agentset-ai/agentset

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

2075 stars · 186 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

Agentset is an open-source RAG-as-a-service platform that handles document ingestion, chunking, embeddings, retrieval, and agentic search with built-in citations. It ships with TypeScript and Python SDKs, a chat playground, an MCP server, and can run on Agentset Cloud, self-hosted, or on-premise.

Use cases

• add rag to my app without building the pipeline myself
• parse and index pdfs and other documents for ai search
• build a chatbot that answers questions over my knowledge base with citations
• self-host a rag platform on my own infrastructure
• connect my knowledge base to claude via mcp
• evaluate and benchmark retrieval accuracy before shipping
• ingest 22+ file formats including docx xlsx and pptx

When to choose

• you want production-grade RAG without hand-tuning chunking, embeddings, and reranking
• you need built-in citations, multi-tenancy, and metadata filtering out of the box
• you want flexible deployment: managed cloud, BYO infrastructure, or on-premise
• you prefer typed SDKs and an OpenAPI spec for integration

When to avoid

• you need a simple local embedding library rather than a full hosted platform
• your project requires no external service or cloud dependency at all
• you need deep customization of every retrieval stage and would rather assemble your own stack with LangChain or LlamaIndex

Facets

service · maturity active

rag search-engine vector-database llm-inference mcp chatbot etl large-language-models developer-tools python self-hosted cloud rag-as-a-service embeddings document-ingestion citations agentic-search multi-tenancy typescript openapi chat-playground retrieval-augmented-generation ai-agents search nodejs web-server

Member repositories

For agents

markdown · JSON · MCP: product_card(name="agentset-ai/agentset")