Deterministic batch tools so LLM agents stop guessing dates and math.
Deterministic batch tools so LLM agents stop guessing dates and math. That is what the gnomon mcp server brings to an AI assistant: the same capability, reachable through the Model Context Protocol rather than a separate app or dashboard.
A small MCP server for the boring-but-essential utilities every model needs: dates, calendars, arithmetic, unit conversion. Use it so your assistant stops "next-token guessing" math and date math.
Because this one is hosted, setup is mostly authentication — you point your client at the endpoint and approve access. Nothing runs on your machine, so there is no runtime to keep patched.
The server publishes 4 tools. What each one is for:
Calendar — Units for diff/until/since: seconds, minutes, hours, days, weeksCalculator — The Calculator tool exposed by this serverCursor — The Cursor tool exposed by this serverContinue — The Continue tool exposed by this serverThis sits in the AI and media services group, where several servers overlap in what they claim to do but differ sharply once you actually set them up. Gnomon's toolset — Calendar, Calculator, Cursor and 1 more — is a fair guide to whether it matches your workflow. It is maintained by lihtness; worth a glance at recent repository activity before you build anything load-bearing on it.
We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.
| Tool | What it does |
|---|---|
| Calendar | Units for diff/until/since: seconds, minutes, hours, days, weeks. |
| Calculator | The Calculator tool exposed by this server. |
| Cursor | The Cursor tool exposed by this server. |
| Continue | The Continue tool exposed by this server. |
{
"mcpServers": {
"gnomon": {
"command": "uvx",
"args": ["gnomon-mcp"]
}
}
}Add to claude_desktop_config.json, then restart Claude Desktop.
Build a programmable telecommunications stack for connecting telephony services with the Internet via a cloud-based utility.
Search built for AI, not humans — semantic web search that returns model-ready content, plus code context.
Answers, not links — delegate questions to Perplexity's search-grounded models and get cited responses back.
Give your assistant a voice — text-to-speech, voice cloning and audio tools from the ElevenLabs API.
Give your assistant a real code sandbox — isolated cloud VMs for actually running the code it writes.
The ML hub in your context window — search models, datasets, papers and run Spaces from the official server.