mcp-local-rag MCP Server
The mcp-local-rag MCP Server enables privacy-respecting, local Retrieval-Augmented Generation (RAG) web search for LLMs. It allows AI assistants to access, embe...
4 min read
MCP
RAG
+5
RAG
Context Portal (ConPort) MCP Server
Context Portal (ConPort) is a memory bank MCP server that empowers AI assistants and developer tools by managing structured project context, enabling Retrieval ...
4 min read
AI
MCP
+5
Pinecone MCP Server Integration
Integrate FlowHunt with Pinecone vector databases using the Pinecone MCP Server. Enable semantic search, Retrieval-Augmented Generation (RAG), and efficient doc...
4 min read
AI
MCP Server
+4
RAG Web Browser MCP Server
The RAG Web Browser MCP Server equips AI assistants and LLMs with live web search and content extraction capabilities, enabling retrieval-augmented generation (...
4 min read
AI
RAG
+7
Agentset MCP Server
The Agentset MCP Server is an open-source platform enabling Retrieval-Augmented Generation (RAG) with agentic capabilities, allowing AI assistants to connect wi...
4 min read
AI
Open Source
+5
Inkeep MCP Server
The Inkeep MCP Server connects AI assistants and developer tools to up-to-date product documentation managed in Inkeep, enabling direct, secure, and efficient r...
4 min read
MCP Server
Documentation
+5
mcp-rag-local MCP Server
The mcp-rag-local MCP Server empowers AI assistants with semantic memory, enabling storage and retrieval of text passages based on meaning, not just keywords. I...
4 min read
MCP
Semantic Search
+6
Graphlit MCP Server Integration
The Graphlit MCP Server connects FlowHunt and other MCP clients to a unified knowledge platform, enabling seamless ingestion, aggregation, and retrieval of docu...
5 min read
MCP
AI
+6
Vectara MCP Server Integration
Vectara MCP Server is an open source bridge between AI assistants and Vectara's Trusted RAG platform, enabling secure, efficient Retrieval-Augmented Generation ...
4 min read
AI
RAG
+5
Cache Augmented Generation (CAG)
Cache Augmented Generation (CAG) is a novel approach to enhancing large language models (LLMs) by preloading knowledge as precomputed key-value caches, enabling...
7 min read
Cache Augmented Generation
LLM
+4
Document Grading
Document grading in Retrieval-Augmented Generation (RAG) is the process of evaluating and ranking documents based on their relevance and quality in response to ...
2 min read
RAG
Document Grading
+3
Document Reranking
Document reranking is the process of reordering retrieved documents based on their relevance to a user's query, refining search results to prioritize the most p...
9 min read
Document Reranking
RAG
+4
Document Retriever
FlowHunt's Document Retriever enhances AI accuracy by connecting generative models to your own up-to-date documents and URLs, ensuring reliable and relevant ans...
4 min read
AI
Document Retrieval
+3
GoogleSearch Component
FlowHunt's GoogleSearch component enhances chatbot accuracy using Retrieval-Augmented Generation (RAG) to access up-to-date knowledge from Google. Control resul...
4 min read
AI
Components
+4
Knowledge Sources
Knowledge Sources make teaching the AI according to your needs a breeze. Discover all the ways of linking knowledge with FlowHunt. Easily connect websites, docu...
3 min read
AI
Knowledge Management
+3
LazyGraphRAG
LazyGraphRAG is an innovative approach to Retrieval-Augmented Generation (RAG), optimizing efficiency and reducing costs in AI-driven data retrieval by combinin...
4 min read
RAG
AI
+4
Make LLMs to fact-check their responses and include sources
Boost AI accuracy with RIG! Learn how to create chatbots that fact-check responses using both custom and general data sources for reliable, source-backed answer...
5 min read
AI
Chatbot
+5
Query Expansion
Query Expansion is the process of enhancing a user’s original query by adding terms or context, improving document retrieval for more accurate and contextually ...
9 min read
AI
RAG
+4
Question Answering
Question Answering with Retrieval-Augmented Generation (RAG) combines information retrieval and natural language generation to enhance large language models (LL...
5 min read
AI
Question Answering
+4
RAG with Reasoning LLMs: OpenAI O1 vs OpenAI GPT4o
Explore how OpenAI O1's advanced reasoning capabilities and reinforcement learning outperform GPT4o in RAG accuracy, with benchmarks and cost analysis.
3 min read
OpenAI O1
GPT4o
+4
Retrieval Augmented Generation (RAG)
Retrieval Augmented Generation (RAG) is an advanced AI framework that combines traditional information retrieval systems with generative large language models (...
4 min read
RAG
AI
+4
Retrieval Pipeline
Discover what a retrieval pipeline is for chatbots, its components, use cases, and how Retrieval-Augmented Generation (RAG) and external data sources enable acc...
6 min read
AI
Chatbots
+4
Retrieval vs Cache Augmented Generation (CAG vs. RAG)
Discover the key differences between Retrieval-Augmented Generation (RAG) and Cache-Augmented Generation (CAG) in AI. Learn how RAG dynamically retrieves real-t...
6 min read
RAG
CAG
+5