The mcp-sequentialthinking-tools
server is a dynamic problem-solving assistant that guides users through complex problems by breaking them down into manageable steps and recommending appropriate tools.
Key capabilities:
Sequential Analysis: Breaks down complex problems into manageable steps
Tool Recommendations: Provides tool suggestions with confidence scores (0-1), rationales, and execution priority
Contextual Awareness: Tracks progress, previous steps, and remaining steps
Flexible Thinking: Supports branching, revision, and adjustment of thought processes
Intelligent Assistance: Suggests input parameters for tools and alternative approaches
Hypothesis Management: Generates and verifies solution hypotheses
Interactive Configuration: Requires initialization with available tools for tailored recommendations
The server provides examples of how it can be used to gather information about Svelte 5's universal reactivity as part of its problem-solving approach
mcp-sequentialthinking-tools
An adaptation of the MCP Sequential Thinking Server designed to guide tool usage in problem-solving. This server helps break down complex problems into manageable steps and provides recommendations for which MCP tools would be most effective at each stage.
A Model Context Protocol (MCP) server that combines sequential thinking with intelligent tool suggestions. For each step in the problem-solving process, it provides confidence-scored recommendations for which tools to use, along with rationale for why each tool would be appropriate.
Features
- 🤔 Dynamic and reflective problem-solving through sequential thoughts
- 🔄 Flexible thinking process that adapts and evolves
- 🌳 Support for branching and revision of thoughts
- 🛠️ LLM-driven intelligent tool recommendations for each step
- 📊 Confidence scoring for tool suggestions
- 🔍 Detailed rationale for tool recommendations
- 📝 Step tracking with expected outcomes
- 🔄 Progress monitoring with previous and remaining steps
- 🎯 Alternative tool suggestions for each step
- 🧠 Memory management with configurable history limits
- 🗑️ Manual history cleanup capabilities
How It Works
This server facilitates sequential thinking with MCP tool coordination. The LLM analyzes available tools and their descriptions to make intelligent recommendations, which are then tracked and organized by this server.
The workflow:
- LLM provides available MCP tools to the sequential thinking server
- LLM analyzes each thought step and recommends appropriate tools
- Server tracks recommendations, maintains context, and manages memory
- LLM executes recommended tools and continues the thinking process
Each recommendation includes:
- A confidence score (0-1) indicating how well the tool matches the need
- A clear rationale explaining why the tool would be helpful
- A priority level to suggest tool execution order
- Suggested input parameters for the tool
- Alternative tools that could also be used
The server works with any MCP tools available in your environment and automatically manages memory to prevent unbounded growth.
Example Usage
Here's an example of how the server guides tool usage:
The server tracks your progress and supports:
- Creating branches to explore different approaches
- Revising previous thoughts with new information
- Maintaining context across multiple steps
- Suggesting next steps based on current findings
Configuration
This server requires configuration through your MCP client. Here are examples for different environments:
Cline Configuration
Add this to your Cline MCP settings:
Claude Desktop with WSL Configuration
For WSL environments, add this to your Claude Desktop configuration:
API
The server implements a single MCP tool with configurable parameters:
sequentialthinking_tools
A tool for dynamic and reflective problem-solving through thoughts, with intelligent tool recommendations.
Parameters:
available_mcp_tools
(array, required): Array of MCP tool names available for use (e.g., ["mcp-omnisearch", "mcp-turso-cloud"])thought
(string, required): Your current thinking stepnext_thought_needed
(boolean, required): Whether another thought step is neededthought_number
(integer, required): Current thought numbertotal_thoughts
(integer, required): Estimated total thoughts neededis_revision
(boolean, optional): Whether this revises previous thinkingrevises_thought
(integer, optional): Which thought is being reconsideredbranch_from_thought
(integer, optional): Branching point thought numberbranch_id
(string, optional): Branch identifierneeds_more_thoughts
(boolean, optional): If more thoughts are neededcurrent_step
(object, optional): Current step recommendation with:step_description
: What needs to be donerecommended_tools
: Array of tool recommendations with confidence scoresexpected_outcome
: What to expect from this stepnext_step_conditions
: Conditions for next step
previous_steps
(array, optional): Steps already recommendedremaining_steps
(array, optional): High-level descriptions of upcoming steps
Memory Management
The server includes built-in memory management to prevent unbounded growth:
- History Limit: Configurable maximum number of thoughts to retain (default: 1000)
- Automatic Trimming: History automatically trims when limit is exceeded
- Manual Cleanup: Server provides methods to clear history when needed
Configuring History Size
You can configure the history size by setting the MAX_HISTORY_SIZE
environment variable:
Or for local development:
Development
Setup
- Clone the repository
- Install dependencies:
- Build the project:
- Run in development mode:
Publishing
The project uses changesets for version management. To publish:
- Create a changeset:
- Version the package:
- Publish to npm:
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
License
MIT License - see the LICENSE file for details.
Acknowledgments
- Built on the Model Context Protocol
- Adapted from the MCP Sequential Thinking Server
An adaptation of the MCP Sequential Thinking Server designed to guide tool usage in problem-solving. This server helps break down complex problems into manageable steps and provides recommendations for which MCP tools would be most effective at each stage.
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