Local AI inference for East Africa — Ollama, open weights, degraded-mode fallbacks. 6 tools. Thesis
Project description
offline-mcp
Local AI inference infrastructure — Ollama wrapper, open weights directory, degraded-mode guide for East Africa.
Why: Never assume OpenAI survives, Anthropic stays accessible, or export controls disappear. This matters more in Africa than anywhere else.
1st world equivalent: Ollama, LLaMA, Mistral local deployment
Install
pip install offline-mcp
Tools (6)
| Tool | Description |
|---|---|
check_ollama_status |
Check if Ollama is running locally and list available models |
run_local_inference |
Run a prompt through a local Ollama model |
list_recommended_models |
Best open-weight models for East Africa use cases |
degraded_mode_guide |
4-level degraded mode architecture for offline operation |
open_weights_directory |
Directory of open-weight models with Africa language support |
local_deployment_guide |
Deployment guide for laptop, server, Raspberry Pi, Android |
Context
Runs on a 50W solar panel + Raspberry Pi 4. Viable for rural Kenya clinics, schools, and community offices.
License
MIT © Gabriel Mahia | contact@aikungfu.dev
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