• PRECISION
  • RELEVANCE
  • ACCURACY
  • HUMAN

How to improve RAG retrieval accuracy with your AI

Connect Jina AI to your agent to fix broken retrieval. Your AI stops guessing and starts finding the specific context it needs.

Ask AI about this page

Short answer

How do I make my RAG retrieval more accurate?

You need to move beyond simple vector searches. By using semantic segmentation to break up text and reranking to prioritize the best matches, your agent finds the right context every time. This process eliminates the noise that usually causes hallucinations.

The results you get.

What your agent achieves.

The AI refines your data so the agent only sees what matters.

PRECISION

Clean context chunks

The AI uses semantic segmentation to split documents at logical points. You get meaningful pieces of text instead of arbitrary character counts.

RELEVANCE

Top-tier results

Reranking ensures the most useful information moves to the top of the list. Your agent sees the best data first.

ACCURACY

Fewer hallucinations

When the context is precise and relevant, your agent stops making things up. It stays grounded in the actual data provided.

HUMAN

Review the logic

You decide if the segmented chunks or the reranked order meet your specific needs. The AI handles the heavy lifting, but you keep control.

The workflow

What your AI does when the data arrives.

The AI processes your raw documents through a two-stage refinement pipeline.

  1. Logical splitting

    Instead of cutting text at arbitrary character counts, the AI identifies semantic boundaries. This creates cohesive chunks that preserve meaning.

    segment_content

  2. Contextual sorting

    The AI evaluates the relationship between the user query and the available chunks. It reorders them so the strongest matches are most prominent.

    rerank_documents

  3. Context delivery

    The most relevant segments are passed directly to your agent's prompt. This ensures the LLM has the exact information required to answer.

    rerank_documents

  4. Final grounding

    The agent uses the refined context to generate a response. This minimizes the chance of the agent pulling from irrelevant parts of the document.

    segment_contentrerank_documents

Try it

Copy these to start.

Use these prompts to trigger the retrieval process once you connect Jina AI.

Starting points

Replace the bracketed text with your specific file names or data sources.

Jina AI Connector

You're all set. Choose your MCP client and follow the setup instructions.

Connector linkhttps://edge.vinkius.com/vk_preview_wGxcPgjZXIdTEE0fANy2lSVGB9dv2CeDi7TDmWBG/mcp

Claude Desktop

Follow the steps below to connect in seconds.

  1. 1In Claude Desktop, open Settings → Connectors.
  2. 2Click “Add custom connector” and paste the connector link above as the remote MCP server URL.
  3. 3Click Add and start a new chat — Jina AI capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "jina-ai-search-foundation-llm-grounding-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_wGxcPgjZXIdTEE0fANy2lSVGB9dv2CeDi7TDmWBG/mcp"
    }
  }
}
Copy into chat04

  • Segment the content in my 'technical_manual.pdf' file and find the section on error codes.

  • Rerank the documents in my 'customer_support_logs' folder to find the most relevant troubleshooting steps for a login failure.

  • Use the segmented chunks from 'project_specs.docx' to answer why the deployment failed.

  • Rerank the snippets from my 'legal_contracts' directory to find the clause regarding termination notice.

  • Claude
  • ChatGPT
  • Cursor
  • VS Code
  • Windsurf
  • Claude Code
  • JetBrains
  • Cline

Start here

Connect Jina AI once, then ask.

Just click the link to connect your account. Your credentials stay encrypted, and you can start using these tools in your favorite MCP client immediately.

Connect Jina AI to your AI

FAQ

How this task behaves.

  • 01

    Can the AI rewrite my original documents?

    No. The tools only read and segment your existing data to improve retrieval; they do not modify your source files.

  • 02

    Does this replace my vector database?

    No. This works alongside your existing retrieval system to refine the results your agent actually sees.

  • 03

    Will the AI delete any of my files?

    No. The tools are read-only operations for segmentation and reranking.

  • 04

    How does semantic segmentation differ from fixed-length chunking?

    Fixed-length chunking cuts text at arbitrary character counts, often splitting sentences. Semantic segmentation looks for natural breaks in meaning to keep context intact.

  • 05

    Can I manually choose which chunks to rerank?

    The AI performs the reranking based on the query, but you can always instruct your agent to look at specific segments you've identified.

  • More questions about Jina AI? The Connector page answers them. See everything the Jina AI Connector can do

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