afya-mcp
Afya MCP server exists for a simple reason — assistants are far more useful when they can act on Afya directly instead of describing what you should do. afya-mcp.
MCP server for Kenya health system navigation — NHIF coverage, facility finder, maternal health, CHW support, and essential medicines. 6 tools.
Once Afya is connected, these are the calls the assistant has available:
bima-mcp — parametric insurance evaluationkilimo-mcp — agricultural advisoryafya-mcp — health surveillance activationcounty-mcp — county office alertDatasets — ** huggingface.co/gmahia · Docs hub: nairobi-stackThe server ships on PyPI as afya-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. Afya's toolset — bima-mcp, kilimo-mcp, afya-mcp and 2 more — 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We check each listing at SyncDev against the project's documentation before it goes live — if something here drifts out of date, it is a bug worth reporting.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 |
|---|---|
| bima-mcp | parametric insurance evaluation |
| kilimo-mcp | agricultural advisory |
| afya-mcp | health surveillance activation |
| county-mcp | county office alert |
| Datasets | ** [huggingface.co/gmahia](https://huggingface.co/gmahia) · **Docs hub:** [nairobi-stack](https://github.com/gabrielmahia/nairobi-stack) |
{
"mcpServers": {
"afya": {
"command": "uvx",
"args": ["afya-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.