Onyx Knowledge Base is knowledge base software with semantic search and chat, enabling teams to access and manage knowle
by lupuletic·Add new capabilities to Claude beyond text generation
Example: Access external data sources, execute code, interact with tools and services
Transform Claude from chatbot to action-taking agent
Provide Claude with access to relevant context and data
Example: Load project documentation, access knowledge bases, query databases
Get more accurate, context-aware responses
Automate multi-step workflows combining AI and external tools
Example: Research → Summarize → Create document → Send notification
Complete complex tasks end-to-end without manual steps
Time estimate: 15-60 minutes depending on server complexity
Prerequisites
Arize Phoenix
Arize Phoenix — unified interface for managing prompts, exploring datasets, and running LLM experiments across providers
Local RAG
Local RAG enables semantic document search using retrieval augmented generation (RAG) without external API calls.
Qdrant Docs Rag
Qdrant Docs Rag offers real-time documentation context using vector-based search and retrieval with Qdrant for efficient
Legion Database
Legion Database: natural-language SQL for multi-database querying. Explore PostgreSQL, MySQL, SQL Server & BigQuery with
Octagon Deep Research
Octagon Deep Research offers competitive analysis software and competitor website analysis tools for advanced SEO and ma
Onyx Knowledge Base reduced integration guesswork — categories and install configs on the listing matched the upstream repo.
We wired Onyx Knowledge Base into a staging workspace; the listing’s GitHub and npm pointers saved time versus hunting across READMEs.
According to our notes, Onyx Knowledge Base benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
I recommend Onyx Knowledge Base for teams standardizing on MCP; the explainx.ai page compares cleanly with sibling servers.
Onyx Knowledge Base is among the better-indexed MCP projects we tried; the explainx.ai summary tracks the official description.
We evaluated Onyx Knowledge Base against two servers with overlapping tools; this profile had the clearer scope statement.
Onyx Knowledge Base has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
Strong directory entry: Onyx Knowledge Base surfaces stars and publisher context so we could sanity-check maintenance before adopting.
Onyx Knowledge Base has been reliable for tool-calling workflows; the MCP profile page is a good permalink for internal docs.
According to our notes, Onyx Knowledge Base benefits from clear Model Context Protocol framing — fewer ambiguous “AI plugin” claims.
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Claude Desktop configuration
{
"mcpServers": {
"onyx-search": {
"command": "npx",
"args": [
"-y",
"@lupuletic/onyx-mcp-server"
],
"env": {
"ONYX_API_TOKEN": "your-api-token-here",
"ONYX_API_URL": "https://your-onyx-api-url.example.com/api"
}
}
}
}Connects MCP clients to Onyx knowledge bases for semantic document search and AI-powered Q&A using RAG (retrieval-augmented generation).
Onyx Knowledge Base is a community-built MCP server published by lupuletic that provides AI assistants with tools and capabilities via the Model Context Protocol. Onyx Knowledge Base is knowledge base software with semantic search and chat, enabling teams to access and manage knowle It is categorized under ai ml.
You can install Onyx Knowledge Base in your AI client of choice. Use the install panel on this page to get one-click setup for Cursor, Claude Desktop, VS Code, and other MCP-compatible clients. This server runs locally on your machine via the stdio transport.
README content is unavailable from source data for this server.
Open GitHub repository →Steps
Troubleshooting
✓ Do
✗ Don't
💡 Pro Tips
Architecture
Model Context Protocol standardizes how AI hosts (Claude, Cursor) communicate with external tools and data sources through server implementations.
Protocols
Compatibility
✓ Use when
Use when you need Claude to access external data, execute actions, or integrate with tools. Best for extending AI capabilities beyond conversation.
✗ Avoid when
Avoid when native integrations exist (use official APIs directly), for real-time critical systems, or when security/compliance requires zero external dependencies.