Which integrations are available for this server?

Integrates with [GitHub Copilot](/mcp/servers/integrations/github-copilot) CLI to provide access to local LLM capabilities through MCP tools for task delegation and reasoning. Supports [Google Gemini](/mcp/servers/integrations/google-gemini) as an optional cloud fallback backend for task delegation and reasoning when local models are unavailable. Provides integration with [Ollama](/mcp/servers/integrations/ollama) for running local LLMs, including automatic model selection, context-aware routing, and support for multiple model tiers (quick, coder, MoE, thinking).

Delia

A Model Context Protocol (MCP) server that cultivates your local LLM garden. Plant a seed, let Delia pick the right vine, and harvest a fresh melon.

Delia - from Greek Δηλία, "from Delos" (the sacred island). Also, she grows watermelons.

Features

Smart Vine Selection: Routes seeds to the right vine - quick (7B), coder (14B+), moe (30B+), or thinking
Multi-Garden Support: Ollama, llama.cpp, and Gemini gardens with automatic failover
Context-Aware Routing: Handles large seeds with appropriate context windows
Circuit Breaker: Drought protection with graceful recovery
Parallel Processing: Tends multiple seeds simultaneously
Authentication: Optional greenhouse access control
Usage Tracking: Per-gardener quotas and harvest monitoring
Dashboard: Real-time garden status with watermelon-themed activity feed

Requirements

Hardware

Component	Minimum	Recommended	Large Models
GPU	4GB VRAM	12GB VRAM	24GB+ VRAM
RAM	8GB	16GB	32GB+
Storage	10GB	30GB	50GB+

Software

Python 3.11+
uv package manager
One or more backends:
- Ollama (recommended)
- llama.cpp
- Google Gemini API (optional cloud fallback)

Quick Start

# Clone and install git clone https://github.com/zbrdc/delia.git cd delia uv sync # Pull models (examples - choose based on your hardware) ollama pull qwen3:14b # General purpose ollama pull qwen2.5-coder:14b # Code specialized ollama pull qwen3:30b-a3b # Complex reasoning # Run server uv run python mcp_server.py

Integration

Delia works with AI coding assistants via MCP. Choose your tool:

VS Code / GitHub Copilot

Add to ~/.config/Code/User/mcp.json:

{ "servers": { "delia": { "command": "uv", "args": ["run", "--directory", "/path/to/delia", "python", "mcp_server.py"], "type": "stdio" } } }

Reload VS Code to activate.

Claude Code

Create ~/.claude/mcp.json:

{ "mcpServers": { "delia": { "command": "uv", "args": ["run", "--directory", "/path/to/delia", "python", "mcp_server.py"] } } }

Then run claude and use @delia to delegate tasks.

Gemini CLI

Option 1: HTTP Mode (Recommended)

# Start server uv run python mcp_server.py --transport sse --port 8200

Add to ~/.gemini/settings.json:

{ "mcpServers": { "delia": { "url": "http://localhost:8200/sse", "transport": "sse" } } }

Option 2: STDIO Mode

Add to ~/.gemini/settings.json:

{ "mcpServers": { "delia": { "command": "uv", "args": ["run", "--directory", "/path/to/delia", "python", "mcp_server.py"] } } }

GitHub Copilot CLI

Create ~/.copilot-cli/mcp.json:

{ "servers": { "delia": { "command": "uv", "args": ["run", "--directory", "/path/to/delia", "python", "mcp_server.py"] } } }

Configuration

Backend Configuration

Edit settings.json in the project root:

{ "backends": [ { "id": "ollama-local", "name": "Ollama Local", "provider": "ollama", "type": "local", "url": "http://localhost:11434", "enabled": true, "priority": 1, "models": { "quick": "qwen3:14b", "coder": "qwen2.5-coder:14b", "moe": "qwen3:30b-a3b", "thinking": "deepseek-r1:14b" } } ], "routing": { "prefer_local": true, "fallback_enabled": true } }

Gemini Cloud Backend (Optional)

Add Gemini as a cloud fallback:

# Install dependency uv add google-generativeai # Set API key export GEMINI_API_KEY="your-key-from-aistudio.google.com"

Add to settings.json:

{ "id": "gemini-cloud", "name": "Gemini Cloud", "provider": "gemini", "type": "remote", "url": "https://generativelanguage.googleapis.com", "enabled": true, "priority": 10, "models": { "quick": "gemini-2.0-flash", "coder": "gemini-2.0-flash", "moe": "gemini-2.0-flash" } }

Authentication (Optional)

For HTTP mode with multiple users:

# Quick setup python setup_auth.py # Or manually export DELIA_AUTH_ENABLED=true export DELIA_JWT_SECRET="your-secure-secret"

Supports username/password and Microsoft 365 OAuth.

Transport Modes

# STDIO (default) - for VS Code, Claude Code, Copilot CLI uv run python mcp_server.py # HTTP/SSE - for Gemini CLI, web clients, remote access uv run python mcp_server.py --transport sse --port 8200 # View all options uv run python mcp_server.py --help

Tools

Delia provides these MCP tools:

Tool	Description
`delegate`	Execute tasks with automatic model selection
`think`	Extended reasoning for complex problems
`batch`	Process multiple tasks in parallel
`health`	Check backend status and statistics
`models`	List available models and tiers
`switch_backend`	Switch between backends at runtime
`switch_model`	Change model for a tier
`get_model_info`	Get model specifications

Vine Selection

Delia picks the right vine for every seed:

Vine	Size	Best For
Quick	7B-14B	Summaries, simple questions
Coder	14B-30B	Generation, review, debugging
MoE	30B+	Architecture, critique, analysis
Thinking	Specialized	Extended reasoning, research

Override with hints in your prompt: "use the large model" or "quick answer".

Troubleshooting

Server won't start

# Check Ollama is running curl http://localhost:11434/api/tags # Test server import uv run python -c "import mcp_server; print('OK')"

MCP not connecting

Verify path in config points to correct directory
Reload VS Code / restart Claude Code
Check logs: ~/.cache/delia/live_logs.json

"Unknown" responses

Backend not running or unreachable
Check settings.json configuration
Run curl http://localhost:11434/health

Slow responses

Try smaller models
Check system resources (nvidia-smi, htop)
Reduce context size in settings.json

Performance

Typical harvest times (modern hardware):

Quick vine: 2-5 seconds
Coder vine: 5-15 seconds
MoE/Thinking vines: 30-60 seconds

License

BSD 3-Clause

Acknowledgments

Ollama - Local LLM runtime
MCP Python SDK - Protocol implementation
Qwen - Base models

Delia

Delia

Features

Requirements

Hardware

Software

Quick Start

Integration

VS Code / GitHub Copilot

Claude Code

Gemini CLI

GitHub Copilot CLI

Configuration

Backend Configuration

Gemini Cloud Backend (Optional)

Authentication (Optional)

Transport Modes

Tools

Vine Selection

Troubleshooting

Server won't start

MCP not connecting

"Unknown" responses

Slow responses

Performance

License

Acknowledgments

Resources

Tools

New MCP Servers

Latest Blog Posts

MCP directory API