Summon-MCP
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Summon-MCPSummon an expert in renewable energy"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
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 superpromptsWhat 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.
Related MCP server: Multi Agent Orchestrator MCP
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-mcpInstall from Source
git clone https://github.com/ZionHopkins/Summon-MCP.git
cd Summon-MCP
npm install
npm run buildUsage
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 |
| Classify objective, recommend shape, generate questions |
| Generate search queries + domain map template |
| Design architecture (expert/council/org/hybrid) |
| Generate 11-layer superprompt templates |
| Generate deployment configs (Claude Project / Paperclip) |
| Run entire pipeline end-to-end |
Resources
Resource | Content |
| Digital Twin Framework quick reference |
| Synthetic Expert Framework quick reference |
| Operations Manual quick reference |
| Paperclip deployment reference |
| Mandatory inter-layer coupling map |
| v5 Master Assembly Template |
| Four archetype definitions + coupling patterns |
Prompts
Prompt | Use |
| "I want to [achieve X]" — objective-first pipeline |
| "Build me an org for [domain]" — full org |
| "Summon an expert in [domain]" — single expert |
| "I need a council for [decision]" — multi-expert debate |
| "Summon [Person Name]" — digital twin |
| "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 versionRoadmap
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)
This server cannot be installed
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Servers
- AlicenseAqualityCmaintenanceProvides LLMs with cognitive tools (Thinking Models), memory structures (Cells), and multi-agent patterns (Organs) for advanced reasoning, memory management, and orchestration. Automatically routes requests to appropriate strategies and generates custom agent blueprints.12MIT
- Alicense-qualityDmaintenanceCoordinates specialized agents (Architecture, Quality, Cloud, Prompt) to plan, build, test, and deploy applications with self-healing capabilities, authentication, and analytics for autonomous software engineering workflows.1MIT
- AlicenseBqualityDmaintenanceA goal-agnostic parallel orchestration framework that enables sophisticated multi-agent coordination for tasks like code generation, UI development, and research through specification-driven architecture. It utilizes wave-based generation and intelligent context management to execute complex, iterative agentic loops.51MIT
- AlicenseAqualityAmaintenanceOrchestrates multiple AI coding agents declaratively to automate software development workflows for engineering teams.212879Apache 2.0
Related MCP Connectors
Deterministic reasoning stack for AI agents: simulate, decide & compute, plus cross-domain tools.
Build, validate, and deploy multi-agent AI solutions from any AI environment.
Sovereign Agent OS — Persistent Memory, Governance & Compliance for AI Agents.
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/ZionHopkins/Summon-MCP'
If you have feedback or need assistance with the MCP directory API, please join our Discord server