Sequential Thinking Mcp Server

What is Sequential Thinking MCP Server?

Sequential Thinking MCP Server is a cloud-hosted Model Context Protocol (MCP) server that enables AI agents to break down complex problems into structured thinking sequences. Unlike simple prompt-response interactions, this server maintains a persistent chain of thoughts with support for revisions, branching, and session persistence.

This Actor is designed for developers building AI agents, automation workflows, and applications that require structured reasoning capabilities. Whether you're building with Claude, GPT, or other LLMs, the Sequential Thinking server provides a standardized API for multi-step problem solving.

No local setup required - the server runs entirely on Apify's cloud infrastructure.

What Can This Actor Do?

Feature	Description
🔄 Multi-step Reasoning	Process complex problems through numbered thought sequences
✏️ Thought Revisions	Go back and revise any previous thought when you gain new insights
🌿 Branching Paths	Explore alternative approaches without losing your main reasoning chain
💾 Session Persistence	Save and resume thinking sessions across multiple runs
☁️ Cloud Deployment	No installation needed - call via API or MCP protocol

Use Cases for Sequential Thinking

🏗️ Software Architecture Design

Break down system design into components, evaluate trade-offs, and revise based on constraints:

Thought 1: Identify core requirements
Thought 2: Propose initial architecture
Thought 3: (Revision) Adjust for scalability concerns
Thought 4: (Branch) Explore serverless alternative
Thought 5: Compare approaches and recommend

🔬 Research Analysis

Analyze data step-by-step, branch into different hypotheses, and revise conclusions as patterns emerge. Perfect for systematic literature reviews, data exploration, and hypothesis testing.

🐛 Debugging Complex Issues

Trace issues systematically, branch into potential root causes, and eliminate hypotheses one by one. Each thought is recorded, making it easy to backtrack when a hypothesis is disproven.

📋 Strategic Planning

Structure complex business decisions, explore multiple alternatives, and refine strategies based on constraints and feedback.

How to Use Sequential Thinking MCP Server

Step 1: Run Without Input (Test Connection)

Run the Actor without any input to verify it's working and see available capabilities:

$apify call constant_quadruped/sequential-thinking-mcp-server

Step 2: Submit Your First Thought

{
  "thought": "Let me analyze the problem by first identifying the key components...",
  "thoughtNumber": 1,
  "totalThoughts": 5,
  "nextThoughtNeeded": true
}

Step 3: Continue the Sequence

Submit subsequent thoughts, incrementing the thoughtNumber:

{
  "thought": "Based on the components identified, the main challenge is...",
  "thoughtNumber": 2,
  "totalThoughts": 5,
  "nextThoughtNeeded": true
}

Step 4: Revise When Needed

If you need to correct a previous thought:

{
  "thought": "Actually, I need to reconsider - component B should come before A...",
  "thoughtNumber": 3,
  "isRevision": true,
  "revisesThought": 2,
  "nextThoughtNeeded": true
}

Step 5: Branch for Alternatives

Explore a different approach without losing your main chain:

{
  "thought": "Let me explore a microservices alternative...",
  "thoughtNumber": 4,
  "branchFromThought": 2,
  "branchId": "microservices-approach",
  "nextThoughtNeeded": true
}

Input Parameters

Parameter	Type	Default	Description
thought	string	-	Your current thinking step (leave empty for server info)
thoughtNumber	integer	1	Position in sequence (1-1000)
totalThoughts	integer	5	Estimated total thoughts needed (adjustable)
nextThoughtNeeded	boolean	true	Set to false when reasoning is complete
isRevision	boolean	false	Mark as revision of a previous thought
revisesThought	integer	-	Which thought number is being revised
branchFromThought	integer	-	Create a branch from this thought number
branchId	string	-	Identifier for your branch (e.g., "alternative-1")
sessionId	string	-	Resume a previous thinking session
persistSession	boolean	true	Save session to dataset for later retrieval
disableLogging	boolean	false	Disable verbose console output

Output Example

{
  "sessionId": "session_1703123456789_abc123",
  "thoughtNumber": 3,
  "totalThoughts": 5,
  "nextThoughtNeeded": true,
  "branches": ["main", "microservices-approach"],
  "thoughtHistoryLength": 3,
  "status": "success"
}

Integration Guide

Claude Desktop (MCP Protocol)

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "sequential-thinking": {
      "command": "npx",
      "args": ["-y", "@anthropic/apify-mcp-client", "constant_quadruped/sequential-thinking-mcp-server"]
    }
  }
}

JavaScript / TypeScript API

import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_API_TOKEN' });

const run = await client.actor('constant_quadruped/sequential-thinking-mcp-server').call({
  thought: "Analyzing the problem step by step...",
  thoughtNumber: 1,
  totalThoughts: 5,
  nextThoughtNeeded: true
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(items);

Python API

from apify_client import ApifyClient

client = ApifyClient("YOUR_API_TOKEN")

run = client.actor("constant_quadruped/sequential-thinking-mcp-server").call(run_input={
    "thought": "Analyzing the problem step by step...",
    "thoughtNumber": 1,
    "totalThoughts": 5,
    "nextThoughtNeeded": True
})

items = client.dataset(run["defaultDatasetId"]).list_items().items
print(items)

Pricing

This Actor uses pay-per-event pricing for predictable costs:

Event	Cost
Thought processed	1 event charge
Server info request (no thought)	Free

Each thought you submit triggers one charge event. You can process unlimited thoughts - you only pay for what you use.

Session Persistence

All thinking sessions are automatically saved to Apify datasets:

• Resume: Pass sessionId to continue where you left off
• Review: Access the complete thought chain for any session
• Compare: Analyze different branches side by side
• Export: Download complete sessions as JSON

FAQ

Can I use this with any LLM?

Yes! The Sequential Thinking MCP Server works with any AI system that can make HTTP API calls or use the MCP protocol. It's been tested with Claude, GPT-4, and other major models.

How many thoughts can I have in a sequence?

Up to 1,000 thoughts per sequence. For most use cases, 5-20 thoughts are sufficient.

What happens if I don't set nextThoughtNeeded to false?

The sequence remains open. You can continue adding thoughts until you explicitly mark it complete.

Can I have multiple branches?

Yes! You can create as many branches as needed. Each branch is identified by its branchId and tracks back to its origin point via branchFromThought.

Support and Resources

• 📚 Model Context Protocol Specification
• 🔧 MCP Servers Repository
• 📖 Apify Documentation
• 🐛 Report Issues

License

MIT License - Based on @modelcontextprotocol/server-sequential-thinking