cbridge-agent 0.1.19

Connect AI Agents to your Local Documents

🇨🇳 中文 | 🇬🇧 English

ContextBridge (cbridge-agent)

Connect AI Agentsto your Local Documents

Local knowledge base for OpenClaw, Cursor and AI assistants. Read your documents instantly—Word, Excel, PDF. No uploads. Privacy first.

🌐 Official Website: https://contextbridge.chat

OpenClaw Skill

Native skills for ContextBridge local-context-bridge are available on clawhub.ai.

• openclaw_skills/local-context-bridge - For English language environments
• openclaw_skills/local-context-bridge-cn - For Chinese language environments

Once installed, OpenClaw will automatically detect ContextBridge — no additional configuration needed to search your local documents.

Quick Start

Installation

pip install cbridge-agent

The vector model will be downloaded automatically on the first run.

Initialization

cbridge init

Follow the interactive wizard to complete the configuration (the default workspace is at ~/.cbridge).

Add a Document Directory

cbridge watch add /path/to/your/documents

File changes in this directory will be automatically synced to the vector database.

Search Document Content

cbridge search ContextBridge

Core Feature: Intelligent Text Chunking

ContextBridge uses a three-tier progressive retrieval architecture to ensure AI can precisely locate document content:

L0 Layer: Document Abstract

Automatically extracts document title and first paragraph core content for quick relevance assessment.

L1 Layer: Structural Outline

Parses document heading hierarchy (H1-H3) to build a complete content navigation map.

L2 Layer: Semantic Chunking

• Default chunk size: 800 characters
• Smart overlap: 150 characters (maintains context continuity)
• Paragraph-aware: Splits at natural paragraph boundaries to avoid semantic fragmentation
• Markdown-friendly: Recognizes code blocks, lists, and other structures to preserve formatting integrity

Retrieval Process

1. Intent Filtering: Quickly match relevant documents at L0/L1 layers
2. Fine-grained Retrieval: Precisely search relevant fragments in L2 layer of matched documents
3. Context Assembly: Return document abstract + relevant excerpts to provide complete context

This design allows AI to quickly locate target documents while obtaining precise contextual information, avoiding the "can't see the forest for the trees" problem of traditional RAG systems.

Other AI Clients

In addition to OpenClaw, ContextBridge also works with Claude Desktop, Cursor, and other MCP-compatible clients:

{
  "mcpServers": {
    "context-bridge": {
      "command": "cbridge",
      "args": ["mcp"]
    }
  }
}

CLI Commands

Command	Description
cbridge init	Interactive initialization (the service starts automatically; no need to run cbridge start manually)
cbridge watch add <dir>	Add a directory to watch
cbridge watch list	List watched directories
cbridge watch remove <dir>	Remove a watched directory
cbridge start	Start the watcher service
cbridge serve	Start both the API and watcher services
cbridge index	Rebuild the index from scratch
cbridge search "query"	Test semantic search
cbridge status	Check running status
cbridge lang <zh|en>	Switch language
cbridge logs -f	View logs

FAQ

Q: How do I switch the PDF parsing strategy? A: Edit the configuration file at ~/.cbridge/config.yaml, and set parser.pdf.strategy to docling (higher accuracy but slower) or markitdown (lightweight default).

Q: What file formats are supported? A: PDF, DOCX, XLSX, PPTX, MD, TXT, and more. MarkItDown covers the vast majority of office document formats.

Q: Where is the indexed data stored? A: All data is stored locally in the ~/.cbridge/ directory, including the vector database and configuration files.

Contributing

Issues and Pull Requests are welcome.

License

MIT License