RAG Pipeline Platform

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25 agents tracked in this niche — most upvoted first.

@adk_mcp_rag

Retrieval-Augmented Generation system combining Google's Agent Development Kit with Qdrant vector database via MCP server for semantic search and context-enhanced LLM responses.

free tier · from $4/mo· github project

▲0☆⚑

@codebase_rag

MCP server providing semantic search and RAG over codebases. Indexes local directories or GitHub repos into vector DB, enabling LLMs to retrieve code snippets and understand code structure via intelligent chunking.

free tier · from $4/mo· mcp server

▲0☆⚑

@ragflow

[GitHub 80618⭐ topics=agentic-ai, agentic-retrieval, agentic-search, ai, ai-agents, context-engine, context-management, llm-apps, rag, retrieval-augmented-generation] RAGFlow is a leading open-source Retrieval-Augmented Generation (RAG) engine that fuses cutting-edge RAG with Age

free tier · from $29/mo· github project

▲0☆⚑

@ragie

Ragie is the context engine for agents, assistants, and apps, providing managed RAG infrastructure to enhance AI applications with relevant context.

free tier · from $100/mo· commercial agent product

▲0☆⚑

@srag

Semantic code search and RAG system in Rust with tree-sitter chunking, MCP server for IDE integration, prompt injection detection, and secret redaction. Indexes repositories for AI agents to find patterns and implementations.

no public price· mcp server

▲0☆⚑

@code_context_engine

Local MCP server that indexes codebases with AST-aware chunking and semantic search, reducing AI coding agent token usage by 94%. Works with Claude, Cursor, Copilot, Gemini, and Codex.

free· mcp server

▲0☆⚑

@reporelay

Self-hosted MCP server that indexes Git repositories and provides hybrid semantic search (BM25 + vector) for LLM code context. Supports unlimited repos from any Git host with versioned snapshots and symbol-aware chunking.

no public price· mcp server

▲0☆⚑

@vectorcode

Code repository indexing tool that injects task-relevant context into LLM prompts to improve coding agent output and reduce hallucination on proprietary or niche projects.

no public price· github project

▲0☆⚑

@vector_mcp

Production-grade MCP server for integrating vector databases (ChromaDB, Couchbase, MongoDB, Qdrant, PGVector) into AI agents. Supports RAG workflows with action-routed tools and enterprise security.

no public price· mcp server

▲0☆⚑

@agentic_ai_guide

Agentic RAG is a model that uses AI agents to enhance RAG by dynamically finding and using data from diverse sources for accurate, secure query responses.

no public price· agent framework

▲0☆⚑

@ucalyptus_prem_mcp_server

Integrate seamlessly with Prem AI's powerful features for chat completions and document management. Enhance your AI assistants with Retrieval-Augmented Generation capabilities and real-time streaming responses. Upload and manage documents effortlessly to enrich your interactions.

no public price· mcp server

▲0☆⚑

@haiku_rag

Agentic RAG framework powered by LanceDB, Pydantic AI, and Docling. Supports hybrid search, multimodal retrieval, vision QA, reranking, and analysis skills with MCP server integration.

no public price· github project

▲0☆⚑

see all 25 in the index →

Methodology. Prices are observed daily from vendor pricing pages (headless render + LLM extraction), normalised to monthly USD, and tagged with a confidence level. Figures are conservative — a price is never invented; agents whose pricing can't be verified are counted as unobserved. Agents can pull this same per-niche report programmatically via our MCP server's niche_report tool — see the docs. Last price scan: 2026-07-16 06:14 UTC · 4,921 captures today · liveness probe: 2026-07-16 14:30 UTC.