MCP Hub
Back to servers

nodespace-core

Local-first knowledge base with semantic search for AI coding assistants. Fewer tokens, faster context.

GitHub
Stars
3
Updated
Feb 6, 2026
Validated
Feb 9, 2026

NodeSpace

Faster context. Fewer tokens.

AI coding assistants forget everything between sessions. NodeSpace gives them persistent, searchable access to your project knowledge — so you stop re-explaining your codebase every time you start a conversation.

nodespace.ai · Download · Discord

NodeSpace Screenshot

⚠️ Alpha Preview — NodeSpace is in early development. Features may change and data formats are not yet stable.


Why NodeSpace

Developers using AI assistants waste time copying files, re-explaining architecture, and watching context degrade mid-session. NodeSpace fixes this by sitting between your knowledge and your AI tools:

  • 80% fewer roundtrips — AI agents query your knowledge base via MCP instead of scanning files with grep/ripgrep
  • Runs entirely on your machine — no cloud accounts, no API calls, no data leaving localhost
  • Works offline — on planes, behind VPNs, anywhere

You write things down once. Every AI tool you use can find them instantly.


Features

📅 Daily Journal

Quick access to today's context. One click opens a new entry for the current date, making it easy to capture thoughts throughout the day.

📝 Hierarchical Nodes

Create nested, indented blocks of content. Organize complex ideas with unlimited depth — like Logseq or Roam Research.

🏷️ Collections

Flexible organization that combines the best of folders and tags. A single node can belong to multiple collections without duplicating content.

🔗 @Mentions & Linking

Type @ to link to any node. Build a knowledge graph by connecting related ideas. A backlinks panel shows everything that references each node.

✅ Task Management

Markdown-style tasks ([ ], [x], [~]) with visual checkboxes. Track progress on projects while keeping tasks connected to their context.

🔍 Semantic Search

Find what you mean, not just what you typed. Ask "Where do we handle authentication?" and find relevant content without exact keyword matches.

📂 Batch Import

Drop a folder of markdown files and import them in seconds. Semantic embeddings are generated in the background, so everything becomes searchable within minutes.

🤖 MCP Integration

Built-in MCP server for AI tools. Opens with the app — Claude Code, Cursor, Codex, and any MCP-compatible assistant can query your knowledge base locally.


Installation

Download the Desktop App

Download NodeSpace →

PlatformFormat
macOS (Apple Silicon).dmg
Windows.exe or .msi

Build from Source

Prerequisites:

  • Bun 1.0+curl -fsSL https://bun.sh/install | bash
  • Rust 1.80+curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
git clone https://github.com/NodeSpaceAI/nodespace-core
cd nodespace-core
bun install
bun run tauri:dev

MCP Setup

NodeSpace includes a built-in MCP server that starts automatically when you open the app. Your AI tools connect to it locally — there's nothing to deploy or host.

Note: The MCP server binds to localhost only and is accessible to other processes on your machine. Authentication is planned for a future release.

Claude Code / Cursor / Codex / Other MCP Clients

Add to your MCP settings (e.g., ~/.claude.json for Claude Code):

{
  "mcpServers": {
    "nodespace": {
      "type": "http",
      "url": "http://localhost:3100/mcp"
    }
  }
}

Verify Connection

With NodeSpace running, test the connection:

curl -X POST http://localhost:3100/mcp \
  -H "Content-Type: application/json" \
  -d '{"jsonrpc":"2.0","id":1,"method":"tools/list","params":{}}'

Semantic Search

Once connected via MCP, your AI assistant can query your knowledge base semantically.

Example Queries

Ask your AI assistant questions like:

  • "What is our development process for picking up issues?"
  • "How do we handle authentication in the backend?"
  • "What are the coding standards for this project?"
  • "Find context related to the quarterly planning meeting"

Using the search_semantic Tool

AI tools can call the semantic search directly:

{
  "name": "search_semantic",
  "arguments": {
    "query": "development process for implementing issues",
    "limit": 5
  }
}

This returns relevant nodes ranked by semantic similarity — not just keyword matches.

Filtering by Collection

Narrow searches to specific areas:

{
  "name": "search_semantic",
  "arguments": {
    "query": "validation flow",
    "collection": "Architecture"
  }
}

Quick Start

  1. Open Daily Journal — Click "Daily Journal" in the sidebar to start today's entry
  2. Create content — Just start typing. Press Enter to create a new block below
  3. Organize with nesting — Press Tab to indent a block under the one above. Press Shift+Tab to outdent
  4. Link your knowledge — Type @ to search and link to any other node
  5. Use Collections — Expand "Collections" in the sidebar to organize content into categories
  6. Import existing docs — Use File > Import to batch-import a folder of .md files. Hundreds of documents import in seconds; semantic indexing runs automatically in the background
  7. Connect your AI — Configure MCP (see above) and ask your AI assistant to search your knowledge base

Roadmap

FeatureStatusDescription
Custom Node Types🚧 In ProgressDefine your own entity types with custom fields and behaviors
Playbooks📋 PlannedInstallable workflow templates (ERP, Creator, Dev Team)
Cloud Sync📋 PlannedReal-time collaboration and cross-device sync

See the open issues for the full backlog.


Community


License

NodeSpace is licensed under the Functional Source License 1.1 (Apache 2.0).

  • ✅ Use NodeSpace freely for any purpose
  • ✅ Modify the code to fit your needs

See LICENSE for the full text.

Reviews

No reviews yet

Sign in to write a review