nyumba-mcp
Connect Nyumba to Claude, Cursor or any other MCP client and it stops being a tab you switch to. nyumba-mcp. The nyumba mcp server is what makes that connection.
MCP server for Kenya housing — rental market, tenant rights, building permits, affordable housing programs, and housing finance. 5 tools.
The toolset is worth reading before you wire it up, because it tells you what the integration is really for:
Datasets — ** huggingface.co/gmahia · Docs hub: nairobi-stackThe server ships on PyPI as nyumba-mcp, so your MCP client can launch it on demand — there is no separate build step. Add the server block to your client's configuration, restart it, and the tools register themselves.
Plenty of AI and media services servers cover similar ground. The differences that matter in practice are scope of access and how much setup stands between you and a working tool call. Nyumba's toolset — Datasets — is a fair guide to whether it matches your workflow. It is maintained by gabrielmahia; 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We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.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 |
|---|---|
| Datasets | ** [huggingface.co/gmahia](https://huggingface.co/gmahia) · **Docs hub:** [nairobi-stack](https://github.com/gabrielmahia/nairobi-stack) |
{
"mcpServers": {
"nyumba": {
"command": "uvx",
"args": ["nyumba-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.