systems-thinking-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., "@systems-thinking-mcpAnalyze our recent database outage with feedback loops and constraint analysis."
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.
systems-thinking-mcp
An MCP server that provides systems thinking models as composable analysis lenses for architecture, infrastructure, DevOps, incident analysis, and technical decision-making.
Inspired by @modelcontextprotocol/server-sequential-thinking. Where sequential-thinking emphasizes rigor — structured step-by-step reasoning with revision and branching — this tool emphasizes abstraction. It provides a library of mental models (feedback loops, constraint analysis, inversion, etc.) that shift Claude's perspective on a problem. The two are complementary: use sequential-thinking to reason carefully through a problem, use systems-thinking to ensure Claude's looking at it from the right angles. This helps prevent tunnel vision, surface edge cases and unintended consequences, and reign in some of Claude's grandiousity by challenging the LLM to view the problem in the broader context in which it lives.
I've had good luck using this in troubleshooting and debugging, design, code review, and spec review (pairs nicely with superpower-mcp just run it against the produced spec after the spec review cylce). This is a highly general tool and can provide good results across different domains, development, infrastructure, devops.
How it works
Five tools with a lifecycle: start a session (returns model clusters by category), expand your selection (get full model details and graph neighbors), apply 2-4 lenses from different perspectives, then synthesize across them.
The value isn't in any single lens — it's in the composition. Each model surfaces things the others miss, and the server provides prior findings from earlier lenses so the LLM can judge connections between them. When you apply constraint analysis and then queuing theory, the findings from the first lens are available when applying the second.
Models also define counterbalances — deliberately opposing perspectives. When you apply leverage-points, the server suggests KISS as a counterbalance: "The simplest solution may miss high-leverage structural changes that pay off long-term." This productive tension prevents single-framework tunnel vision.
Related MCP server: Clear Thought MCP Server
Install
{
"mcpServers": {
"systems-thinking": {
"type": "stdio",
"command": "npx",
"args": ["-y", "systems-thinking-mcp"]
}
}
}Or run locally:
git clone https://github.com/davidpanter/systems-thinking.git
cd systems-thinking
npm install && npm run build{
"mcpServers": {
"systems-thinking": {
"type": "stdio",
"command": "node",
"args": ["/path/to/systems-thinking/dist/index.js"]
}
}
}Tools
Tool | Purpose |
start_analysis | Frame a problem. Returns model clusters grouped by category for selection. |
expand_selection | Takes model IDs. Returns full model details, graph neighbors, counterbalances, and uncovered categories. |
apply_lens | Apply a model to the problem. Returns prior findings from earlier lenses, counterbalance suggestions, analysis depth indicator, and complementary next lenses. |
synthesize | Integrate findings across all applied lenses. Suggests additional lenses to fill gaps. |
get_strategy | Returns a concern map (domain, focus, weight) for a named strategy, guiding which categories to prioritize. |
Models (56)
Category | Models |
Architecture | Modularity, Coupling & Cohesion, Conway's Law, Failure Modes, KISS, Separation of Concerns, Idempotency, Blast Radius, State Ownership, Error Propagation, Contract Boundaries, Data Transformation Fidelity |
Dynamics | Source & Sink, System Dynamics, Feedback & Feedforward Loops, Stock & Flow, Causal Loop Diagrams, Local vs Global Optimization |
Operations | Queuing Theory, Buffers & Buffer Sizing, Constraint Analysis, Leverage Points, Migration |
Paradigms | Functional Lens, Domain Modeling Lens, Event-Driven Lens |
Reasoning | Inversion, Second-Order Thinking, Map vs Territory, Circle of Competence, Occam's Razor, Margin of Safety, Reversibility, Hanlon's Razor, Build vs. Buy, Dependency Risk, Adversarial Analysis, Goodhart's Law |
Reliability | Observability Gaps, Error Budgets, Graceful Degradation, Back Pressure, Operational Complexity |
Schema | Normalization, Denormalization |
Security | CIA Triad, Least Privilege, Attack Surface, Defense in Depth, Trust Boundaries |
Troubleshooting | Bottom-Up, Top-Down, Binary Search, Parallelism, Caches, What's Changed |
Models support multi-facet categories via a categories array in YAML, allowing a single model to appear in multiple categories.
Strategies (8)
Strategies guide the LLM toward the right categories for a given task. Each strategy defines a concern map — a list of domains (matching category names) with a focus question and weight (required, conditional, optional). Strategies work for any system — code, infrastructure, pipelines, platforms, or design documents. Strategy-to-model validation runs at startup, ensuring concern domains match actual category names.
Strategy | Description |
system-design | Designing or evaluating system architecture, infrastructure, or design documents |
code-review | Reviewing code changes for structural and operational issues |
incident-investigation | Diagnosing production incidents |
post-mortem | Systemic analysis after incidents — feedback loops, structural weaknesses, incentive misalignments |
security-audit | Evaluating security posture |
capacity-planning | Planning for load, growth, and resource constraints |
technical-decision | Evaluating build/buy, migration, and technology choices |
codebase-understanding | Building a mental model of an unfamiliar system or area of code |
Custom models
Add your own models via --models-dir. Custom models with the same ID as built-in models override them.
{
"mcpServers": {
"systems-thinking": {
"type": "stdio",
"command": "npx",
"args": ["-y", "systems-thinking-mcp", "--models-dir", "/path/to/models"]
}
}
}Models are YAML files in category subdirectories. See models/ for the format.
Environment variables
DISABLE_THOUGHT_LOGGING=true— suppress stderr logging
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