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Sequentialthinking

Lightweight Sequential Thinking MCP Server

Unclaimed MIT last commit 10 months ago devtools
51Fair

Scored 2 days ago · breakdown

About Sequentialthinking

Sequentialthinking is an MCP server published by bpradana in the Developer Tools category: lightweight Sequential Thinking MCP Server. It has been installed 0 times through Conduid.

The repository has 2 stars and 0 forks, with the last commit 10 months ago. Six months or more without a commit doesn't mean the server is broken, but check the open issues (0) before depending on it in production.

Install

Install
npx sequentialthinking

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

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Releases

v1.2.0v1.2.0 · 30 Oct 2025
v1.1.1v1.1.1 · 30 Oct 2025
v1.1.0v1.1.0 · 30 Oct 2025
v1.0.0v1.0.0 · 29 Oct 2025

README

Sequential Thinking MCP Server

Go Report Card Release Docker Pulls

Sequential Thinking is a Model Context Protocol (MCP) server that operationalizes deliberate reasoning. It lets MCP clients create structured thinking sessions, capture sequential steps (analysis → hypothesis → verification → conclusion), branch into alternative lines of thought, and export or audit the full chain of reasoning.

Overview

  • Written in Go 1.24 with the MCP Go SDK as its only direct dependency.
  • Ships an in-memory session store, branch management, logical validation, and reasoning-quality heuristics.
  • Provides eleven MCP tools, resource endpoints for sessions and templates, and three reasoning prompts.
  • Supports stdio (default) and streamable HTTP transports, plus a minimal scratch-based Docker image published as bpradana/sequentialthinking.
  • Backed by unit tests across handlers and an end-to-end MCP integration test.

Quick Start

Prerequisites

  • Go 1.24 or newer
  • Git (or another way to obtain the source)

Build and Run (stdio transport)

go mod download
go build -o sequentialthinking ./cmd/sequentialthinking
./sequentialthinking

The binary listens on stdio and is ready to be launched by MCP-aware clients.

Run as HTTP server

./sequentialthinking -http :8080

The -http flag enables streamable HTTP transport on the supplied address.

Docker (prebuilt image)

docker pull bpradana/sequentialthinking
docker run --rm -i bpradana/sequentialthinking

-i keeps stdin open so MCP clients can speak stdio with the containerised server.

Docker (build locally)

docker build -t sequentialthinking .
docker run --rm sequentialthinking

The multi-stage Dockerfile builds a static binary and runs it from a scratch image (UID 65532).

Integrating with MCP Clients

  • MCP Inspector
    npm install -g @modelcontextprotocol/inspector
    mcp-inspector ./sequentialthinking
    
  • Claude Desktop via Docker (macOS path shown)
    {
      "mcpServers": {
        "sequentialthinking": {
          "command": "docker",
          "args": [
            "run",
            "--rm",
            "-i",
            "bpradana/sequentialthinking"
          ]
        }
      }
    }
    
    Pull the image first with docker pull bpradana/sequentialthinking. Claude keeps the container alive while the MCP session is active and re-creates it on demand.

Kick off a Template Session

Once connected (Inspector, Claude, or another MCP client), call the sequentialthinking.start_from_template tool to seed a new session:

{
  "name": "sequentialthinking.start_from_template",
  "arguments": {
    "template": "scientific-method",
    "problem": "Why did the nightly build fail?",
    "context": {
      "repo": "widgets-service",
      "last_green_commit": "abc1234"
    }
  }
}

The server responds with the new session_id, populated steps from the requested template, and suggested next actions. Subsequent calls can extend or branch the reasoning as usual.

Tooling Surface

Tool Purpose Notable Arguments
start_thinking Create a new session with initial analysis and suggested next steps. problem, optional context, optional tags, optional template
add_step Append a reasoning step to the main flow or a branch. session_id, optional branch_id, step_type, step_content
update_step Edit an existing step’s content, type, or metadata. session_id, step_number, optional fields to update
review_thinking Retrieve the full chain, connections, patterns, and summary. session_id, optional format (linear, tree, summary)
branch_thinking Fork the reasoning path from an existing step and seed a branch. session_id, from_step, alternative_reasoning
merge_insights Synthesize conclusions across multiple branches. session_id, branch_ids
validate_logic Flag logical issues and describe strengths. session_id, optional range_start, range_end
export_session Export a session as markdown, JSON, or plain text. session_id, optional include_branches, format
list_sessions Filterable session directory with quality scores. optional status, tags, limit
delete_session Remove a session. session_id
get_metrics Aggregate reasoning metrics across sessions. optional time_range (day, week, month, all)

Resources and Prompts

  • Resources

    • thinking://session/{session_id} – JSON snapshot of a single session.
    • thinking://sessions/list – JSON list of all sessions in memory.
    • thinking://template/{template_type} – JSON representation of thinking frameworks (scientific-method, five-whys, root-cause-analysis, decision-matrix, swot-analysis, pros-cons, first-principles, fishbone, pareto-analysis).
  • Prompts

    • problem_breakdown – Structures complex problem decomposition.
    • critical_analysis – Guides evaluation of claims and evidence.
    • synthesis_prompt – Helps combine multiple insights into coherent output.

Reasoning Model Highlights

  • Step Types: analysis, hypothesis, verification, conclusion. Parent references and connection tracking let clients build reasoning graphs.
  • Branching: Any step can branch into alternative reasoning paths. Branch steps are numbered locally and remain tied to the originating step.
  • Quality Scoring: Heuristic combines step-type diversity (30%), connection density (30%), and depth (40%). Scores stay in [0,1] and recompute after each update.
  • Logical Validation: Detects unsupported conclusions and unverified hypotheses. Returns structured issues, suggestions, strength highlights, and an overall validity score.
  • Pattern Detection: Identifies recurring reasoning patterns (hypothesis-verification, progressive refinement, branching synthesis) for analytics.
  • Exports: Markdown, JSON, and text exporters include metadata, connections, branches, and suggested filenames.

Operational Notes

  • Storage: In-memory (internal/thinking.MemoryStore) guarded by RW mutexes. Sessions are ephemeral and cleared on restart.
  • Concurrency: Reads return deep clones to prevent external mutation; writes update timestamps, current step counters, and quality scores.
  • Logging: Uses log/slog for initialization messages and mcp.LoggingTransport for stdio diagnostics.
  • Completion Support: Autocomplete handler surfaces session IDs and template names for MCP completion requests.

Development Workflow

# Run unit and integration tests
go test ./...

# Format and lint
go fmt ./...
golangci-lint run    # optional, if installed

Project Layout

cmd/sequentialthinking   CLI entry point and flag parsing
internal/server          MCP server assembly, transports, integration tests
internal/handlers        Tool, resource, prompt handlers and helper logic
internal/thinking        Core domain types, in-memory store, exports, metrics

Release Tips

  • Build with CGO_ENABLED=0 for static binaries (already used in Dockerfile).
  • Bump the version in internal/server.New when publishing server changes.
  • Use the provided Dockerfile as the canonical container build.

License

MIT License (use repository root LICENSE if present).

README mirrored from the source repository 2 days ago. The original is authoritative.

Questions

About Sequentialthinking

How do I install Sequentialthinking?

Run npx sequentialthinking, then add the server to your MCP client's configuration. Conduid has recorded 0 installs, so the command is known to work with current clients.

Is Sequentialthinking safe to use with an AI agent?

Its trust score is 51 out of 100 (fair). It passes 0 of 1 static security checks; the failures are listed above. It has no ConduID identity yet, so agent calls to it are not receipted.

Is Sequentialthinking still maintained?

The last commit was 10 months ago, with 0 open issues. That's long enough that you should check whether the maintainer is responding to issues before depending on it.