Skip to main content
Glama
mustafaskyer

Sequential Thinking MCP Server

by mustafaskyer

sequentialthinking

Break down complex problems into manageable steps with the ability to revise, branch, or adjust thoughts dynamically, ensuring a thorough and flexible analysis.

Instructions

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

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
thoughtYesYour current thinking step
nextThoughtNeededYesWhether another thought step is needed
thoughtNumberYesCurrent thought number (numeric value, e.g., 1, 2, 3)
totalThoughtsYesEstimated total thoughts needed (numeric value, e.g., 5, 10)
isRevisionNoWhether this revises previous thinking
revisesThoughtNoWhich thought is being reconsidered
branchFromThoughtNoBranching point thought number
branchIdNoBranch identifier
needsMoreThoughtsNoIf more thoughts are needed

Implementation Reference

  • The processThought method is the main handler that processes a sequential thinking step. It validates input via validateThoughtData, stores the thought in history, handles branching, logs the formatted thought, and returns structured JSON output including thoughtNumber, totalThoughts, nextThoughtNeeded, branches, and thoughtHistoryLength.
    public processThought(input: unknown): {
      content: Array<{ type: string; text: string }>
      isError?: boolean
    } {
      try {
        const validatedInput = this.validateThoughtData(input)
    
        if (validatedInput.thoughtNumber > validatedInput.totalThoughts) {
          validatedInput.totalThoughts = validatedInput.thoughtNumber
        }
    
        this.thoughtHistory.push(validatedInput)
    
        if (validatedInput.branchFromThought && validatedInput.branchId) {
          if (!this.branches[validatedInput.branchId]) {
            this.branches[validatedInput.branchId] = []
          }
          this.branches[validatedInput.branchId].push(validatedInput)
        }
    
        if (!this.disableThoughtLogging) {
          const formattedThought = this.formatThought(validatedInput)
          console.error(formattedThought)
        }
    
        return {
          content: [
            {
              type: 'text',
              text: JSON.stringify(
                {
                  thoughtNumber: validatedInput.thoughtNumber,
                  totalThoughts: validatedInput.totalThoughts,
                  nextThoughtNeeded: validatedInput.nextThoughtNeeded,
                  branches: Object.keys(this.branches),
                  thoughtHistoryLength: this.thoughtHistory.length,
                },
                null,
                2,
              ),
            },
          ],
        }
      } catch (error) {
        return {
          content: [
            {
              type: 'text',
              text: JSON.stringify(
                {
                  error: error instanceof Error ? error.message : String(error),
                  status: 'failed',
                },
                null,
                2,
              ),
            },
          ],
          isError: true,
        }
      }
    }
  • The ThoughtData interface defines the input schema with fields: thought, thoughtNumber, totalThoughts, isRevision, revisesThought, branchFromThought, branchId, needsMoreThoughts, and nextThoughtNeeded.
    interface ThoughtData {
      thought: string
      thoughtNumber: number
      totalThoughts: number
      isRevision?: boolean
      revisesThought?: number
      branchFromThought?: number
      branchId?: string
      needsMoreThoughts?: boolean
      nextThoughtNeeded: boolean
    }
    
    class SequentialThinkingServer {
      private thoughtHistory: ThoughtData[] = []
      private branches: Record<string, ThoughtData[]> = {}
      private disableThoughtLogging: boolean
    
      constructor() {
        this.disableThoughtLogging =
          (process.env.DISABLE_THOUGHT_LOGGING || '').toLowerCase() === 'true'
      }
    
      private validateThoughtData(input: unknown): ThoughtData {
        const data = input as Record<string, unknown>
    
        if (!data.thought || typeof data.thought !== 'string') {
          throw new Error('Invalid thought: must be a string')
        }
        if (!data.thoughtNumber || typeof data.thoughtNumber !== 'number') {
          throw new Error('Invalid thoughtNumber: must be a number')
        }
        if (!data.totalThoughts || typeof data.totalThoughts !== 'number') {
          throw new Error('Invalid totalThoughts: must be a number')
        }
        if (typeof data.nextThoughtNeeded !== 'boolean') {
          throw new Error('Invalid nextThoughtNeeded: must be a boolean')
        }
    
        return {
          thought: data.thought,
          thoughtNumber: data.thoughtNumber,
          totalThoughts: data.totalThoughts,
          nextThoughtNeeded: data.nextThoughtNeeded,
          isRevision: data.isRevision as boolean | undefined,
          revisesThought: data.revisesThought as number | undefined,
          branchFromThought: data.branchFromThought as number | undefined,
          branchId: data.branchId as string | undefined,
          needsMoreThoughts: data.needsMoreThoughts as boolean | undefined,
        }
      }
  • The SEQUENTIAL_THINKING_TOOL constant defines the tool's name ('sequentialthinking'), description, and JSON Schema inputSchema specifying required fields (thought, nextThoughtNeeded, thoughtNumber, totalThoughts) and optional fields.
    const SEQUENTIAL_THINKING_TOOL: Tool = {
      name: 'sequentialthinking',
      description: `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`,
      inputSchema: {
        type: 'object',
        properties: {
          thought: {
            type: 'string',
            description: 'Your current thinking step',
          },
          nextThoughtNeeded: {
            type: 'boolean',
            description: 'Whether another thought step is needed',
          },
          thoughtNumber: {
            type: 'integer',
            description: 'Current thought number (numeric value, e.g., 1, 2, 3)',
            minimum: 1,
          },
          totalThoughts: {
            type: 'integer',
            description:
              'Estimated total thoughts needed (numeric value, e.g., 5, 10)',
            minimum: 1,
          },
          isRevision: {
            type: 'boolean',
            description: 'Whether this revises previous thinking',
          },
          revisesThought: {
            type: 'integer',
            description: 'Which thought is being reconsidered',
            minimum: 1,
          },
          branchFromThought: {
            type: 'integer',
            description: 'Branching point thought number',
            minimum: 1,
          },
          branchId: {
            type: 'string',
            description: 'Branch identifier',
          },
          needsMoreThoughts: {
            type: 'boolean',
            description: 'If more thoughts are needed',
          },
        },
        required: [
          'thought',
          'nextThoughtNeeded',
          'thoughtNumber',
          'totalThoughts',
        ],
      },
  • index.ts:288-289 (registration)
    The ListToolsRequestSchema handler registers the 'sequentialthinking' tool by returning SEQUENTIAL_THINKING_TOOL in the tools array.
    server.setRequestHandler(ListToolsRequestSchema, async () => ({
      tools: [SEQUENTIAL_THINKING_TOOL],
  • index.ts:292-295 (registration)
    The CallToolRequestSchema handler routes incoming tool calls. When request.params.name equals 'sequentialthinking', it delegates to thinkingServer.processThought with the arguments.
    server.setRequestHandler(CallToolRequestSchema, async (request) => {
      if (request.params.name === 'sequentialthinking') {
        return thinkingServer.processThought(request.params.arguments)
      }
Behavior5/5

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

With no annotations provided, the description fully discloses behavioral traits: ability to revise, branch, adjust thought counts, express uncertainty, and the iterative hypothesis-verification loop. It also explains how parameters like 'nextThoughtNeeded' and 'totalThoughts' can adjust dynamically.

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

Conciseness5/5

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

The description is long but well-structured: introduction, when-to-use, key features, parameter explanations, and a numbered list of instructions. It is front-loaded with purpose and each sentence contributes meaningful context. No redundancy or fluff.

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

Completeness5/5

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

Given the complexity (9 parameters, 4 required, no output schema), the description is thorough: it explains the iterative process, parameter behavior, and even provides a 'you should' list covering steps from start to final answer. It adequately covers what the tool does and how to use it in all aspects.

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

Parameters4/5

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

Schema coverage is 100%, so baseline is 3. The description adds significant value with its 'Parameters explained' section, detailing the types of content for 'thought' and clarifying the role of each parameter (e.g., 'branch_id' for branching). This enhances understanding beyond the schema alone.

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 is for dynamic and reflective problem-solving through thoughts, with explicit use cases like breaking down complex problems, planning, and multi-step analysis. It distinguishes itself from any potential siblings by describing its unique adaptive process.

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

Usage Guidelines5/5

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 with specific scenarios (e.g., problems where full scope isn't clear, situations requiring course correction). This gives clear guidance on appropriate usage, though no alternatives are mentioned due to lack of siblings.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/mustafaskyer/SequentialThinkingMCPServer'

If you have feedback or need assistance with the MCP directory API, please join our Discord server