# Vectorize

> Use this tool when you need to leverage advanced vector search, text extraction, and deep research capabilities to analyze documents and generate comprehensive insights. It solves problems in knowledge management, document analysis, and research workflows by providing a bridge to vector database services. The tool accepts organization IDs and API tokens as inputs and outputs relevant documents, Markdown-formatted text, and in-depth analyses.

Canonical page: https://skillsregistry.net/skills/vectorize-io  
JSON: https://api.skillsregistry.net/v1/skills/vectorize-io

## Description

Vectorize MCP Server provides a bridge between Claude and Vectorize.io's vector database services, enabling advanced retrieval, text extraction, and deep research capabilities. Built with TypeScript, it exposes three primary tools: vector search for retrieving relevant documents from pipelines, text extraction for converting various document formats to Markdown, and deep research for generating comprehensive analyses from document collections. The implementation handles authentication through organization IDs and API tokens, making it particularly valuable for knowledge management, document analysis, and research workflows that require sophisticated vector search capabilities without leaving the conversation interface.

## Trust

- **Trust score (0–1):** 0.97
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** database
- **Updated:** 2026-09-19

## Source

- **Source listing:** [PulseMCP](https://www.pulsemcp.com/servers/vectorize-io)
- **Repository:** <https://github.com/vectorize-io/vectorize-mcp-server>

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "vectorize-io"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/vectorize-io` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/vectorize-io/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt