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I need to search my documents

Index your own files and notes so an agent can find and cite what's in them (RAG).

65 tools · 18 official

Picked from listings that mention rag, retrieval, vector search, embeddings or knowledge base in their name, description, tags or skills; those in Vector Databases, Research & Knowledge or Memory & State, or with API or MCP access, rank higher.

Best fits · 12

  1. Ragie

    API

    Retrieval API for AI applications. Ingest PDFs, web pages, and files, then query with semantic search. Built-in…

    Verifiedby Ragie · Research & Knowledge · 5 skills · API Key

    Why Ingest PDFs, DOCX, web pages, and 20+ file types into a managed retrieval pipeline

  2. FastGPT

    API · MCP

    Builds AI agents on a visual Flow canvas backed by hybrid-retrieval knowledge bases, workflow and RPA nodes…

    Verifiedby labring · Orchestration, Research & Knowledge · 5 skills · API Key

    Why Hybrid Retrieval Search: Searches multiple reusable knowledge bases with hybrid retrieval and reranking, and tests recall from a single-point search…

  3. Qdrant

    API · CLI

    High-performance open-source vector database. Supports dense, sparse, and multi-vector search. On-premise or cloud.…

    Verifiedby Qdrant · Vector Databases · 5 skills · API Key

    Why Support sparse vectors for keyword-style retrieval alongside semantic dense search

  4. Pinecone

    API

    Fully managed vector database for AI applications. Store and search billions of high-dimensional embeddings with low…

    Verifiedby Pinecone · Vector Databases · 5 skills · API Key

    Why Upsert vectors in real-time with immediate consistency for live knowledge bases

  5. WeKnora

    API · MCP · CLI · Extension

    Turns documents into a queryable knowledge base with RAG question answering, a ReAct agent orchestrating retrieval, MCP…

    VerifiedOfficialby Tencent · Research & Knowledge, Customer Support · 5 skills · API Key

    Why Hybrid Retrieval: Retrieves passages via BM25, dense vectors, GraphRAG and parent-child chunking across pgvector, Elasticsearch, Milvus and Qdrant.

  6. RAGFlow

    API · MCP

    Open-source RAG engine with deep document parsing (tables, charts, images) and an official MCP server. Deploy via…

    Verifiedby InfiniFlow · Research & Knowledge, Infrastructure & Ops · 3 skills · API Key

    Why Knowledge Retrieval: Query ingested knowledge bases via hybrid search (semantic + keyword) with source-cited answers.

  7. LightRAG

    API · CLI

    Builds a graph-based retrieval index over documents so agents can answer questions spanning many sources, served…

    VerifiedFeaturedby HKU Data Science Lab · Memory & State, Research & Knowledge · 4 skills · No auth

    Why Graph Index: Builds an entity and relationship graph from raw documents to support multi-hop retrieval.

  8. Milvus

    API · MCP · CLI

    High-performance open-source vector database with REST API, gRPC, and an official MCP server. Stores billions of…

    Verifiedby Zilliz · Vector Databases · 3 skills · API Key

    Why Hybrid Search: Combine dense vector search with sparse keyword retrieval for accurate RAG pipeline retrieval results.

  9. Oracle AI Database 26ai

    API · MCP · CLI

    World's first AI-native database with agents running inside the kernel. Features no-code Agent Factory, unified vector…

    VerifiedOfficialby Oracle · Infrastructure & Ops · 5 skills · OAuth 2.0

    Why Query structured and unstructured data with unified vector search for multi-modal Retrieval Augmented Generation

  10. MaxKB

    API · CLI

    Open-source enterprise RAG platform for building AI agents. Upload docs, auto-vectorize, and orchestrate multi-step…

    Verifiedby 1Panel · Research & Knowledge, Infrastructure & Ops · 4 skills · API Key

    Why RAG Query: Query a knowledge base with natural language and receive grounded answers with cited source references.

  11. Alibaba Cloud Model Studio

    API

    Serves Qwen and third-party models through DashScope and OpenAI-compatible APIs on Alibaba Cloud, covering text…

    VerifiedOfficialNewby Alibaba Cloud · Language & Translation, Infrastructure & Ops · 5 skills · API Key

    Why Knowledge Base: Builds a knowledge base for retrieval-augmented generation in Model Studio, billed separately from inference.

  12. Voyage AI (MongoDB)

    API

    Provides Voyage AI text, contextualized chunk, and multimodal embedding models plus rerankers through a MongoDB-hosted…

    VerifiedOfficialNewby MongoDB · Vector Databases, Infrastructure & Ops · 4 skills · API Key

    Why Text Embeddings: Converts text into vector embeddings for general-purpose and multilingual retrieval.

See all 65 on Browse, with filters

Official · 18

The ones published by the company behind the product.

See all 18 official on Browse

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/tasks/search-my-documents
I need to search my documents · 65 fit · 18 official · keywords: rag, retrieval, vector search, embeddings, knowledge base · categories: vector-databases, research, memory-state · access: api+mcp
Index your own files and notes so an agent can find and cite what's in them (RAG).
best fits
ragieapiIngest PDFs, DOCX, web pages, and 20+ file types into a managed retrieval pipelinefastgptapi+mcpHybrid Retrieval Search: Searches multiple reusable knowledge bases with hybrid retrieval and reranking, and tests recall from a single-point search…qdrantapi+cliSupport sparse vectors for keyword-style retrieval alongside semantic dense searchpineconeapiUpsert vectors in real-time with immediate consistency for live knowledge basesweknoraapi+mcp+cli+browser-extensionHybrid Retrieval: Retrieves passages via BM25, dense vectors, GraphRAG and parent-child chunking across pgvector, Elasticsearch, Milvus and Qdrant.ragflowapi+mcpKnowledge Retrieval: Query ingested knowledge bases via hybrid search (semantic + keyword) with source-cited answers.lightragapi+cliGraph Index: Builds an entity and relationship graph from raw documents to support multi-hop retrieval.milvusapi+mcp+cliHybrid Search: Combine dense vector search with sparse keyword retrieval for accurate RAG pipeline retrieval results.oracle-ai-database-26aiapi+mcp+cliQuery structured and unstructured data with unified vector search for multi-modal Retrieval Augmented Generationmaxkbapi+cliRAG Query: Query a knowledge base with natural language and receive grounded answers with cited source references.alibaba-model-studioapiKnowledge Base: Builds a knowledge base for retrieval-augmented generation in Model Studio, billed separately from inference.voyage-aiapiText Embeddings: Converts text into vector embeddings for general-purpose and multilingual retrieval.
official
weknora, oracle-ai-database-26ai, alibaba-model-studio, voyage-ai, algolia, jina-reader, cohere, you-com-search-api, redis-mcp, gaia-amd, mongodb-mcp, supabase-mcp, cloudflare-workers-ai, zvec, tencentdb-agent-memory, elasticsearch-mcp, exa-ai, funes
related tasks
/tasks/give-an-agent-memory34 fitgive an agent long-term memory/tasks/search-the-web27 fitsearch the web/tasks/read-pdfs-and-documents28 fitread PDFs and documents/tasks/work-in-notion-and-docs10 fitwork in Notion, Confluence or Drive
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/browse?task=search-my-documentsall 65, with filters/tasksevery task/api/tasks/search-my-documentsthis task as JSONGET · no auth