + Worker │ ← Main process
│ ┌─────────┐ ┌──────────────┐ │
│ │ Routes │ │ Background │ │
│ │ /api/* │ │ Worker │ │
│ └────┬─────┘ └──────┬───────┘ │
│ │ │ │
│ ┌────▼───────────────▼───────┐ │
│ │ SQLite (WAL mode) │ │
│ └────────────────────────────┘ │
└──────────────────────────────────┘
│
│ waybackpy
▼
Internet Archive SPN2Two processes: the MCP server talks stdio with your AI client, and forwards requests over HTTP to the FastAPI service. The FastAPI service manages the queue and runs the background worker.
Getting started
You need Python 3.10+.
git clone https://github.com/your-org/omniarchive-mcp.git
cd omniarchive-mcp
pip install -e ".[dev]"Start the backend service:
python -m omniarchive_mcp.mainRuns on 127.0.0.1:19210 by default.
Run the tests:
pytest test/ -v # 84 tests, takes ~12sMCP tools
archive_url
Queue a URL for archiving.
Param | Type | Required | |
url | string | yes | Must be http or https |
Returns: { "task_id": "...", "status": "pending", "url": "..." }
get_archive_status
Check on a task. Pass either task_id or url (at least one).
Param | Type | Required | |
task_id | string | no | The ID from archive_url |
url | string | no | Looks up the most recent task for this URL |
Returns the task status, archive URL (if done), error info (if failed).
Hooking it up to your editor
You need both: the backend service running, AND the MCP server configured in your client.
Kiro — .kiro/settings/mcp.json:
{
"mcpServers": {
"omniarchive": {
"command": "python",
"args": ["-m", "omniarchive_mcp.mcp_server.main"]
}
}
}Cursor — .cursor/mcp.json:
{
"mcpServers": {
"omniarchive": {
"command": "python",
"args": ["-m", "omniarchive_mcp.mcp_server.main"]
}
}
}Claude Desktop — claude_desktop_config.json:
{
"mcpServers": {
"omniarchive": {
"command": "python",
"args": ["-m", "omniarchive_mcp.mcp_server.main"]
}
}
}Don't forget to start the backend first: python -m omniarchive_mcp.main
Configuration
Everything's controlled via env vars (prefix OMNIARCHIVE_):
Variable | Default | What it does |
|
| Bind address |
|
| Port |
|
| Where the SQLite file lives |
|
| How many times to retry a failed archive |
|
| Base retry delay in seconds (doubles each time) |
|
| How many tasks to process per poll cycle |
|
| Seconds between queue polls |
| — | Your IA S3 key (optional, for higher rate limits) |
| — | Your IA S3 secret |
|
| Log verbosity |
|
| Log file location |
How it works under the hood
Agent calls
archive_url→ MCP server validates the URL → POSTs to FastAPIFastAPI checks if this URL was already submitted in the last 24h (dedup) → writes to SQLite → returns task ID
Worker picks up pending tasks every 5s → calls Internet Archive via waybackpy
Success? Stores the archive URL. Got 429/5xx? Backs off and retries. Got 403? Gives up.
License
MIT. See LICENSE.
Contributing
See CONTRIBUTING.md.
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