openviking

What This Skill Does

OpenViking acts as a sophisticated, context-aware memory layer for your AI agent. Unlike traditional flat vector databases that can suffer from noise and retrieval degradation, OpenViking utilizes a filesystem-inspired paradigm. This structure allows your agent to organize knowledge using intuitive URIs (e.g., viking://resources/projects/alpha), enabling a more human-like, hierarchical retrieval process. By utilizing tiered context (L0/L1/L2), the system effectively manages memory, moving from abstract overviews to deep, document-level details exactly when the agent needs them for RAG-based reasoning.

Installation

To integrate OpenViking, first ensure you have the necessary environment configured. Run the setup script using bash ~/.openclaw/skills/openviking-mcp/scripts/init.sh to clone the repository and prepare your dependencies via uv. After installation, you must edit the generated ov.conf file to include your specific Volcengine Ark API keys for embedding and VLM processing. Once configured, launch the server using uv run server.py. For seamless integration, add the server to your Claude MCP configuration by pointing it to your local host at http://localhost:2033/mcp. Always verify the service is operational by running the provided curl health check command before attempting to query.

Use Cases

OpenViking is ideal for professional knowledge management, technical documentation retrieval, and long-term memory for research-heavy AI tasks. It shines when managing disparate project files, onboarding documents, or large repositories of PDF literature that require high-precision retrieval rather than general-purpose LLM knowledge. Agents can use it to maintain a living, breathing knowledge base that evolves alongside user input.

Example Prompts

1. "Query: Summarize the key findings from the project roadmap PDF stored in my context database."
2. "Add https://docs.python.org/3/reference/ to the knowledge base so I can query Python specs later."
3. "Search: Find all documents related to Q4 strategic planning and list the top three takeaways."

Tips & Limitations

Always monitor your API usage, as excessive indexing of large directories will consume your Volcengine credits. If you encounter connectivity issues, verify that your port settings match between the server and the MCP client. Note that performance is heavily dependent on the quality of your embeddings; ensure your API keys are valid and have sufficient quota. For large-scale data, consider using separate directories within the data folder to maintain organizational clarity and improve retrieval speed.