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分类: 其它需要 API Key

OpenViking

通过 OpenViking ContextDatabase MCP 服务器实现 RAG 与语义搜索,支持文档查询、知识库搜索、向量化存储添加文件/URL。用于文档问答、知识管理、AI 代理记忆、文件搜索和语义检索。触发关键词:"openviking", "search documents", "semanticsearch", "knowledge base", "vector database", "RAG", "query pdf", "document query", "add resource"。

person作者: zaynjarvishubclawhub

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