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SearchMixedbread

Mixedbread

Managed multimodal search over your text, PDFs, images, and video.

Category
Search
Pricing
FREEMIUM
Hosting
Cloud
Platforms
APIWeb
Models
Self-contained (on-device)
Verified
Jun 9, 2026

A fully managed search engine that indexes text, PDFs, tables, images, and video across 100+ languages without hand-tuning embeddings or a multi-stage pipeline. The Berlin team is best known for its open-source mxbai embedding and reranking models, which the hosted product builds on. Access it via dashboard, Python/TypeScript SDKs, or MCP.

Capabilities 6

What it actually does — grouped by capability family.

  • MCP server (secondary capability)
  • Unified search (primary capability)
  • Vector search (secondary capability)
  • Embeddings (secondary capability)
  • RAG pipeline (secondary capability)
  • Document parsing (structured) (secondary capability)

Pros & cons

  • Fully managed, no infra to run
  • Built on strong open mxbai models
  • 100+ language coverage
  • No embedding/pipeline hand-tuning
  • Managed search is closed/commercial
  • Embedding context ~512-token sweet spot
  • Weak at clustering/summarization tasks
  • Smaller player vs incumbents

Tags

View all Search
  • View Exa details
    SearchFREEMIUM

    Exa

    Exa Labs

    Neural search API. Find pages by meaning, not keywords.

    Semantic search engine that indexes the open web with embeddings — pass a description, get matching pages. Strong for research-style queries and find-similar workflows; formerly known as Metaphor.

    Semantic 'find pages like this' retrieval
    Index narrower than Google-scale crawlers
    • semantic-search
    • neural
    • research
    • api
  • View Jina AI details
    SearchFREEMIUMOpen core

    Jina AI

    Jina AI

    Search-foundation APIs — Reader, embeddings, and reranker — for grounding LLMs.

    A suite of search-foundation APIs for retrieval and RAG: a Reader that turns any URL or web search into LLM-ready markdown, multilingual multimodal embeddings, and a reranker. One key spans every service, the Reader is open source, and the embedding models are also released as open weights for self-hosting.

    One key spans Reader, embeddings, reranker
    Acquired by Elastic (Oct 2025); roadmap may shift
    • search
    • embeddings
    • reranker
    • rag
    • +1
  • View Tavily details
    SearchFREEMIUM

    Tavily

    Tavily

    Web search API built for LLM agents and RAG pipelines.

    Search-as-a-tool for LLM agents — returns scrape-friendly results tuned for retrieval rather than ranking. Native integrations across LangChain, LangGraph, CrewAI, and the major agent surfaces.

    Retrieval-tuned, scrape-ready results
    Not a general consumer search
    • search-api
    • agents
    • rag
    • tool-use
  • View Weaviate details
    Vector DBFREEMIUMOpen core

    Weaviate

    Weaviate

    Open-source vector database with built-in vectorisers.

    Cloud-native vector DB that can compute embeddings inline — pass raw text in, store vectors out. Strong hybrid (BM25 + vector) search; self-hostable or managed.

    Hybrid BM25 + vector search
    Resource-heavy at large scale
    • open-source
    • self-hosted
    • hybrid-search
    • rag