The request "rag" does not name a product, so these are candidate tools for retrieval-augmented generation. Established options with RAG-specific features include Amazon Bedrock with Knowledge Bases 3, Redis with vector search for retrieval 2, and LangChain for building agents over retrieved data 6; Mastra 4 and FalkorDB's GraphRAG database 8 are further options depending on stack.
- 1
Amazon Bedrockamazon.comverified and signed
Builds generative AI applications on Amazon Bedrock, covering RAG with Knowledge Bases, model invocation and Guardrails 3.
official:SDK · @aws-sdk/client-bedrock-runtimerepository · bedrock-agentcore-sdk-pythonskill · amazon-bedrockSDK · bedrock-agentcore
for agents: amazon-bedrock · CreateGuardrail · CreatePromptRouter
- 2
Redisredis.iofound in code, not yet checked
Provides Redis-powered vector search to retrieve the most 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
An open agent platform for building agents and integrating language models, used to assemble RAG pipelines 6.
+163 community tools built for it
for agents: langchain · langchain · langgraph
- 4
Mastramastra.aiverified and signed
A TypeScript framework providing agents, tools, memory and workflows for AI applications, which can be used to build RAG flows 4.
+13 community tools built for it
for agents: rag · ralph-plan · mastra
- 5
FalkorDBfalkordb.comfound in code, not yet checked
A graph database for GraphRAG, offering OpenCypher queries over knowledge graphs to ground GenAI answers 8.
official:MCP server · com.falkordb/QueryWeaver+4 community tools built for it
for agents: index_repo · query_graph · search_code
Sources
- 2Redis - Real-time data for agents & appsredis.io · read 2026-10-29
- 3amazon-bedrock — aws/agent-toolkit-for-awsskills.sh · read 2026-10-29
- 4TypeScript AI Framework for Agents and Apps | Mastramastra.ai · read 2026-10-29
- 6LangChain: the open agent platform to own your intelligencelangchain.com · read 2026-10-29
- 8FalkorDB Documentation | Graph Database for GraphRAG & GenAI - FalkorDB Docsdocs.falkordb.com · read 2026-10-29
For agents: the 10 actions behind this answer
· 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.
analyze_rag_quality · docs found in code, not yet checked
Analyze a documentation page for RAG retrieval quality.
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
rag · @mastra/core verified and signed
structured-autonomy-generate · structured-autonomy-generate verified and signed
Structured Autonomy Implementation Generator Prompt
langchain · Docs by LangChain verified and signed
Use when building AI agents, integrating language models with
· 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.
index_repo · code-graph found in code, not yet checked
Implementation for the ``index_repo`` MCP tool.
· 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.