• ENTITIES
  • TOPICS
  • HUMAN
  • OUTPUT

How to extract entities and topics with your AI

Connect MeaningCloud to your AI client once. Your agent then scans your text to pull out the specific details you need.

Ask AI about this page

Short answer

How can I pull names and topics from my documents?

Your AI uses MeaningCloud to scan text and isolate specific people, locations, and core subjects. This turns messy reports into organized lists of entities and themes. You get a structured breakdown of the most important information in the text.

Where your data lands.

The results of your extraction.

The AI processes your text and organizes the findings into these categories.

ENTITIES

Identified people and places

The AI pulls out specific names of individuals and geographic locations. You get a clean list of who and where is mentioned in the text.

TOPICS

Core subject matter

The agent identifies the main themes and concepts discussed. This helps you understand the gist of a long report without reading every word.

HUMAN

Manual verification

You review the extracted lists to ensure the context is correct. The AI provides the raw data, but you decide if the entities are relevant to your goal.

OUTPUT

Structured summaries

The extracted topics and entities are ready to be used in your notes or databases. You can ask your agent to format these into a table or a bulleted list.

The workflow

What your AI does when the text arrives.

The AI handles the heavy lifting of reading and categorizing the content.

  1. Scan text

    Your agent reads the provided article or report to find meaningful patterns.

    extract_topics

  2. Isolate entities

    The AI picks out specific names, organizations, and locations from the prose.

    extract_topics

  3. Identify themes

    The agent determines the primary topics that define the document's purpose.

    extract_topics

  4. Organize findings

    The AI presents the extracted data in a way that makes sense for your specific request.

    extract_topics

Try it

Copy these to start.

Use these prompts once you have connected MeaningCloud.

Starting points

Swap the bracketed text for your actual file names or URLs.

MeaningCloud Connector

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

Connector linkhttps://edge.vinkius.com/vk_preview_ci7wUEXUooIV5O30n0FSRcWOY6xykLKoUj6B44uN/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 — MeaningCloud capabilities are ready to use.
Configuration · claude_desktop_config.jsonCopy
{
  "mcpServers": {
    "meaningcloud-mcp": {
      "url": "https://edge.vinkius.com/vk_preview_ci7wUEXUooIV5O30n0FSRcWOY6xykLKoUj6B44uN/mcp"
    }
  }
}
Copy into chat04

  • Extract all the key topics from this report: [paste text or file]

  • Who are the main people mentioned in this article? [paste URL]

  • List all the locations found in this document: [paste text]

  • Summarize the main concepts in this PDF using the extracted topics: [paste file]

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

Start here

Connect MeaningCloud once, then ask.

Just click the link to connect. Your login stays encrypted, and you can immediately start asking your agent to process text.

Connect MeaningCloud to your AI

FAQ

How this task behaves.

  • 01

    Can the AI edit my original document?

    No. The AI only reads the text to extract information. It does not change your files.

  • 02

    Does the AI automatically save these topics to a spreadsheet?

    No. The AI extracts the topics into the chat. You must manually copy them or ask the agent to format them for a spreadsheet.

  • 03

    Can it extract topics from images?

    No. The tool works on text data provided to the agent.

  • 04

    Will it identify every single person mentioned?

    The AI identifies significant entities, but it might miss obscure names if they lack enough context in the text.

  • 05

    How does it handle very long reports?

    The agent reads the text through the connector to find the most relevant themes and entities throughout the document.

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

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