Sequential Thinking MCP Server

Created By

zannyonear1h18 months ago

Content

Sequential Thinking MCP Server

A Model Context Protocol (MCP) server focused on structured sequential thinking capabilities, designed to integrate with Cline's Memory Bank. This server helps break down complex problems into structured sequential steps, track reasoning chains, and store thinking patterns.

Features

Create and manage sequential thinking chains for problem-solving
Track chains of thought with validation at each step
Store and retrieve reasoning patterns
Analyze the quality of reasoning processes
Visualize thinking pathways
Seamlessly integrate with the Memory Bank system

Architecture

The server consists of the following core components:

Sequential Thinking Engine: Manages thinking chains, steps, and reasoning validation
Memory Bank Connector: Integrates with Cline's Memory Bank
Tag Manager: Implements a comprehensive tagging system
Visualization Generator: Creates visual representations of thinking chains
Utilities: File storage, thinking validation, and other helpers

Available Tools

The server provides the following MCP tools:

create_thinking_chain

Create a new sequential thinking process with specified parameters.

Input: problem description, thinking type, context
Output: chain_id and initial structure

add_thinking_step

Add a step to an existing thinking chain.

Input: chain_id, step description, reasoning, evidence
Output: updated step information

validate_step

Validate logical connections between steps.

Input: chain_id, step_id
Output: validation results, potential issues

get_chain

Retrieve a complete thinking chain.

Input: chain_id
Output: full chain with all steps

generate_visualization

Create visual representation of a thinking chain.

Input: chain_id, format (mermaid, json, text)
Output: visualization code/data

save_to_memory

Save a thinking chain to Memory Bank.

Input: chain_id, memory_name, tags
Output: confirmation and memory_id

load_from_memory

Load a thinking chain from Memory Bank.

Input: memory_id or search parameters
Output: complete chain

search_related_thinking

Find related thinking chains based on parameters.

Input: keywords, tags, thinking_type
Output: list of relevant chains

apply_template

Apply a reasoning template to current thinking.

Input: template_name, problem_context
Output: pre-structured thinking chain

Thinking Types

The server supports various thinking types, each with specific patterns and structures:

Analytical - Break down, analyze, synthesize
Creative - Diverge, explore, converge
Critical - Question, evaluate, conclude
Systems - Map, analyze, model
First-Principles - Identify, break down, reassemble
Divergent - Generate alternatives, explore
Convergent - Analyze, evaluate, select
Inductive - Observe, pattern, hypothesize
Deductive - Premise, logic, conclusion

Templates

The server includes ready-to-use reasoning templates to jumpstart the thinking process:

First Principles Analysis - Break down a complex problem into its fundamental principles
Systems Thinking Analysis - Analyze complex systems holistically

Installation

Ensure Node.js v14+ is installed
Clone the repository
Install dependencies:
```
npm install
```

Usage

Start the server:
```
node index.js
```
The server will be available as an MCP server that you can connect to via Claude/Cline

Memory Bank Integration

This server is designed to integrate with Cline's Memory Bank, allowing:

Reading from Memory Bank files (projectbrief.md, activeContext.md, etc.)
Storing complete thinking chains as structured memories
Updating activeContext.md with reasoning outcomes
Creating links between reasoning and Memory Bank sections

Example Tool Usage

// Example: Create a new thinking chain
{
  "problem": "How to improve user engagement on our platform",
  "thinking_type": "systems",
  "context": "Our user engagement metrics have decreased by 15% over the past quarter"
}

// Example: Add a thinking step
{
  "chain_id": "3a7e4fc0-5c1d-4b9f-9d1a-8b5e7c5a9d3e",
  "description": "Identify key components of the engagement system",
  "reasoning": "User engagement consists of several interconnected components including onboarding, core user actions, notification systems, and retention mechanisms.",
  "evidence": "Analysis of our user journey maps and analytics data",
  "confidence": 0.8
}

// Example: Generate a visualization
{
  "chain_id": "3a7e4fc0-5c1d-4b9f-9d1a-8b5e7c5a9d3e",
  "format": "mermaid",
  "options": {
    "showValidation": true,
    "showConfidence": true
  }
}