Summon-MCP
Objective-driven cognitive architecture engine that builds single experts, councils, or full autonomous organizations from user goals, generating deployment-ready superprompts and configurations.
README
SUMMON MCP
Objective-Driven Cognitive Architecture Engine
Say what you want to achieve. SUMMON figures out the right cognitive architecture — single expert, council of minds, or full autonomous organization — and builds it deployment-ready.
"I want to grow my SaaS to $10M ARR"
→ SUMMON classifies: business_growth → full_org
→ Researches SaaS scaling domain
→ Designs 6-agent org with 4 archetype diversity
→ Builds 11-layer superprompts with coupling verification
→ Outputs Paperclip-ready deployment package
"Summon an expert in regenerative agriculture"
→ SUMMON classifies: learning_mastery → single_expert
→ Researches the domain (5+ web searches)
→ Builds one deep Integrator-archetype expert
→ Outputs Claude.ai Project prompt + re-anchoring template
"I need a council to evaluate this acquisition"
→ SUMMON classifies: decision_support → council
→ Builds 4 experts with structurally different reasoning
→ Outputs debate protocol + conflict map + all superprompts
What This Is
An MCP server that encodes three cognitive architecture frameworks into a reusable tool pipeline:
- Digital Twin Superprompt Framework v5 — 11-layer cognitive architecture for reconstructing any mind
- Synthetic Expert Creation Framework v3 — domain-first expert construction with archetype coupling
- Cognitive Twin System Operations Manual v2 — anti-drift engineering, deployment, evaluation
The MCP server handles orchestration. The host LLM (Claude, etc.) handles all research and reasoning via its native web search. Zero API keys required.
Quick Start
Install via npx (Recommended)
No installation required — just configure your MCP client:
Connect to Claude Desktop
Add to your Claude Desktop config (claude_desktop_config.json):
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"summon": {
"command": "npx",
"args": ["summon-mcp"]
}
}
}
Restart Claude Desktop. SUMMON tools will appear in your tool list.
Connect to Claude Code
claude mcp add summon -- npx summon-mcp
Install from Source
git clone https://github.com/ZionHopkins/Summon-MCP.git
cd Summon-MCP
npm install
npm run build
Usage
Objective-First (SUMMON decides the shape)
"I want to build a competitive intelligence operation for the semiconductor industry"
"Help me build generational wealth"
"I need to master negotiation for my next funding round"
Direct Entry Points
"Summon an expert in biotech" — builds a single deep synthetic expert
"Summon Naval Ravikant" — builds a digital twin from research
"Build me an organization for content production" — builds a full Paperclip-deployable org
"I need a council to decide whether to pivot my product" — builds a 3-5 expert debate council
Upgrade Existing Agents
"Upgrade this agent to v5 architecture" — adds coupling, SCAN checkpoints, Chain of Persona
Architecture
How It Works
User states objective
↓
summon_discover → classifies objective → recommends architecture shape → asks smart questions
↓
summon_research → generates search queries → host LLM does web research → fills domain map
↓
summon_design → designs architecture (expert/council/org/hybrid) → DMAD verification
↓
summon_build_agents → returns 11-layer templates → host LLM builds superprompts → coupling validation
↓
summon_deploy_config → generates deployment package (Claude Project / Paperclip / both)
Key Design Decision: Thick Orchestration, Thin Cognition
The MCP server does not call external APIs. The host LLM does all research and reasoning. The server handles workflow sequencing, template assembly, validation, and config generation. This means:
- Zero API keys required
- Zero external dependencies
- Works with any MCP-compatible host LLM
- The user's Claude session handles all intelligence work
Objective Types → Architecture Shapes
| Objective | Shape | Why |
|---|---|---|
| Business growth | Full org | Multiple functions needed |
| Wealth creation | Council | Multi-perspective analysis |
| Intelligence product | Full org | Domain specialists + delivery |
| Learning/mastery | Single expert | Deep domain expert |
| Creative production | Full org | Creative council + pipeline |
| Decision support | Council | Diverse reasoning approaches |
| Operational automation | Full org | Process specialists + QA |
| Research/discovery | Full org or council | Research + synthesis |
| Digital twin | Single agent | One deep 11-layer twin |
Tools
| Tool | Purpose |
|---|---|
summon_discover |
Classify objective, recommend shape, generate questions |
summon_research |
Generate search queries + domain map template |
summon_design |
Design architecture (expert/council/org/hybrid) |
summon_build_agents |
Generate 11-layer superprompt templates |
summon_deploy_config |
Generate deployment configs (Claude Project / Paperclip) |
summon_full_pipeline |
Run entire pipeline end-to-end |
Resources
| Resource | Content |
|---|---|
summon://frameworks/digital-twin-v5 |
Digital Twin Framework quick reference |
summon://frameworks/synthetic-expert-v3 |
Synthetic Expert Framework quick reference |
summon://frameworks/operations-manual-v2 |
Operations Manual quick reference |
summon://references/paperclip |
Paperclip deployment reference |
summon://templates/coupling-map |
Mandatory inter-layer coupling map |
summon://templates/assembly |
v5 Master Assembly Template |
summon://templates/archetypes |
Four archetype definitions + coupling patterns |
Prompts
| Prompt | Use |
|---|---|
summon-objective |
"I want to [achieve X]" — objective-first pipeline |
summon-organization |
"Build me an org for [domain]" — full org |
summon-expert |
"Summon an expert in [domain]" — single expert |
summon-council |
"I need a council for [decision]" — multi-expert debate |
summon-twin |
"Summon [Person Name]" — digital twin |
summon-upgrade |
"Upgrade this agent" — add v5 architecture |
The 11-Layer Cognitive Architecture
Every full-depth agent built by SUMMON has:
- Mental Models — how they process information
- Core Beliefs — non-negotiable worldview (contrarian positions)
- Decision Frameworks — rules governing choices
- Communication Style — tone, phrases, delivery
- Emotional Processing — what energizes/frustrates, how it affects output
- Anti-Patterns — what they NEVER do (min 5 entries)
- Belief Conflict Map — where they clash with mainstream
- Domain Transfer — how to apply outside primary domain
- Metacognition — how they monitor their own thinking
- Uncertainty Management — how they handle unknowns
- Response Protocol — step-by-step with Chain of Persona self-check
Plus SCAN checkpoints for anti-drift and inter-layer coupling ensuring every layer references 2+ others by name.
The Four Archetypes
| Archetype | Tightest Coupling | Metacognition Check |
|---|---|---|
| Systematizer | Mental Models → Decision Frameworks | "Is this process repeatable?" |
| Contrarian | Core Beliefs → Belief Conflict Map | "Am I being contrarian for its own sake?" |
| First-Mover | Uncertainty Mgmt → Decision Frameworks | "Am I moving too early, or too late?" |
| Integrator | Domain Transfer → Mental Models | "Am I forcing a false synthesis?" |
Quality Guarantees
SUMMON enforces these rules in code:
- Every full-depth superprompt has all 11 layers in XML tags
- Every layer references 2+ other layers by specific name (coupling verification)
- SCAN checkpoints at position 2→3 and 4→5 boundaries
- Response Protocol includes Chain of Persona (3 named layer checks)
- Every multi-agent architecture has 2+ different archetype signatures (DMAD)
- Anti-Patterns minimum 5 entries per full-depth agent
- Paperclip budgets never set to 0 (runaway protection)
- Paperclip heartbeats never below 30 seconds
Deployment Targets
- Single experts & councils → Claude.ai Project system prompt (copy-paste ready)
- Full organizations → Paperclip deployment package (company config, agent configs, agents.md files, heartbeats, budgets, org chart, Claude Code build prompt)
- Hybrid → Both outputs
Development
npm install # Install dependencies
npm run build # Compile TypeScript
npm run dev # Run with tsx (development)
npm start # Run compiled version
Roadmap
- [ ] Community template library — share and import org architectures
- [ ] Automated quality scoring via LLM-as-judge
- [ ] Multi-orchestrator output (CrewAI, LangGraph, AutoGen configs)
- [ ] Fine-tuning integration for persistent high-fidelity twins
- [ ] Visual org chart rendering
- [ ] Optimization loop execution (autoresearch)
License
MIT
Credits
Built on three cognitive architecture frameworks:
- Digital Twin Superprompt Framework v5
- Synthetic Expert Creation Framework v3
- Cognitive Twin System Operations Manual v2
Deployment target: Paperclip AI
Protocol: Model Context Protocol (MCP)
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.