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    Branch Thinking Mcp

    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.

    15 stars
    TypeScript
    Updated Sep 14, 2025
    agentic-ai
    agents
    cache
    cognitive-architecture
    cross-referencing
    insight-generation
    knowledge-graph
    knowledge-graph-embeddings
    mcp
    mcp-server
    mcp-tools
    nodejs
    semantic-search
    task-management
    task-management-system
    tasks-manager
    typescript
    workflow
    workflow-automation

    Documentation

    🚦 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)

    mermaid
    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?
    • Summary
    • Features
    • Quick Start
    • Getting Started
    • Real-World Usage Recipes
    • Architecture & Flow
    • Roadmap (Gantt)
    • Testing & Quality
    • Security
    • Accessibility & Internationalization
    • Troubleshooting & FAQ
    • Best Practices
    • Contributing
    • Changelog
    • References & Related Projects
    • Credits
    • License

    ---

    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

    mermaid
    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:

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

    ---

    Getting Started

    1. Clone & Install

    bash
    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:

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

    3. Run

    bash
    node dist/index.js

    ---

    Real-World Usage Recipes

    1. Knowledge Capture & Linking

    bash
    # 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

    bash
    # 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

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

    ---

    🧑‍💻 Live Example: Agentic Workflow

    bash
    # 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

    References and Related Projects

    • Model Context Protocol (MCP)
    • Sequential Thinking Tool
    • Obsidian
    • Logseq

    ---

    Credits

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

    ---

    License

    MIT

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