OpenViking

👤 zaynjarvis 📦 v1.0.3 ⭐ 4.2 ⬇️ 6.3K 下載
📚 知識管理 免費 🔑 需 API Key

📖 技能介紹


name: openviking description: RAG and semantic search via OpenViking Context Database MCP server. Query documents, search knowledge base, add files/URLs to vector memory. Use for document Q&A, knowledge management, AI agent memory, file search, semantic retrieval. Triggers on "openviking", "search documents", "semantic search", "knowledge base", "vector database", "RAG", "query pdf", "document query", "add resource".


OpenViking - Context Database for AI Agents

OpenViking is ByteDance's open-source Context Database designed for AI Agents — a next-generation RAG system that replaces flat vector storage with a filesystem paradigm for managing memories, resources, and skills.

Key Features: - Filesystem paradigm: Organize context like files with URIs (viking://resources/...) - Tiered context (L0/L1/L2): Abstract → Overview → Full content, loaded on demand - Directory recursive retrieval: Better accuracy than flat vector search - MCP server included: Full RAG pipeline via Model Context Protocol


Quick Check: Is It Set Up?

test -f ~/code/openviking/examples/mcp-query/ov.conf && echo "Ready" || echo "Needs setup"
curl -s http://localhost:2033/mcp && echo "Running" || echo "Not running"

If Not Set Up → Initialize

Run the init script (one-time):

bash ~/.openclaw/skills/openviking-mcp/scripts/init.sh

This will: 1. Clone OpenViking from https://github.com/volcengine/OpenViking 2. Install dependencies with uv sync 3. Create ov.conf template 4. Pause for you to add API keys (embedding.dense.api_key, vlm.api_key)

Required: Volcengine/Ark API Keys

Config Key Purpose
embedding.dense.api_key Semantic search embeddings
vlm.api_key LLM for answer generation

Get keys from: https://console.volcengine.com/ark

Start the Server

cd ~/code/openviking/examples/mcp-query
uv run server.py

Options: - --port 2033 - Listen port - --host 127.0.0.1 - Bind address - --data ./data - Data directory

Server will be at: http://127.0.0.1:2033/mcp

Connect to Claude

claude mcp add --transport http openviking http://localhost:2033/mcp

Or add to ~/.mcp.json:

{
  "mcpServers": {
    "openviking": {
      "type": "http",
      "url": "http://localhost:2033/mcp"
    }
  }
}

Tools Available

Tool Description
query Full RAG pipeline — search + LLM answer
search Semantic search only, returns docs
add_resource Add files, directories, or URLs

Example Usage

Once connected via MCP:

"Query: What is OpenViking?"
"Search: machine learning papers"
"Add https://example.com/article to knowledge base"
"Add ~/documents/report.pdf"

Troubleshooting

Issue Fix
Port in use uv run server.py --port 2034
Auth errors Check API keys in ov.conf
Server not found Ensure it's running: curl localhost:2033/mcp

Files

  • ov.conf - Configuration (API keys, models)

    小蔥技能7w4.net持續更新中。

  • data/ - Vector database storage
  • server.py - MCP server implementation

🤖 AI 評測

這個 Skill 質量較好,安裝設定有中文說明,步驟清晰易懂,初始化指令碼能自動完成大部分工作。風險提示比較充分,使用起來比較放心。不足之處是示例和案例偏少,新手可能需要額外查閱資料才能快速上手。

📊 多維度評分

適應性4
規範性4.2
有效性4.5
可靠性3.7
可信度4.7

📁 包含檔案 (4 個)

📄 SKILL.md 3.1 KB
📄 _meta.json 135 B
📄 scripts/init.sh 1.7 KB
📄 skill.yaml 455 B