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io.github.gabrielmahia/offline-mcp

Registre officiel Cloud et DevOps

Local AI over Ollama for low connectivity: status, local inference, model and deployment guides.

Code source Documentation

Installation

Ajoutez ceci à la configuration MCP de votre client (Claude Desktop : claude_desktop_config.json ; Cursor : .cursor/mcp.json ; VS Code et les autres utilisent la même forme « mcpServers »).

PYPI package offline-mcp
Claude Code 
claude mcp add offline-mcp -- uvx offline-mcp==0.1.10
Configuration JSON (Claude Desktop, Cursor, VS Code) 
{
    "mcpServers": {
        "offline-mcp": {
            "command": "uvx",
            "args": [
                "offline-mcp==0.1.10"
            ]
        }
    }
}

Documentation

Tirée du README du projet sur GitHub, actualisée chaque semaine. Les liens ouvrent GitHub.

Sommaire
  1. offline-mcp
  2. Why This Exists: Data Sovereignty
  3. Research Foundation
  4. Install
  5. Tools (6)
  6. Context
  7. License
  8. Part of the East Africa Coordination Stack
  9. IP & Collaboration
  10. Part of the East Africa coordination stack

offline-mcp

Install: pip install offline-mcp · Use with any MCP client.

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

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."
— 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) — Offline-First LLM Architecture for Adaptive Learning in Low-Connectivity Environments — 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 — 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

pip install offline-mcp

Tools (6)

ToolDescription
check_ollama_statusCheck if Ollama is running locally and list available models
run_local_inferenceRun a prompt through a local Ollama model
list_recommended_modelsBest open-weight models for East Africa use cases
degraded_mode_guide4-level degraded mode architecture for offline operation
open_weights_directoryDirectory of open-weight models with Africa language support
local_deployment_guideDeployment 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.

→ The Nairobi Stack

License

MIT © Gabriel Mahia | contact@aikungfu.dev

Part of the East Africa Coordination Stack

This MCP server is part of the Kenya coordination infrastructure. Connect it to africa-coord-bus — the coordination event bus that routes signals between domains automatically.

pip install africa-coord-bus

All servers: pypi.org/user/gmahia Live demo: coord-cascade-demo

IP & Collaboration

MIT licensed. Feedback via GitHub Issues only — 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

Model-agnostic by design: closed APIs, open-weight models, and small distilled models are all first-class citizens.

Questions fréquentes

Qu'est-ce que io.github.gabrielmahia/offline-mcp ?

Local AI over Ollama for low connectivity: status, local inference, model and deployment guides.

Comment installer io.github.gabrielmahia/offline-mcp ?

Il s'exécute sur votre machine. Dans Claude Code : claude mcp add offline-mcp -- uvx offline-mcp==0.1.10. Pour les autres clients, collez la configuration JSON de cette page dans leurs réglages MCP.

Faut-il une clé API pour io.github.gabrielmahia/offline-mcp ?

Son entrée au registre n'indique aucune clé ni secret obligatoire. Certaines fonctions peuvent tout de même demander un compte auprès du service auquel il se connecte.

io.github.gabrielmahia/offline-mcp est-il open source ?

Oui. Son code est sur GitHub sous licence MIT.

Qui maintient io.github.gabrielmahia/offline-mcp ?

Il est publié par gabrielmahia. AI.tn le référence sans le maintenir ni le recommander.

Issu du registre MCP officiel. Être listé n'est pas une recommandation : vérifiez le code et les permissions d'un serveur avant de lui donner accès à vos données.