The request names no specific product, so these are candidates for building RAG. Amazon Bedrock offers RAG with Knowledge Bases 1, Redis provides vector search for retrieval 2, and LangChain and Mastra are frameworks for building agents with retrieval 56. The sources do not show how well each fits a particular stack, so the choice depends on which platform and constraints you have.
A question back: Which language or platform will you build in (for example Python, TypeScript, or AWS), and do you need a managed cloud service or a self-hosted framework?
- 1
Amazon Bedrockamazon.comverified and signed
Builds generative AI applications with RAG through Knowledge Bases, alongside model invocation and Guardrails 1.
official:SDK · @aws-sdk/client-bedrock-runtimerepository · bedrock-agentcore-sdk-pythonskill · amazon-bedrockSDK · bedrock-agentcore
for agents: amazon-bedrock · CreateGuardrail · CreatePromptRouter
- 2
Redis Enterpriseredis.iofound in code, not yet checked
Provides Redis-powered vector search to retrieve relevant structured and unstructured data as context for models 2.
official:MCP server · Redis MCP ServerSDK · redisCLI · memtier_benchmarkrepository · agent-memory-serverskill · redis-core+39 community tools built for it
for agents: analyze_rag_quality · redis-search · redis-semantic-cache
- 3
LangChainlangchain.comverified and signed
Open agent engineering platform for building agents and integrating language models, with retrieval patterns available 5.
+163 community tools built for it
for agents: langchain · langchain · langgraph
- 4
Mastramastra.aiverified and signed
Open-source TypeScript framework providing agents, memory, tools and workflows for building RAG-style AI applications 6.
+13 community tools built for it
for agents: rag · ralph-plan · embeddings
Sources
- 1amazon-bedrock — aws/agent-toolkit-for-awsskills.sh · read 2026-10-29
- 2Redis - Real-time data for agents & appsredis.io · read 2026-10-29
- 5LangChain: the open agent platform to own your intelligencelangchain.com · read 2026-10-29
- 6TypeScript AI Framework for Agents and Apps | Mastramastra.ai · read 2026-10-29
For agents: the 10 actions behind this answer
amazon-bedrock · amazon-bedrock verified and signed
Builds generative AI applications on Amazon Bedrock. Covers model invocation (Converse API, InvokeModel), RAG with Knowledge Bases, Bedrock Agents, Guardrails, and AgentCore (including the Harness managed agent loop). Applies when invoking models, setting up Knowledge Bases, creating agents, applyin
analyze_rag_quality · docs found in code, not yet checked
Analyze a documentation page for RAG retrieval quality.
structured-autonomy-generate · structured-autonomy-generate verified and signed
Structured Autonomy Implementation Generator Prompt
· ai·rete·rag website read, tools not yet checked
ai·rete·rag pairs a Rete rule engine with retrieval-augmented generation: rules decide the what, auditable and repeatable; retrieval explains the why, grounded in your own documents.
langchain · Docs by LangChain verified and signed
Use when building AI agents, integrating language models with
rag · @mastra/core verified and signed
· Apple RAG MCP website read, tools not yet checked
Search official Apple developer docs and WWDC transcripts through MCP, with RAG retrieval and Jev relevance ranking.
· S1 website read, tools not yet checked
Real-time web search, RAG retrieval, crawling, and structured data extraction for AI agents and LLMs. 100 free credits via REST API, MCP server, and CLI.
· AgentsKit website read, tools not yet checked
Build agents without gluing many libraries together. A composable TypeScript foundation for runtime, tools, memory, RAG, and chat interfaces.
· SGLang website read, tools not yet checked
SGLang powers fast, scalable inference for large language and multimodal models. Open-source serving framework with state-of-the-art performance.
Labels are the instruments' verdict and are never changed by ranking. Agents and robots get this same answer as JSON at /api/v1/find?q=…&answer=1 and through the MCP server.