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Sequential Thinking MCP Server

by cmarin
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Sequential Thinking MCP Server

An MCP server implementation that provides a tool for dynamic and reflective problem-solving through a structured thinking process.

Features

  • Break down complex problems into manageable steps

  • Revise and refine thoughts as understanding deepens

  • Branch into alternative paths of reasoning

  • Adjust the total number of thoughts dynamically

  • Generate and verify solution hypotheses

Related MCP server: CRASH - Cascaded Reasoning with Adaptive Step Handling

Tool

sequential_thinking

Facilitates a detailed, step-by-step thinking process for problem-solving and analysis.

Inputs:

  • thought (string): The current thinking step

  • nextThoughtNeeded (boolean): Whether another thought step is needed

  • thoughtNumber (integer): Current thought number

  • totalThoughts (integer): Estimated total thoughts needed

  • isRevision (boolean, optional): Whether this revises previous thinking

  • revisesThought (integer, optional): Which thought is being reconsidered

  • branchFromThought (integer, optional): Branching point thought number

  • branchId (string, optional): Branch identifier

  • needsMoreThoughts (boolean, optional): If more thoughts are needed

Usage

The Sequential Thinking tool is designed for:

  • Breaking down complex problems into steps

  • Planning and design with room for revision

  • Analysis that might need course correction

  • Problems where the full scope might not be clear initially

  • Tasks that need to maintain context over multiple steps

  • Situations where irrelevant information needs to be filtered out

Configuration

Usage with Claude Desktop

Add this to your claude_desktop_config.json:

npx

{
  "mcpServers": {
    "sequential-thinking": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-sequential-thinking"
      ]
    }
  }
}

docker

{
  "mcpServers": {
    "sequentialthinking": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "mcp/sequentialthinking"
      ]
    }
  }
}

To disable logging of thought information set env var: DISABLE_THOUGHT_LOGGING to true. Comment

Usage with VS Code

For quick installation, click one of the installation buttons below...

Install with NPX in VS Code Install with NPX in VS Code Insiders

Install with Docker in VS Code Install with Docker in VS Code Insiders

For manual installation, you can configure the MCP server using one of these methods:

Method 1: User Configuration (Recommended) Add the configuration to your user-level MCP configuration file. Open the Command Palette (Ctrl + Shift + P) and run MCP: Open User Configuration. This will open your user mcp.json file where you can add the server configuration.

Method 2: Workspace Configuration Alternatively, you can add the configuration to a file called .vscode/mcp.json in your workspace. This will allow you to share the configuration with others.

For more details about MCP configuration in VS Code, see the official VS Code MCP documentation.

For NPX installation:

{
  "servers": {
    "sequential-thinking": {
      "command": "npx",
      "args": [
        "-y",
        "@modelcontextprotocol/server-sequential-thinking"
      ]
    }
  }
}

For Docker installation:

{
  "servers": {
    "sequential-thinking": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "mcp/sequentialthinking"
      ]
    }
  }
}

Building

Docker:

docker build -t mcp/sequentialthinking -f src/sequentialthinking/Dockerfile .

License

This MCP server is licensed under the MIT License. This means you are free to use, modify, and distribute the software, subject to the terms and conditions of the MIT License. For more details, please see the LICENSE file in the project repository.

Available Tools

1 tool
sequentialthinkingA

A detailed tool for dynamic and reflective problem-solving through thoughts. This tool helps analyze problems through a flexible thinking process that can adapt and evolve. Each thought can build on, question, or revise previous insights as understanding deepens.

When to use this tool:

  • Breaking down complex problems into steps

  • Planning and design with room for revision

  • Analysis that might need course correction

  • Problems where the full scope might not be clear initially

  • Problems that require a multi-step solution

  • Tasks that need to maintain context over multiple steps

  • Situations where irrelevant information needs to be filtered out

Key features:

  • You can adjust total_thoughts up or down as you progress

  • You can question or revise previous thoughts

  • You can add more thoughts even after reaching what seemed like the end

  • You can express uncertainty and explore alternative approaches

  • Not every thought needs to build linearly - you can branch or backtrack

  • Generates a solution hypothesis

  • Verifies the hypothesis based on the Chain of Thought steps

  • Repeats the process until satisfied

  • Provides a correct answer

Parameters explained:

  • thought: Your current thinking step, which can include:

  • Regular analytical steps

  • Revisions of previous thoughts

  • Questions about previous decisions

  • Realizations about needing more analysis

  • Changes in approach

  • Hypothesis generation

  • Hypothesis verification

  • next_thought_needed: True if you need more thinking, even if at what seemed like the end

  • thought_number: Current number in sequence (can go beyond initial total if needed)

  • total_thoughts: Current estimate of thoughts needed (can be adjusted up/down)

  • is_revision: A boolean indicating if this thought revises previous thinking

  • revises_thought: If is_revision is true, which thought number is being reconsidered

  • branch_from_thought: If branching, which thought number is the branching point

  • branch_id: Identifier for the current branch (if any)

  • needs_more_thoughts: If reaching end but realizing more thoughts needed

You should:

  1. Start with an initial estimate of needed thoughts, but be ready to adjust

  2. Feel free to question or revise previous thoughts

  3. Don't hesitate to add more thoughts if needed, even at the "end"

  4. Express uncertainty when present

  5. Mark thoughts that revise previous thinking or branch into new paths

  6. Ignore information that is irrelevant to the current step

  7. Generate a solution hypothesis when appropriate

  8. Verify the hypothesis based on the Chain of Thought steps

  9. Repeat the process until satisfied with the solution

  10. Provide a single, ideally correct answer as the final output

  11. Only set next_thought_needed to false when truly done and a satisfactory answer is reached

ParametersJSON Schema
NameRequiredDescriptionDefault
thoughtYesYour current thinking step
nextThoughtNeededYesWhether another thought step is needed
thoughtNumberYesCurrent thought number
totalThoughtsYesEstimated total thoughts needed
isRevisionNoWhether this revises previous thinking
revisesThoughtNoWhich thought is being reconsidered
branchFromThoughtNoBranching point thought number
branchIdNoBranch identifier
needsMoreThoughtsNoIf more thoughts are needed

TDQS

A4.6/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description fully carries the burden of behavioral disclosure. It details the iterative process including revision, branching, hypothesis generation, verification, and repetition. It explains that thoughts can build, question, or revise previous insights. This level of detail fully informs the agent of the tool's behavior.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections (When to use, Key features, Parameters explained, You should). It is front-loaded with the tool's purpose. However, it is somewhat verbose, particularly the 'You should' list which repeats earlier points (e.g., generating and verifying hypothesis). Trimming redundant points could improve conciseness without losing value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (9 parameters, no output schema, no annotations), the description covers most aspects: purpose, usage guidelines, parameter details, and behavioral process. The only gap is that it does not mention the return value format or output structure. Since there is no output schema, the description could have briefly described what the tool returns (e.g., final answer or thought log) to be fully complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Although schema coverage is 100%, the description adds substantial meaning beyond the schema. For example, the 'thought' parameter is described as including regular analytical steps, revisions, questions, etc. The 'next_thought_needed' and 'total_thoughts' parameters are explained with usage context. This extra information greatly helps the agent understand how to use each parameter effectively.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'dynamic and reflective problem-solving through thoughts.' It specifies that it helps analyze problems through a flexible thinking process. Since there are no sibling tools, differentiation is not needed. The verb 'helps analyze' and the resource 'problems' make it specific and actionable.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides a dedicated 'When to use this tool' section listing scenarios like breaking down complex problems, planning with revision, and analysis needing course correction. It offers clear context but does not explicitly state when to avoid using the tool or mention alternatives. With no sibling tools, the lack of exclusions is acceptable, but the guidance could be more comprehensive.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 1 tool update
    • First observedsequentialthinking
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TDQS

A4.1/5.0

Scored across 1 tool

Disambiguation5/5

With only one tool, there is no possibility of ambiguity or overlap between tools. The tool 'sequentialthinking' has a clearly distinct purpose focused on dynamic problem-solving through iterative thought processes.

Naming Consistency5/5

Since there is only one tool, naming consistency is inherently perfect. The tool name 'sequentialthinking' follows a clear, descriptive pattern that accurately reflects its function without any conflicting naming conventions.

Tool Count2/5

A single tool is too few for a server named 'Sequential Thinking MCP Server', which implies a broader scope for problem-solving assistance. While the tool is detailed, the server feels thin and limited, lacking complementary tools for different aspects of thinking or analysis.

Completeness2/5

The tool surface is severely incomplete for the implied domain of sequential thinking. There are obvious gaps, such as no tools for summarizing thoughts, managing thought branches, exporting results, or integrating with other problem-solving methods, leaving agents with a single, monolithic tool that may not cover all needed operations.

Maintenance

ActivityInactive
ResponsivenessNo issues

Resources

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