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Launch MCP orchestration workflows (Dream Cascade and Dream Swarm) for multi-agent coordination and synthesis.
This skill uses the workspace's default tool permissions.
reference/examples.mdscripts/cascade-research.pyscripts/cascade-status.pyscripts/cascade.pyscripts/monitor.pyscripts/orchestrator.pyscripts/server.pyscripts/swarm.pysrc/core/llm/__init__.pysrc/core/llm/anthropic_provider.pysrc/core/llm/claude_code_provider.pysrc/core/llm/cohere_provider.pysrc/core/llm/complexity_router.pysrc/core/llm/elevenlabs_provider.pysrc/core/llm/factory.pysrc/core/llm/gemini_provider.pysrc/core/llm/groq_provider.pysrc/core/llm/huggingface_provider.pysrc/core/llm/manus_provider.pysrc/core/llm/mistral_provider.pyMCP Orchestration Skill (formerly Dream Cascade)
The MCP Orchestration skill provides advanced multi-agent coordination patterns for Claude. It allows you to launch massive, hierarchical research swarms or task-specific agent teams to solve complex problems that require multiple perspectives or large-scale data processing.
Architecture: Dream Cascade
The primary pattern is the Dream Cascade, a 3-tier hierarchical swarm:
- Tier 1: Belters (Workers)
- Parallel agents (1-30+) that execute specific subtasks.
- Each Belter has a unique specialization (Research, Analysis, Technical, etc.).
- Tier 2: Drummers (Synthesizers)
- Aggregation agents that synthesize every 5 Belter responses.
- They filter noise and highlight key findings from the worker tier.
- Tier 3: Camina (Executive)
- Final synthesis agent that provides a high-level strategic report based on Drummer syntheses.
Features
- Hierarchical Synthesis: Automatic aggregation of insights from large swarms.
- Multi-Provider Support: Switch between Anthropic, OpenAI, Gemini, etc.
- Cost Optimization: Uses
ProviderFactoryto select models based on tier and task complexity. - Structured Reporting: Generates Markdown, PDF, and DOCX reports via the
reportinglibrary. - Parallel Execution: Handled with
asyncioand semaphore-based rate limiting.
Setup
Environment Variables
Ensure the following API keys are set:
ANTHROPIC_API_KEYOPENAI_API_KEYGEMINI_API_KEY- (Other providers defined in
src/core/llm/factory.py)
Claude Desktop Configuration
Add the following to your claude_desktop_config.json:
{
"mcpServers": {
"orchestration": {
"command": "python3",
"args": ["/home/coolhand/geepers/skills/source/mcp-orchestration/scripts/server.py"]
}
}
}
Available Tools
dream_orchestrate_research
Starts a hierarchical 3-tier research workflow.
Parameters:
task(string, required): The research topic or question.num_agents(integer): Total number of Belters (default: 5).enable_drummer(boolean): Whether to enable synthesis tier (default: true).enable_camina(boolean): Whether to enable executive tier (default: false).provider_name(string): LLM provider to use (default: "anthropic").
CLI Usage
You can also run the orchestrator directly from the command line:
# Basic run with 5 belters
python3 scripts/orchestrator.py "What is the future of AGIs?"
# Advanced run with 15 belters, 3 drummers, and 1 camina
python3 scripts/orchestrator.py "Analyze the global semiconductor supply chain" --belters 15 --drummers 3 --caminas 1 --pdf
Internal Structure
scripts/: Executable entry points (CLI and Server).src/core/orchestration/: Core logic and patterns.src/core/llm/: Unified provider factory.src/core/reporting/: Multi-format report generation.reference/: Examples and templates.