01
Multi-Model Workflows
Combine different AI models for complex tasks - use one for reasoning, another for code.
Use GPT-4 for analysis and Claude for code generation in the same taskAI & LLM Updated Jan 2026
Sequential Thinking
Enhance AI reasoning with step-by-step thinking for complex problems.
95 /100
Quick Overview
Everything you need to know about Sequential Thinking
Best For
- AI-powered workflows
- LLM integrations
- Model management
Requirements
- Node.js 18+ or Bun
Quick Start
- 1Install via npx or bun
- 2Add to your MCP config
- 3Restart your AI assistant
- 4Start using 0 tool
How good is this MCP?
Our scoring algorithm analyzes multiple dimensions to help you make informed decisions.
82 /100
Very Good
Score Breakdown by Dimension
This is a simplified score based on publicly available data. Full scoring with all 5 dimensions coming soon!
Adoption How popular and trusted is this MCP?
98
Based on 75.7k GitHub stars
Activity Is this project actively maintained?
60
Last updated 49 days ago
Coming Soon
More insights on the way
Trend Analysis Track how the score evolves over time
Percentile Ranking See where this MCP ranks among all servers
Compare MCPs Side-by-side comparison of similar servers
What can this MCP do?
Explore the 0 tools available in Sequential Thinking
Tool Discovery Pending
We haven't indexed the tools for this MCP yet. This usually means:
- The MCP manifest isn't published or is in a custom format
- Tools are dynamically generated at runtime
- The repository was recently added to our catalog
Get Started in Seconds
Add Sequential Thinking to your AI coding assistant
4 Compatible IDEs
npx One-command install
Choose your IDE:
Config file location
~/Library/Application Support/Claude/claude_desktop_config.json Windows: %APPDATA%\Claude\claude_desktop_config.json{
"mcpServers": {
"sequential-thinking": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-sequentialthinking"
]
}
}
}1 Save the configuration file
2 Restart Claude Desktop
Ready to use!
Try It Out
Copy these prompts to get started with Sequential Thinking
How to use these prompts
Open your AI assistant with Sequential Thinking enabled, paste any prompt below, and watch the magic happen.
2 official examples
Workflows
Use Cases
Common workflows and scenarios for AI & LLM MCPs
02
Image Generation
Generate images from text descriptions using DALL-E, Stable Diffusion, or Midjourney.
Create a logo for my startup based on this description03
Specialized Analysis
Access models fine-tuned for specific domains like legal, medical, or financial.
Analyze this contract using our legal-trained model04
Embedding & Search
Generate embeddings for semantic search and similarity matching.
Find similar documents in our knowledge base to this query05
Voice & Audio
Transcribe audio, generate speech, or process voice commands.
Transcribe this meeting recording and summarize key points06
Cost Optimization
Route requests to cheaper models for simple tasks, expensive ones for complex.
Use a fast model for classification, GPT-4 only for generationWhy use AI & LLM MCPs?
Key advantages of integrating Sequential Thinking with your AI assistant
1
Model Diversity
Access multiple AI providers from a single interface.
2
Specialized Capabilities
Use the best model for each specific task.
3
Cost Control
Route requests to cost-effective models when appropriate.
4
Fallback & Redundancy
Automatically fallback to alternative models if one fails.
5
Unified Interface
Interact with all AI services through your primary assistant.
6
Custom Fine-tuning
Access your own fine-tuned models through MCP.
Example Prompts — Sequential Thinking
6 prompts
Important Considerations
- API calls to AI services incur costs - monitor your usage
- Different models have different rate limits and quotas
- Sensitive data may be sent to external AI providers
- Image generation may have content policy restrictions
- Fine-tuning requires significant computational resources
Guidelines
Best Practices
Tips for getting the most out of Sequential Thinking
Do This
Use GPT-3.5 for simple classification, GPT-4 for complex reasoning
Configure alternative models as backups
Check provider policies before generating sensitive content
Use environment variables for API keys
VS
Avoid This
Use the most expensive model for every request
Assume AI calls will always succeed
Assume all models allow all types of content
Hardcode API keys in configuration files
Tools
Common Tool Patterns
Typical tools found in AI & LLM MCPs
generate generationGenerate text or completions from a model
embed embeddingCreate vector embeddings for text
image_generate generationGenerate images from text prompts
transcribe processingConvert audio to text
classify analysisClassify text into categories
list_models utilityList available models and their capabilities