Ask questions to a RAG knowledge base and retrieve grounded answers with source citations.
MIT
466,089 tools. Updated 2026-08-19 11:00
"A server to build a knowledge base of Node.js packages with RAG search functionality" matching MCP tools:
- Scrape a public URL to create a searchable knowledge base. Extracts content from web pages (including JavaScript-rendered), chunks it, and indexes for RAG.MIT
- Connect knowledge bases to an agent to enable RAG-powered, grounded answers. Replaces all current attachments, so pass the complete list of knowledge base IDs.MIT
- Create a knowledge store to store documents for RAG, enabling AI agents to search and answer questions. Set dryRun=false to create.MIT
- Create a searchable knowledge base from plain text, automatically chunked and indexed for RAG retrieval. Ideal for FAQs, product specs, and policies.MIT
- Ask natural-language questions and receive grounded, cited answers from Calypso's knowledge base, with support for file IDs and multi-turn follow-ups.MIT
Matching MCP Servers
- AlicenseAqualityDmaintenanceMCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.11MIT
- Alicense-qualityCmaintenanceA knowledge base MCP server that aggregates team knowledge from multiple sources into Postgres. It provides hybrid search (full-text + vector + RRF) via MCP tools, and enables direct recording of decisions, learnings, and pitfalls.MIT
Matching MCP Connectors
A searchable knowledge base your assistant reads and writes.
AI-powered knowledge base for Double - Thank You with semantic search and question answering.
- List available data sources in the MongoDB Assistant knowledge base to locate search filter parameters for targeted knowledge queries.Apache 2.0
- Search Symbols documentation with natural language queries to find relevant information and answers. Get source references from the knowledge base.Creative Commons Attribution Non Commercial 4.0 International
- Upload a project archive to auto-detect build settings and start a Node.js build immediately, simplifying deployment into a single action.MIT
- Retrieve a list of all knowledge folders in your organization, each containing documents for RAG capabilities.MIT
- Validate and delete a knowledge chunk from a store. Set dryRun to false to permanently remove and stop RAG search.MIT
- Retrieve logs from a Node.js build process for debugging. Pass from_line to poll new output while the build is running, using domain, username, and build UUID.MIT
- Retrieve paginated Node.js builds for a website, filterable by state, to monitor build pipeline runs.MIT
- Index local research documents (PDF, Markdown, JSON, TXT) into the Onyx RAG knowledge base. These documents become searchable for instant retrieval and querying.MIT
- Retrieve the full content, metadata, and source of a specific knowledge chunk to inspect what content is used in RAG searches.MIT
- Retrieve aggregated knowledge search and RAG query counts for a project or entire organization within a date range.MIT
- Ask natural language questions to get answers with cited sources from the Onyx knowledge base using RAG.MIT
- Add specific text segments to a Cognigy.AI knowledge store as searchable chunks for RAG. Set dryRun=false to create.MIT
- Find alternative packages for your npm dependencies. Compare similar functionality to identify suitable replacements.TypeScriptMIT
- Create a searchable knowledge tool for retrieving documents. Integrates selected knowledge folders into a custom tool for RAG-based document search.MIT