Sponsored by Deepsite.site

🚦 Branch-Thinking MCP Tool

Created By
ssdeanx8 months ago
Branch-Thinking MCP Tool A TypeScript-powered MCP server for managing parallel branches of thought, semantic cross-references, and persistent tasks. Features dynamic scoring, AI-generated insights, batch operations, and visual graph navigation for advanced agentic workflows.
Content

🚦 Branch-Thinking MCP Tool

Changelog Issues Node.js TypeScript MCP MIT License @dagrejs/graphlib ml-kmeans lru-cache @xenova/transformers @modelcontextprotocol/sdk chalk Mermaid pnpm

What’s New (2025-04):

  • Advanced visualization: clustering (k-means/degree), centrality overlays, edge bundling, and agentic overlays for tasks and priorities
  • Agentic cache & prefetch: LRU+TTL caches for embeddings, summaries, analytics, and proactive agent cache warming
  • Enhanced analytics: real-time, multi-branch, and focusNode support; agent-optimized metadata
  • Upgraded documentation and onboarding for agents and users

Features

  • 🌳 Branch Management: Create, focus, and navigate multiple lines of thought
  • 🔗 Cross-References: Link related thoughts across branches (typed, scored)
  • 💡 AI Insights: Automatic insight and summary generation
  • 🧠 Semantic Search: Find related thoughts using embeddings
  • 📊 Advanced Visualization:
    • Node clustering (k-means/degree)
    • Centrality overlays (closeness, betweenness)
    • Edge bundling
    • Task overlays (status, priority, next-action)
    • Agentic overlays and metadata for all nodes/edges
    • FocusNode and multi-branch visualization
  • Agentic Cache & Prefetch:
    • LRU+TTL caches for embeddings, summaries, analytics
    • Proactive cache warming for agent workflows
  • 🗂️ Persistent Storage: Queryable, extensible, and never lose a thought
  • 🔄 Real-Time & Multi-Branch: Visualize and analyze multiple branches and nodes in real-time
  • 🛠️ Production-Grade: Robust error handling, performance optimizations, and agent/human-friendly APIs

🛠️ Technology Stack

  • Node.js (18+)
  • TypeScript (4.x)
  • @dagrejs/graphlib: Graph structure, algorithms, and analytics
  • ml-kmeans: Clustering for visualization
  • lru-cache: LRU+TTL caching for embeddings, summaries, analytics
  • @xenova/transformers: Embedding and summarization pipelines
  • @modelcontextprotocol/sdk: MCP protocol and agent integration
  • chalk: CLI output styling
  • Mermaid: Gantt/roadmap visualization
  • pnpm: Fast dependency management

Roadmap (Gantt)

gantt
    title Branch-Thinking MCP Roadmap (2025)
    dateFormat  YYYY-MM-DD
    section Q2 2025
    Advanced Visualization/Analytics :done,      vis1, 2025-04-01,2025-04-20
    Agentic Cache & Prefetch         :done,      cache1, 2025-04-10,2025-04-22
    Enhanced Agentic Docs            :done,      doc1, 2025-04-15,2025-04-25
    Real-time Collaboration          :active,    collab1, 2025-04-20,2025-06-01
    Web Visualization Dashboard      :active,    webviz1, 2025-04-25,2025-06-15
    section Q3 2025
    Plugin System                    :planned,   plugin1, 2025-06-15,2025-07-15
    Mobile/Tablet UI                 :planned,   mobile1, 2025-07-01,2025-08-01
    AI Branch Merging                :planned,   merge1, 2025-07-15,2025-08-15
    Knowledge Base Sync              :planned,   sync1, 2025-08-01,2025-09-01

Table of Contents


Why Branch-Thinking?

  • Agentic by Design: Built for both human and AI workflows—every command is agent-friendly.
  • True Branching: Organize, cross-link, and reason over ideas, code, and tasks in parallel.
  • AI-Native: Semantic search, auto-summarization, and insight generation out-of-the-box.
  • Persistent & Visual: Never lose a thought—everything is queryable, visualizable, and extensible.

Summary

Branch-Thinking MCP Tool is an advanced agentic platform for managing, visualizing, and reasoning over branching thoughts, tasks, code, and knowledge. It empowers both AI agents and humans to organize complex projects, cross-link ideas, and automate insight generation using a powerful branch-based paradigm. With semantic search, visualization, and persistent task/code management, it is designed for next-generation collaborative and autonomous workflows.

Branch-Thinking MCP Tool is an advanced agentic platform for managing, visualizing, and reasoning over branching thoughts, tasks, code, and knowledge. It empowers both AI agents and humans to organize complex projects, cross-link ideas, and automate insight generation using a powerful branch-based paradigm. With semantic search, visualization, and persistent task/code management, it is designed for next-generation collaborative and autonomous workflows.


Architecture & Flow

flowchart TD
    User([User/Agent 🤖])
    CLI([CLI/API])
    BM[BranchManager 🧠]
    EmbCache[[Embedding/Summary Cache]]
    Storage[(Persistent Storage 💾)]
    Viz([Visualization/Analytics])
    Tasks([Task Extraction])
    Snippets([Code Snippet Storage])

    User-->|Commands/Queries|CLI
    CLI-->|Manage/Query|BM
    BM-->|Cache|EmbCache
    BM-->|Save/Load|Storage
    BM-->|Visualize|Viz
    BM-->|Tasks|Tasks
    BM-->|Snippets|Snippets
    BM-->|Results|CLI
    CLI-->|Output|User

Quick Start

Get up and running in seconds:

pnpm install  # Recommended for speed (or npm install)
pnpm build
node dist/index.js --help  # See available commands

Getting Started

1. Clone & Install

git clone https://github.com/your-org/branch-thinking-mcp.git
cd branch-thinking-mcp
pnpm install  # Or npm install
pnpm build   # Or npm run build

2. Configure (Optional)

For Claude Desktop integration, add to your claude_desktop_config.json:

"branch-thinking": {
  "command": "node",
  "args": [
    "/your-custom-mcp-dir-here/branch-thinking/dist/index.js"
  ]
}

3. Run

node dist/index.js

Real-World Usage Recipes

1. Knowledge Capture & Linking

# Batch capture meeting notes
add-thought dev "Discussed semantic search improvements" note
add-thought dev "Agreed to refactor API" decision
# Link related thoughts
link-thoughts t1 t2 supports "API refactor supports search improvements"

2. Agentic Task Extraction

# Extract and manage tasks from a research branch
extract-tasks research
list-tasks research open
update-task-status task-1 in_progress

3. Visualization for Insight

# Generate and interpret a knowledge graph
visualize dev
# Review AI-generated summary
summarize-branch dev

🧑‍💻 Live Example: Agentic Workflow

# 1. Create a new branch for your project or idea
create-branch "AI Research"

# 2. Add thoughts and observations
add-thought [branchId] "Explore semantic search for agent workflows" analysis
add-thought [branchId] "Test cross-linking and summarization" observation

# 3. Link related thoughts
link-thoughts [thoughtId1] [thoughtId2] supports "Thought 2 validates Thought 1"

# 4. See your knowledge graph
visualize [branchId]

# 5. Extract tasks and get AI review
extract-tasks [branchId]
review-branch [branchId]

Replace [branchId] and [thoughtIdX] with actual IDs from list and history.


Command Reference

Branch Management

CommandDescription
listShow all branches with status
focus [branchId]Switch focus to a branch
history [branchId?]Show thought history
summarize-branch [branchId?]AI summary of branch
review-branch [branchId?]AI review of branch
visualize [branchId?]Visual graph of connections

Thought & Insight Management

CommandDescription
insights [branchId?]Get AI-generated insights
crossrefs [branchId?]Show cross-references
hub-thoughts [branchId?]List hub thoughts
semantic-search [query]Find similar thoughts
link-thoughts [from] [to] [type] [reason?]Link two thoughts
add-snippet [content] [tags]Save a code snippet
snippet-search [query]Search code snippets
doc-thought [thoughtId]Document a thought

Task Management

CommandDescription
extract-tasks [branchId?]Extract actionable items
list-tasks [branchId] [status] [assignee] [due]List/filter tasks
update-task-status [taskId] [status]Update a task’s status
summarize-tasks [branchId]Summarize tasks

AI & Knowledge

CommandDescription
ask [question]AI answer from knowledge base

Best Practices

  • Always start with create-branch to ensure clean context.
  • Use list and focus to navigate between projects or lines of thought.
  • Leverage summarize-branch and insights after adding several thoughts to get AI-generated context.
  • Use link-thoughts to explicitly connect ideas, tasks, or code for richer semantic graphs.
  • After code changes, always run pnpm lint and pnpm build to catch errors early.
  • Decompose complex goals into sequences of thought/task/insight commands.
  • Iterate and adapt: Use feedback from summaries, reviews, and visualizations to refine next actions.
  • Explicitly specify parameters (branchId, status, assignee, etc.) for precise results.
  • Use cross-references and multi-hop links to foster creativity and bridge ideas.
  • Prompt agents (Claude, GPT-4, etc.) to "think step by step" or "use chain of thought" for best results.

Security

  • All persistent data is stored locally (default: project directory or MCP_STORAGE_PATH)
  • No external API calls unless configured
  • Agents/users are responsible for privacy of stored thoughts and tasks
  • To report security issues, please open an issue or email the maintainer.

Troubleshooting and FAQ

Q: The tool isn't responding! A: Check the MCP server logs and ensure configuration is correct.

Q: How do I reset storage? A: Delete or move the persistent storage directory (see config).

Q: How do I add a new command? A: Extend handleCommand in src/index.ts and document it in the README.

Accessibility and Internationalization

  • All badges/images have descriptive alt text.
  • English is the default language; contributions for translations are welcome.
  • Please open a PR or issue if you want to help localize this tool.

Contributing

Contributions, issues, and feature requests are welcome! Please open a PR or issue on GitHub.

  1. Fork this repo
  2. Create a new branch (git checkout -b feature/your-feature)
  3. Commit your changes
  4. Push to the branch
  5. Open a Pull Request

Credits

  • Concept & Testing: @ssdeanx
  • Core Code Generation: Claude, GPT-4, and Cascade
  • Implementation, Fixes, and Documentation: @ssdeanx

License

MIT

Recommend Servers
TraeBuild with Free GPT-4.1 & Claude 3.7. Fully MCP-Ready.
Visual Studio Code - Open Source ("Code - OSS")Visual Studio Code
Serper MCP ServerA Serper MCP Server
Amap Maps高德地图官方 MCP Server
TimeA Model Context Protocol server that provides time and timezone conversion capabilities. This server enables LLMs to get current time information and perform timezone conversions using IANA timezone names, with automatic system timezone detection.
Tavily Mcp
MCP AdvisorMCP Advisor & Installation - Use the right MCP server for your needs
Zhipu Web SearchZhipu Web Search MCP Server is a search engine specifically designed for large models. It integrates four search engines, allowing users to flexibly compare and switch between them. Building upon the web crawling and ranking capabilities of traditional search engines, it enhances intent recognition capabilities, returning results more suitable for large model processing (such as webpage titles, URLs, summaries, site names, site icons, etc.). This helps AI applications achieve "dynamic knowledge acquisition" and "precise scenario adaptation" capabilities.
Context7Context7 MCP Server -- Up-to-date code documentation for LLMs and AI code editors
Baidu Map百度地图核心API现已全面兼容MCP协议,是国内首家兼容MCP协议的地图服务商。
CursorThe AI Code Editor
Playwright McpPlaywright MCP server
Howtocook Mcp基于Anduin2017 / HowToCook (程序员在家做饭指南)的mcp server,帮你推荐菜谱、规划膳食,解决“今天吃什么“的世纪难题; Based on Anduin2017/HowToCook (Programmer's Guide to Cooking at Home), MCP Server helps you recommend recipes, plan meals, and solve the century old problem of "what to eat today"
Jina AI MCP ToolsA Model Context Protocol (MCP) server that integrates with Jina AI Search Foundation APIs.
ChatWiseThe second fastest AI chatbot™
WindsurfThe new purpose-built IDE to harness magic
DeepChatYour AI Partner on Desktop
EdgeOne Pages MCPAn MCP service designed for deploying HTML content to EdgeOne Pages and obtaining an accessible public URL.
MiniMax MCPOfficial MiniMax Model Context Protocol (MCP) server that enables interaction with powerful Text to Speech, image generation and video generation APIs.
AiimagemultistyleA Model Context Protocol (MCP) server for image generation and manipulation using fal.ai's Stable Diffusion model.
BlenderBlenderMCP connects Blender to Claude AI through the Model Context Protocol (MCP), allowing Claude to directly interact with and control Blender. This integration enables prompt assisted 3D modeling, scene creation, and manipulation.