Conduit AI Intelligence Hub
Conduit automates the discovery and configuration of MCP servers while transforming your personal artifacts into a precise knowledge layer, delivering AI-ready context without the manual setup or document bloat.
Installation
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Conduit
Make Your AI Tools Smarter with a Private Knowledge Base
Your Documents. Your AI. Your Control.
Conduit transforms your local documents into a private knowledge base that makes AI tools like Claude Desktop, ChatGPT, Perplexity, and AI coding assistants like Claude Code, Cursor, Copilot, Kiro, and Gemini CLI significantly smarter.
Everything stays local. No documents or artifacts ever leave your machine.
Why Conduit?
AI tools are powerful, but they struggle with:
- Context bloat: Feeding too much information overwhelms the AI
- Missing context: Not enough information leads to hallucinations
- Privacy concerns: Sensitive documents shouldn't leave your machine
Conduit solves this by:
- Intelligent retrieval: RAG (Retrieval-Augmented Generation) and KAG (Knowledge-Augmented Generation) find exactly the right context
- Local-first: All processing happens on your machine - documents never leave
- MCP integration: Works with any AI tool that supports Model Context Protocol
Quick Start (5 minutes)
Install via CLI (Recommended)
curl -fsSL https://raw.githubusercontent.com/amlandas/Conduit-AI-Intelligence-Hub/main/scripts/install.sh | bash
The installer handles everything:
- Installs Conduit CLI and daemon
- Sets up container runtime (Podman/Docker)
- Installs AI models via Ollama
- Configures vector database (Qdrant) and knowledge graph (FalkorDB)
- Auto-configures MCP server in Claude Code
Verify Installation
# Restart terminal, then:
conduit doctor
Add Your Documents
# Add a folder to your knowledge base
conduit kb add ~/Documents/my-project --name "My Project"
# Sync documents (indexes for search)
conduit kb sync
# Test search
conduit kb search "how does authentication work"
That's it! Your AI tools now have access to your private knowledge base.
How It Works
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β Your Local Machine β
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ€
β β
β ββββββββββββββββ ββββββββββββββββββββββββββββββββββββ β
β β Your Docs β βββββββΊ β Conduit β β
β β (PDF, MD, β β ββββββββββββββββββββββββββββββ β β
β β Code, etc.) β β β RAG: Semantic + Keyword β β β
β ββββββββββββββββ β β KAG: Knowledge Graph β β β
β β ββββββββββββββββββββββββββββββ β β
β βββββββββββββββββ¬βββββββββββββββββββ β
β β β
β β MCP Protocol β
β βΌ β
β ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ β
β β AI Tools (via MCP Server) β β
β β Claude Code β Cursor β Claude Desktop β ChatGPT β etc. β β
β ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ β
β β
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Key Technologies
| Component | Purpose |
|---|---|
| RAG (Retrieval-Augmented Generation) | Finds semantically similar documents using vector search |
| KAG (Knowledge-Augmented Generation) | Builds a knowledge graph for multi-hop reasoning |
| MCP (Model Context Protocol) | Standard protocol for AI tools to access external data |
| Qdrant | Vector database for semantic search (runs locally in container) |
| FalkorDB | Graph database for knowledge graphs (runs locally in container) |
| Ollama | Local AI models for embeddings and entity extraction |
CLI Reference
Conduit is a CLI-first tool. For the complete command reference, see CLI Command Index.
Essential Commands
# Setup & Health
conduit doctor # Run diagnostics
conduit status # Show system status
# Knowledge Base
conduit kb add <path> # Add document folder
conduit kb sync # Index documents
conduit kb search <query> # Search your knowledge base
conduit kb list # List all sources
conduit kb stats # Show statistics
# MCP Server
conduit mcp status # Verify MCP server is configured
conduit mcp configure # Configure MCP for Claude Code
Search Modes
# Hybrid search (default) - combines keyword + semantic
conduit kb search "authentication flow"
# Semantic search - finds by meaning
conduit kb search "securing user login" --semantic
# Keyword search - exact matches
conduit kb search "OAuth2 client_id" --fts5
Knowledge Graph Queries
# Extract entities from your documents
conduit kb kag-sync
# Query relationships
conduit kb kag-query "Kubernetes"
conduit kb kag-query "authentication" --entities OAuth,JWT --max-hops 2
MCP Server Integration
Conduit automatically creates an MCP server for your knowledge base and configures it for Claude Code.
For Claude Code (Auto-configured)
After running conduit kb sync, your knowledge base is automatically available in Claude Code.
For Other AI Tools (Manual Configuration)
Add to your AI tool's MCP configuration:
{
"mcpServers": {
"conduit-kb": {
"command": "conduit",
"args": ["mcp", "kb"]
}
}
}
Configuration locations:
- Claude Desktop:
~/Library/Application Support/Claude/claude_desktop_config.json - Cursor:
.cursor/mcp.json - VS Code:
.vscode/settings.json(undermcp.servers)
Available MCP Tools
| Tool | Description |
|---|---|
kb_search | Hybrid search (semantic + keyword) |
kb_search_with_context | Search with merged results and citations |
kb_list_sources | List indexed document sources |
kb_get_document | Retrieve full document content |
kb_stats | Knowledge base statistics |
kag_query | Query knowledge graph for entities |
Installation Options
CLI Installation (Recommended)
# Standard install
curl -fsSL https://raw.githubusercontent.com/amlandas/Conduit-AI-Intelligence-Hub/main/scripts/install.sh | bash
# Custom options
curl -fsSL ... | bash -s -- --install-dir ~/.local/bin # Custom location
curl -fsSL ... | bash -s -- --skip-model # Skip AI model download
curl -fsSL ... | bash -s -- --no-kag # Skip knowledge graph setup
curl -fsSL ... | bash -s -- --verbose # Verbose output
Manual Installation
git clone https://github.com/amlandas/Conduit-AI-Intelligence-Hub.git
cd Conduit-AI-Intelligence-Hub
make build
sudo cp bin/conduit bin/conduit-daemon /usr/local/bin/
conduit setup
Desktop App (Experimental)
Note: The Desktop App is currently experimental and under active development. The CLI is the recommended way to use Conduit.
For users who prefer a graphical interface, download the DMG from Releases.
Desktop App Details
Download
- Apple Silicon (M1/M2/M3/M4):
Conduit-x.x.x-arm64.dmg
macOS Security Note
On first launch, you may see "Conduit.app is damaged". Run:
xattr -cr /Applications/Conduit.app
Features (Experimental)
- Dashboard with real-time status
- Knowledge Base management with RAG tuning
- KAG search interface
- Settings and configuration
Supported Document Formats
| Category | Formats |
|---|---|
| Documentation | .md, .txt, .rst |
| Code | .go, .py, .js, .ts, .java, .rs, .rb, .c, .cpp, .h, .cs, .swift, .kt |
| Scripts | .sh, .bash, .zsh, .ps1, .bat |
| Config | .json, .yaml, .yml, .xml, .toml, .ini |
| Data | .csv, .tsv |
| Documents | .pdf, .doc, .docx, .odt, .rtf |
Uninstalling
The recommended way to uninstall is via the CLI:
# Preview what will be removed
conduit uninstall --dry-run --all
# Uninstall (keeps your data)
conduit uninstall --keep-data
# Full uninstall (removes everything)
conduit uninstall --all
Backup method (if CLI is unavailable):
curl -fsSL https://raw.githubusercontent.com/amlandas/Conduit-AI-Intelligence-Hub/main/scripts/uninstall.sh | bash
Troubleshooting
Quick Diagnostics
conduit doctor # Comprehensive health check
conduit status # System status overview
Common Issues
Semantic search shows 0 vectors:
conduit qdrant status # Check Qdrant
conduit kb sync --rebuild-vectors # Rebuild vectors
MCP server not working:
conduit mcp status # Check MCP configuration
conduit mcp configure # Reconfigure
KAG extraction slow on first run:
The extraction model (~4GB) loads on first use. Enable preloading in ~/.conduit/conduit.yaml:
kb:
kag:
preload_model: true
For more troubleshooting, see Known Issues.
Documentation
| Document | Description |
|---|---|
| CLI Command Index | Complete CLI reference |
| Quick Start Guide | Step-by-step getting started |
| User Guide | Detailed usage instructions |
| Admin Guide | System administration |
| Known Issues | Issues and workarounds |
| MCP Server Design | MCP implementation details |
Contributing
We welcome contributions! Please see CONTRIBUTING.md for guidelines.
- Bug Reports: Use the bug report template
- Feature Requests: Use the feature request template
- Questions: Ask in GitHub Discussions
Requirements
The installer handles these automatically:
| Requirement | Version | Notes |
|---|---|---|
| macOS or Linux | - | Windows support planned |
| Podman or Docker | 4.0+ / 20.10+ | Container runtime |
| Ollama | Latest | Local AI models |
Privacy & Security
- 100% Local: All documents and processing stay on your machine
- No Telemetry: Conduit doesn't phone home
- Sandboxed Containers: Qdrant and FalkorDB run in isolated containers
- Read-Only MCP: AI tools can only read, not modify your knowledge base
License
MIT License - see LICENSE for details.
Acknowledgments
Built with:
- Qdrant - Vector database
- FalkorDB - Graph database
- Ollama - Local AI models
- Model Context Protocol - AI tool integration
Conduit v1.0 β Private Knowledge Base for AI Tools
