Geepers

Multi-agent orchestration system with MCP tools and Claude Code plugin agents.

Installation

From PyPI (MCP tools)

pip install geepers

# With optional dependencies
pip install geepers[all]
pip install geepers[anthropic,openai]

As Claude Code Plugin (agents)

/plugin add lukeslp/geepers

What's Included

43 Specialized Agents

Markdown-defined agents for Claude Code that provide specialized workflows:

90+ MCP Tools

Six specialized MCP servers expose tools for:

• geepers-unified - All tools in one server
• geepers-providers - 13 LLM providers (Anthropic, OpenAI, xAI, etc.)
• geepers-data - 29+ data sources (Census, arXiv, GitHub, NASA, etc.)
• geepers-cache - Redis-backed caching
• geepers-utility - Document parsing, citations, TTS
• geepers-websearch - Multi-engine web search

FREE Alternative: Use Ollama for Local LLM

Want to run geepers without paying for LLM APIs? Replace Anthropic/OpenAI/xAI with Ollama for $0/month.

Quick Comparison

Savings: $600-2,400/year for multi-agent orchestration.

Why Ollama for Geepers?

Benefits:

• Zero Cost: No API usage fees for 43 agents
• Privacy: All 90+ MCP tools run locally
• Unlimited: Run as many agent calls as needed
• Offline: No internet required after model download
• GDPR/HIPAA: Compliant by default (local-only)

Recommended Models:

• llama3.2:7b - Best for general agents (4GB)
• mistral:7b - Fast and efficient (4GB)
• codellama:13b - Code-focused agents (7GB)
• mixtral:8x7b - Advanced reasoning (26GB)

Setup Guide

1. Install Ollama

# macOS
brew install ollama
brew services start ollama

# Linux
curl -fsSL https://ollama.com/install.sh | sh
sudo systemctl start ollama

# Pull model (4GB download)
ollama pull llama3.2

See ollama-local-ai plugin for detailed setup.

2. Install Geepers with Local LLM Support

# Install without paid provider dependencies
pip install geepers

# No need for [anthropic,openai] extras!

3. Configure Ollama as LLM Provider

Create ~/.geepers/config.yaml:

llm:
  provider: ollama
  base_url: http://localhost:11434
  model: llama3.2
  temperature: 0.7

# No API keys required!

4. Update MCP Config

{
  "mcpServers": {
    "geepers": {
      "command": "geepers-unified",
      "env": {
        "GEEPERS_LLM_PROVIDER": "ollama",
        "OLLAMA_BASE_URL": "http://localhost:11434",
        "OLLAMA_MODEL": "llama3.2"
      }
    }
  }
}

Cost Comparison: 43 Agents

Cloud APIs (Anthropic/OpenAI)

43 agents × 1000 calls/month × $0.002/call = $86/month
Annual cost: $1,032

Required API Keys:

• Anthropic Claude API: $50-100/mo
• OpenAI GPT-4: $30-80/mo
• xAI Grok: $20-50/mo
• Total: $100-230/mo

Ollama (Local LLM)

43 agents × unlimited calls/month × $0 = $0/month
Annual cost: $0

Required:

• Hardware you already own
• One-time model download (4-26GB)
• Total: $0/mo

Savings: $1,200-2,760/year

Migration Examples

Before (Paid APIs)

# Install with paid dependencies
pip install geepers[anthropic,openai]

# Set API keys
export ANTHROPIC_API_KEY=sk-ant-...
export OPENAI_API_KEY=sk-...
export XAI_API_KEY=xai-...

Monthly Cost: $100-230

After (Ollama)

# Install without paid dependencies
pip install geepers

# Start Ollama (one-time setup)
ollama pull llama3.2
ollama serve

# Configure geepers
export GEEPERS_LLM_PROVIDER=ollama
export OLLAMA_BASE_URL=http://localhost:11434

Monthly Cost: $0

Real Use Case: Multi-Agent Session

Scenario: Running geepers_orchestrator_checkpoint (5 agent calls per session)

Cloud APIs Version

# Using Anthropic Claude
import anthropic

client = anthropic.Anthropic(api_key="sk-ant-...")
response = client.messages.create(
    model="claude-3-5-sonnet-20241022",
    messages=[{"role": "user", "content": "Scout the repo"}]
)

Cost per session: 5 calls × $0.002 = $0.01 Monthly (100 sessions): $1.00 Annual: $12.00

Ollama Version

# Using local Ollama
import ollama

response = ollama.chat(
    model='llama3.2',
    messages=[{"role": "user", "content": "Scout the repo"}]
)

Cost per session: 5 calls × $0 = $0.00 Monthly (100 sessions): $0.00 Annual: $0.00

Same intelligence, zero cost.

Performance Comparison

Agent-Specific Recommendations

Fast Agents (scout, status, snippets):

ollama pull llama3.2:7b  # Fast, 4GB