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OpenViking

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".

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Install for OpenClaw

Quick setup

Download the package from Yavira.
Extract the archive and review SKILL.md first.
Import or place the package into your OpenClaw setup.

Requirements

Target platform: OpenClaw
Install method: Manual import
Extraction: Extract archive
Prerequisites: OpenClaw
Primary doc: SKILL.md

Package facts

Download mode: Yavira redirect
Package format: ZIP package
Source platform: Tencent SkillHub
What's included: SKILL.md, scripts/init.sh, skill.yaml

Validation

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Review SKILL.md after the package is downloaded.
Confirm the extracted package contains the expected setup assets.

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Trust & source

Release facts

Source: Tencent SkillHub
Verification: Indexed source record
Version: 1.0.3

Provenance

Publisher: ZaynJarvis
Source page: View original listing
Canonical URL: Open canonical page

Documentation

ClawHub primary doc Primary doc: SKILL.md 9 sections Open source page

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: Clone OpenViking from https://github.com/volcengine/OpenViking Install dependencies with uv sync Create ov.conf template Pause for you to add API keys (embedding.dense.api_key, vlm.api_key) Required: Volcengine/Ark API Keys Config KeyPurposeembedding.dense.api_keySemantic search embeddingsvlm.api_keyLLM 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

ToolDescriptionqueryFull RAG pipeline — search + LLM answersearchSemantic search only, returns docsadd_resourceAdd 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

IssueFixPort in useuv run server.py --port 2034Auth errorsCheck API keys in ov.confServer not foundEnsure it's running: curl localhost:2033/mcp

Files

ov.conf - Configuration (API keys, models) data/ - Vector database storage server.py - MCP server implementation

Category context

Code helpers, APIs, CLIs, browser automation, testing, and developer operations.

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Package contents

Included in package

1 Docs1 Scripts1 Config

SKILL.md Primary doc
scripts/init.sh Scripts
skill.yaml Config