Enables execution of JavaScript code within literate programming notebooks with isolated execution environments and package management
Runs JavaScript/TypeScript code in notebook environments using Node.js runtime with package.json support
Provides caching capabilities through Redis cluster integration with connection pooling and LRU eviction for high-traffic API scenarios
Supports TypeScript code execution in interactive notebooks with full dependency management and output capture
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Thoughtboxuse the five-whys model to analyze why our deployment failed"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Thoughtbox
A reasoning ledger for AI agents. Thoughtbox is an MCP server that provides structured reasoning tools, enabling agents to think step-by-step, branch into alternative explorations, revise earlier conclusions, and maintain a persistent record of their cognitive process.
Unlike ephemeral chain-of-thought prompting, Thoughtbox creates a durable reasoning chain — a ledger of thoughts that can be visualized, exported, and analyzed. Each thought is a node in a graph structure supporting forward thinking, backward planning, branching explorations, and mid-course revisions.
Observatory UI showing a reasoning session with 14 thoughts and a branch exploration (purple nodes 13-14) forking from thought 5.
Core Concepts
The Reasoning Ledger
Thoughtbox treats reasoning as data, not just process. Every thought is:
Numbered: Logical position in the reasoning chain (supports non-sequential addition)
Timestamped: When the thought was recorded
Linked: Connected to previous thoughts, branch origins, or revised thoughts
Persistent: Stored in sessions that survive across conversations
Exportable: Full reasoning chains can be exported as JSON or Markdown
This creates an auditable trail of how conclusions were reached — invaluable for debugging agent behavior, understanding decision-making, and improving reasoning strategies.
Thinking Patterns
Thoughtbox supports multiple reasoning strategies out of the box:
Pattern | Description | Use Case |
Forward Thinking | Sequential 1→2→3→N progression | Exploration, discovery, open-ended analysis |
Backward Thinking | Start at goal (N), work back to start (1) | Planning, system design, working from known goals |
Branching | Fork into parallel explorations (A, B, C...) | Comparing alternatives, A/B scenarios |
Revision | Update earlier thoughts with new information | Error correction, refined understanding |
Interleaved | Alternate reasoning with tool actions | Tool-oriented tasks, adaptive execution |
See the Patterns Cookbook for comprehensive examples.
Features
1. Thoughtbox Tool — Structured Reasoning
The core tool for step-by-step thinking with full graph capabilities.
Parameters:
thought(string): The current thinking stepthoughtNumber(integer): Logical position in the chaintotalThoughts(integer): Estimated total (adjustable)nextThoughtNeeded(boolean): Continue thinking?branchFromThought(integer): Fork point for branchingbranchId(string): Branch identifierisRevision(boolean): Marks revision of earlier thoughtrevisesThought(integer): Which thought is being revised
2. Observatory — Real-Time Visualization
A built-in web UI for watching reasoning unfold in real-time.
Features:
Live Graph: Watch thoughts appear as they're added
Snake Layout: Compact left-to-right flow with row wrapping
Hierarchical Branches: Branches collapse into clickable stub nodes (A, B, C...)
Navigation: Click stubs to explore branches, back button to return
Detail Panel: Click any node to view full thought content
Multi-Session: Switch between active reasoning sessions
Access: The Observatory is available at http://localhost:1729 when the server is running.
3. Mental Models — Reasoning Frameworks
15 structured mental models that provide process scaffolds for different problem types.
Available Models:
rubber-duck— Explain to clarify thinkingfive-whys— Root cause analysispre-mortem— Anticipate failuressteelmanning— Strengthen opposing argumentsfermi-estimation— Order-of-magnitude reasoningtrade-off-matrix— Multi-criteria decisionsdecomposition— Break down complexityinversion— Solve by avoiding failureAnd 7 more...
Operations:
get_model— Retrieve a specific model's promptlist_models— List all models (filter by tag)list_tags— Available categories (debugging, planning, decision-making, etc.)
4. Notebook — Literate Programming
Interactive notebooks combining documentation with executable JavaScript/TypeScript.
Features:
Isolated execution environments per notebook
Full package.json support with dependency installation
Sequential Feynman template for deep learning workflows
Export to
.src.mdformat
Operations: create, add_cell, run_cell, export, list, load, update_cell
Installation
Quick Start
MCP Client Configuration
Claude Code
Add to your ~/.claude/settings.json or project .claude/settings.json:
Cline / VS Code
Add to your MCP settings or .vscode/mcp.json:
Usage Examples
Forward Thinking — Problem Analysis
Backward Thinking — System Design
Branching — Comparing Alternatives
Environment Variables
DISABLE_THOUGHT_LOGGING=true— Suppress thought logging to stderr
Development
Architecture
License
MIT License — free to use, modify, and distribute.