MCP server enabling offline-first agent operation over intermittent connectivity
An MCP server that enables offline-first agent operation over intermittent connectivity. It provides Model Context Protocol support and is oriented around Python-based installation, intended to work with any MCP client.
š ļø Key Features
MCP server for offline-first operation over intermittent connectivity
Compatible with claude-sonnet-5 (released 2026-06-30) ā Anthropic's most agentic
Sonnet yet. Runs multi-step tool chains end-to-end without stopping short.
Install: pip install offline-mcp Ā· Use with any MCP client.
Local AI inference infrastructure ā 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
Why This Exists: Data Sovereignty
"If you take the deal, you're going to be exploited. If you don't take it, you're going to die."
ā Frank Ssekamwa, Ugandan digital rights expert
Across the Global South, AI and health data from communities is being extracted, processed abroad,
and used to build models whose value flows away from the communities that generated it.
offline-mcp is the sovereignty floor of the East Africa coordination stack.
When this runs on a Raspberry Pi 4 with a 50W solar panel and a 256GB SD card:
Health data stays in the clinic. Health guidance comes from local models.
Land records stay in the land office. Queries don't touch foreign servers.
Civic data stays in the county. AI assistance runs without internet.
No API key. No cloud dependency. No data leaving the community.
The models available via offline-mcp (Llama 3.2, Qwen 2.5) run entirely on device.
Community data used to generate AI outputs creates no dataset sent back to model providers.
This is not a privacy feature. It is the architectural foundation of digital independence.
Research Foundation
This server implements patterns validated by peer-reviewed research on offline-first
AI for bandwidth-constrained environments:
arXiv:2603.03339 (2026) ā Offline-First LLM Architecture for Adaptive Learning
in Low-Connectivity Environments ā confirms that meaningful AI support is achievable
with hardware-aware model selection when designed for infrastructure-limited deployment.
Key finding: offline-first is a complementary paradigm, not a compromise.
Design principles applied:
Local-first: all core operations execute without internet connectivity
Graceful degradation: reduced functionality beats no functionality
JSONL queue: events accumulated offline sync when connectivity returns
Hardware-aware: tool selection adapts to available compute
East Africa context:
Kenya, Tanzania, Uganda ā rural areas with intermittent connectivity represent
the primary deployment target. This server is not designed for ideal conditions.
It is designed for real ones.
Install
bash
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.
This MCP server is part of the Kenya coordination infrastructure.
Connect it to africa-coord-bus ā
the coordination event bus that routes signals between domains automatically.
MIT licensed. Feedback via GitHub Issues only ā pull requests are not accepted. Demo data is labeled DEMO and is not suitable for operational decisions. Full policy: docs/architecture/IP_POLICY.md. Security reports: see SECURITY.md.
Part of the East Africa coordination stack
Install & run:pip install reli-cli && reli list ā the MCP servers on the official MCP Registry under io.github.gabrielmahia