MCP Sequentialthinking Tools

What is MCP Sequentialthinking Tools about?

MCP Sequentialthinking Tools extends the MCP Sequential Thinking Server to guide tool usage during problem‑solving. For each thought step it suggests the most appropriate MCP tools, scores each suggestion, explains the reasoning, and can propose alternatives.

How to use MCP Sequentialthinking Tools?

1. Configure the server in your MCP client (see the serverConfig section).
2. Call the sequentialthinking_tools tool, supplying the current thought, step information, and a list of available MCP tools.
3. The server returns a structured response that includes recommended_tools with confidence, rationale, priority, and suggested input parameters.
4. Execute the recommended tools, feed any new results back into the next thought, and repeat until next_thought_needed is false.

Key features of MCP Sequentialthinking Tools

• Dynamic, reflective sequential thinking workflow
• LLM‑driven tool recommendations with confidence scoring (0‑1)
• Detailed rationale and priority ordering for each suggestion
• Support for branching, revisions, and alternative tool paths
• Configurable memory management (MAX_HISTORY_SIZE)
• Automatic trimming and manual cleanup of thought history
• Single MCP tool interface (sequentialthinking_tools) with rich parameters

Use cases of MCP Sequentialthinking Tools

• Complex research tasks where multiple tools (search, code execution, data retrieval) must be orchestrated
• Software development assistance that iteratively refines code snippets using linters, test runners, and documentation search tools
• Knowledge‑base construction that alternates between gathering information and synthesizing summaries
• Any multi‑step problem‑solving scenario where tool selection impacts efficiency and accuracy

FAQ from the MCP Sequentialthinking Tools

Q: Do I need to list all available MCP tools each request? A: Yes. Provide the available_mcp_tools array so the server can evaluate suitability.

Q: How is the confidence score calculated? A: The underlying LLM assesses the match between the step’s intent and each tool’s description, normalising the result to a 0‑1 range.

Q: Can I limit the number of thoughts stored in memory? A: Set the MAX_HISTORY_SIZE environment variable; the server will automatically trim older thoughts.

Q: What if I want to explore a different approach? A: Use branch_from_thought and branch_id to create a new branch without discarding the original line of reasoning.

Q: Is there a way to clear history manually? A: The server exposes a cleanup method (e.g., a dedicated MCP tool or API endpoint) to purge stored thoughts.

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:

1. LLM provides available MCP tools to the sequential thinking server
2. LLM analyzes each thought step and recommends appropriate tools
3. Server tracks recommendations, maintains context, and manages memory
4. 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:

{
	"thought": "Initial research step to understand what universal reactivity means in Svelte 5",
	"current_step": {
		"step_description": "Gather initial information about Svelte 5's universal reactivity",
		"expected_outcome": "Clear understanding of universal reactivity concept",
		"recommended_tools": [
			{
				"tool_name": "search_docs",
				"confidence": 0.9,
				"rationale": "Search Svelte documentation for official information",
				"priority": 1
			},
			{
				"tool_name": "tavily_search",
				"confidence": 0.8,
				"rationale": "Get additional context from reliable sources",
				"priority": 2
			}
		],
		"next_step_conditions": [
			"Verify information accuracy",
			"Look for implementation details"
		]
	},
	"thought_number": 1,
	"total_thoughts": 5,
	"next_thought_needed": true
}

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:

{
	"mcpServers": {
		"mcp-sequentialthinking-tools": {
			"command": "npx",
			"args": ["-y", "mcp-sequentialthinking-tools"],
			"env": {
				"MAX_HISTORY_SIZE": "1000"
			}
		}
	}
}

Claude Desktop with WSL Configuration

For WSL environments, add this to your Claude Desktop configuration:

{
	"mcpServers": {
		"mcp-sequentialthinking-tools": {
			"command": "wsl.exe",
			"args": [
				"bash",
				"-c",
				"MAX_HISTORY_SIZE=1000 source ~/.nvm/nvm.sh && /home/username/.nvm/versions/node/v20.12.1/bin/npx mcp-sequentialthinking-tools"
			]
		}
	}
}

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 step
• next_thought_needed (boolean, required): Whether another thought step is needed
• thought_number (integer, required): Current thought number
• total_thoughts (integer, required): Estimated total thoughts needed
• is_revision (boolean, optional): Whether this revises previous thinking
• revises_thought (integer, optional): Which thought is being reconsidered
• branch_from_thought (integer, optional): Branching point thought number
• branch_id (string, optional): Branch identifier
• needs_more_thoughts (boolean, optional): If more thoughts are needed
• current_step (object, optional): Current step recommendation with:
  • step_description: What needs to be done
  • recommended_tools: Array of tool recommendations with confidence scores
  • expected_outcome: What to expect from this step
  • next_step_conditions: Conditions for next step
• previous_steps (array, optional): Steps already recommended
• remaining_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:

{
  "mcpServers": {
    "mcp-sequentialthinking-tools": {
      "command": "npx",
      "args": ["-y", "mcp-sequentialthinking-tools"],
      "env": {
        "MAX_HISTORY_SIZE": "500"
      }
    }
  }
}

Or for local development:

MAX_HISTORY_SIZE=2000 npx mcp-sequentialthinking-tools

Development

Setup

1. Clone the repository
2. Install dependencies:

pnpm install

3. Build the project:

pnpm build

4. Run in development mode:

pnpm dev

Publishing

The project uses changesets for version management. To publish:

1. Create a changeset:

pnpm changeset

2. Version the package:

pnpm changeset version

3. Publish to npm:

pnpm release

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