Which operations does the server expose?

It exposes retrieval, extraction, and deep-research operations.

What input does document extraction accept?

The extract operation accepts a base64-encoded document and its content type.

Can deep research use web search?

Yes. The deep-research operation includes a webSearch option.

Which MCP clients are documented as compatible?

The README provides configuration examples for Claude, Windsurf, Cursor, and Cline.

Vectorize MCP Server

vector-searchdocument-extractiondeep-researchtext-chunking

MCP server for Vectorize document retrieval, private deep research, file-to-Markdown extraction, and text chunking.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to Cursor Add to VS Code

Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag — we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON ▾

Client Config & Setup

Choose your client or environment

Target File:~/Library/Application Support/Claude/claude_desktop_config.json

claude_desktop_config.json

{
  "mcpServers": {
    "vectorize-io-vectorize-mcp-server": {
      "command": "npx",
      "args": [
        "-y",
        "@vectorize-io/vectorize-mcp-server@latest"
      ]
    }
  }
}

💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Overview

This server connects MCP clients to Vectorize retrieval and extraction APIs. Use it to search indexed documents, generate private deep-research reports, or convert files into chunked Markdown. It requires a Vectorize organization ID, token, and pipeline ID.

Use cases

Retrieve documents with vector search

Generate private deep-research reports

Extract text from PDF and other files

Convert documents to chunked Markdown

Key features

Vector document retrieval

Private deep research generation

File-to-Markdown text extraction

Text chunking

Optional web search for deep research

Capabilities & Tool Schemas

Inspect callable tools, capabilities, and parameters exposed to AI agents by Vectorize MCP Server.

Extracted Tool Capabilities

Vector document retrieval

Private deep research generation

File-to-Markdown text extraction

Text chunking

Optional web search for deep research

Documentation Overview

Vectorize MCP Server

A Model Context Protocol (MCP) server implementation that integrates with Vectorize for advanced Vector retrieval and text extraction.

Installation

Running with npx

server.ts

export VECTORIZE_ORG_ID=YOUR_ORG_ID
export VECTORIZE_TOKEN=YOUR_TOKEN
export VECTORIZE_PIPELINE_ID=YOUR_PIPELINE_ID

npx -y @vectorize-io/vectorize-mcp-server@latest

VS Code Installation

For one-click installation, click one of the install buttons below:

Manual Installation

For the quickest installation, use the one-click install buttons at the top of this section.

To install manually, add the following JSON block to your User Settings (JSON) file in VS Code. You can do this by pressing Ctrl + Shift + P and typing Preferences: Open User Settings (JSON).

config.json

{
  "mcp": {
    "inputs": [
      {
        "type": "promptString",
        "id": "org_id",
        "description": "Vectorize Organization ID"
      },
      {
        "type": "promptString",
        "id": "token",
        "description": "Vectorize Token",
        "password": true
      },
      {
        "type": "promptString",
        "id": "pipeline_id",
        "description": "Vectorize Pipeline ID"
      }
    ],
    "servers": {
      "vectorize": {
        "command": "npx",
        "args": ["-y", "@vectorize-io/vectorize-mcp-server@latest"],
        "env": {
          "VECTORIZE_ORG_ID": "${input:org_id}",
          "VECTORIZE_TOKEN": "${input:token}",
          "VECTORIZE_PIPELINE_ID": "${input:pipeline_id}"
        }
      }
    }
  }
}

Optionally, you can add the following to a file called .vscode/mcp.json in your workspace to share the configuration with others:

config.json

{
  "inputs": [
    {
      "type": "promptString",
      "id": "org_id",
      "description": "Vectorize Organization ID"
    },
    {
      "type": "promptString",
      "id": "token",
      "description": "Vectorize Token",
      "password": true
    },
    {
      "type": "promptString",
      "id": "pipeline_id",
      "description": "Vectorize Pipeline ID"
    }
  ],
  "servers": {
    "vectorize": {
      "command": "npx",
      "args": ["-y", "@vectorize-io/vectorize-mcp-server@latest"],
      "env": {
        "VECTORIZE_ORG_ID": "${input:org_id}",
        "VECTORIZE_TOKEN": "${input:token}",
        "VECTORIZE_PIPELINE_ID": "${input:pipeline_id}"
      }
    }
  }
}

Configuration on Claude/Windsurf/Cursor/Cline

config.json

{
  "mcpServers": {
    "vectorize": {
      "command": "npx",
      "args": ["-y", "@vectorize-io/vectorize-mcp-server@latest"],
      "env": {
        "VECTORIZE_ORG_ID": "your-org-id",
        "VECTORIZE_TOKEN": "your-token",
        "VECTORIZE_PIPELINE_ID": "your-pipeline-id"
      }
    }
  }
}

Tools

Retrieve documents

Perform vector search and retrieve documents (see official API):

config.json

{
  "name": "retrieve",
  "arguments": {
    "question": "Financial health of the company",
    "k": 5
  }
}

Text extraction and chunking (Any file to Markdown)

Extract text from a document and chunk it into Markdown format (see official API):

config.json

{
  "name": "extract",
  "arguments": {
    "base64document": "base64-encoded-document",
    "contentType": "application/pdf"
  }
}

Deep Research

Generate a Private Deep Research from your pipeline (see official API):

config.json

{
  "name": "deep-research",
  "arguments": {
    "query": "Generate a financial status report about the company",
    "webSearch": true
  }
}

Development

Terminal

npm install
npm run dev

Release

Change the package.json version and then:

bash

git commit -am "x.y.z"
git tag x.y.z
git push origin
git push origin --tags

Contributing

Fork the repository
Create your feature branch
Submit a pull request

Read the full README →View source on GitHub →

Related MCP Servers

View all in Search & Data Extraction View all alternatives

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars

111

Stargazers on the source repository.

Last commit

8d ago

Most recent push to the default branch.

Directory activity

2 views

Config copies, upvotes, and views on AllMCPs.

Reviews

No reviews yet — be the first to share how this listing worked for you.

Frequently Asked Questions about Vectorize MCP Server

It requires VECTORIZE_ORG_ID, VECTORIZE_TOKEN, and VECTORIZE_PIPELINE_ID.

AllMCPs Directory Badge

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Vectorize MCP Server AllMCPs Directory Badge

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Technical Specs & Signals

CategorySearch & Data Extraction

PricingBring your own API key (usage-based cost)

10/11 checks healthy over the last 33d

55Quality signal: Good · 55/100How this signal is calculated ▾

Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20

Documentation & tools23/30

Adoption & activity8/15

Community engagement0/10

A guidance signal from public completeness & health data — not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 22d ago via OSV.dev · @vectorize-io/vectorize-mcp-server@latest (npm)

★ Featured

AllMCPs Server

The official MCP server for AllMCPs.com - submit and manage tools directly from your AI. The open directory for MCP servers. Connect Claude, Cursor, Windsurf, and AI agents to databases, tools, files, and APIs. Explore 10,000+ servers. AllMCPs is the premier, open directory for discovering, evaluating, and installing Model Context Protocol (MCP) servers to equip AI agents and LLMs with real-world superpowers.

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Explore more

More in 🔎 Search & Data Extraction →Best MCP servers for Web Search & Scraping →Alternatives to Vectorize MCP Server →Install in Claude Desktop Install in Cursor Install in VS Code

Vectorize MCP Server

vector-searchdocument-extractiondeep-researchtext-chunking

MCP server for Vectorize document retrieval, private deep research, file-to-Markdown extraction, and text chunking.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.

Add to Cursor Add to VS Code

Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag — we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON ▾

Client Config & Setup

Choose your client or environment

Target File:~/Library/Application Support/Claude/claude_desktop_config.json

claude_desktop_config.json

{
  "mcpServers": {
    "vectorize-io-vectorize-mcp-server": {
      "command": "npx",
      "args": [
        "-y",
        "@vectorize-io/vectorize-mcp-server@latest"
      ]
    }
  }
}

💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Overview

Use cases

Retrieve documents with vector search

Generate private deep-research reports

Extract text from PDF and other files

Convert documents to chunked Markdown

Key features

Vector document retrieval

Private deep research generation

File-to-Markdown text extraction

Text chunking

Optional web search for deep research

Capabilities & Tool Schemas

Inspect callable tools, capabilities, and parameters exposed to AI agents by Vectorize MCP Server.

Extracted Tool Capabilities

Vector document retrieval

Private deep research generation

File-to-Markdown text extraction

Text chunking

Optional web search for deep research

Documentation Overview

Vectorize MCP Server

A Model Context Protocol (MCP) server implementation that integrates with Vectorize for advanced Vector retrieval and text extraction.

Installation

Running with npx

server.ts

export VECTORIZE_ORG_ID=YOUR_ORG_ID
export VECTORIZE_TOKEN=YOUR_TOKEN
export VECTORIZE_PIPELINE_ID=YOUR_PIPELINE_ID

npx -y @vectorize-io/vectorize-mcp-server@latest

VS Code Installation

For one-click installation, click one of the install buttons below:

Manual Installation

For the quickest installation, use the one-click install buttons at the top of this section.

To install manually, add the following JSON block to your User Settings (JSON) file in VS Code. You can do this by pressing Ctrl + Shift + P and typing Preferences: Open User Settings (JSON).

config.json

{
  "mcp": {
    "inputs": [
      {
        "type": "promptString",
        "id": "org_id",
        "description": "Vectorize Organization ID"
      },
      {
        "type": "promptString",
        "id": "token",
        "description": "Vectorize Token",
        "password": true
      },
      {
        "type": "promptString",
        "id": "pipeline_id",
        "description": "Vectorize Pipeline ID"
      }
    ],
    "servers": {
      "vectorize": {
        "command": "npx",
        "args": ["-y", "@vectorize-io/vectorize-mcp-server@latest"],
        "env": {
          "VECTORIZE_ORG_ID": "${input:org_id}",
          "VECTORIZE_TOKEN": "${input:token}",
          "VECTORIZE_PIPELINE_ID": "${input:pipeline_id}"
        }
      }
    }
  }
}

Optionally, you can add the following to a file called .vscode/mcp.json in your workspace to share the configuration with others:

config.json

{
  "inputs": [
    {
      "type": "promptString",
      "id": "org_id",
      "description": "Vectorize Organization ID"
    },
    {
      "type": "promptString",
      "id": "token",
      "description": "Vectorize Token",
      "password": true
    },
    {
      "type": "promptString",
      "id": "pipeline_id",
      "description": "Vectorize Pipeline ID"
    }
  ],
  "servers": {
    "vectorize": {
      "command": "npx",
      "args": ["-y", "@vectorize-io/vectorize-mcp-server@latest"],
      "env": {
        "VECTORIZE_ORG_ID": "${input:org_id}",
        "VECTORIZE_TOKEN": "${input:token}",
        "VECTORIZE_PIPELINE_ID": "${input:pipeline_id}"
      }
    }
  }
}

Configuration on Claude/Windsurf/Cursor/Cline

config.json

{
  "mcpServers": {
    "vectorize": {
      "command": "npx",
      "args": ["-y", "@vectorize-io/vectorize-mcp-server@latest"],
      "env": {
        "VECTORIZE_ORG_ID": "your-org-id",
        "VECTORIZE_TOKEN": "your-token",
        "VECTORIZE_PIPELINE_ID": "your-pipeline-id"
      }
    }
  }
}

Tools

Retrieve documents

Perform vector search and retrieve documents (see official API):

config.json

{
  "name": "retrieve",
  "arguments": {
    "question": "Financial health of the company",
    "k": 5
  }
}

Text extraction and chunking (Any file to Markdown)

Extract text from a document and chunk it into Markdown format (see official API):

config.json

{
  "name": "extract",
  "arguments": {
    "base64document": "base64-encoded-document",
    "contentType": "application/pdf"
  }
}

Deep Research

Generate a Private Deep Research from your pipeline (see official API):

config.json

{
  "name": "deep-research",
  "arguments": {
    "query": "Generate a financial status report about the company",
    "webSearch": true
  }
}

Development

Terminal

npm install
npm run dev

Release

Change the package.json version and then:

bash

git commit -am "x.y.z"
git tag x.y.z
git push origin
git push origin --tags

Contributing

Fork the repository
Create your feature branch
Submit a pull request

Read the full README →View source on GitHub →

Related MCP Servers

View all in Search & Data Extraction View all alternatives

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars

111

Stargazers on the source repository.

Last commit

8d ago

Most recent push to the default branch.

Directory activity

2 views

Config copies, upvotes, and views on AllMCPs.

Reviews

No reviews yet — be the first to share how this listing worked for you.

Frequently Asked Questions about Vectorize MCP Server

It requires VECTORIZE_ORG_ID, VECTORIZE_TOKEN, and VECTORIZE_PIPELINE_ID.

AllMCPs Directory Badge

Full Badge Customizer

Showcase your server listing on GitHub or your project documentation. Embed this dynamic SVG badge to highlight official listing status and live engagement.

Badge Style:

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Markdown (GitHub README)

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<a href="https://allmcps.com/mcp/vectorize-io-vectorize-mcp-server"><img src="https://allmcps.com/api/badge/vectorize-io-vectorize-mcp-server?style=directory" alt="Vectorize MCP Server on AllMCPs" /></a>

Technical Specs & Signals

CategorySearch & Data Extraction

PricingBring your own API key (usage-based cost)

10/11 checks healthy over the last 33d

55Quality signal: Good · 55/100How this signal is calculated ▾

Server availabilityNot measured

Not scored for repo-hosted servers — we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20

Documentation & tools23/30

Adoption & activity8/15

Community engagement0/10

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 22d ago via OSV.dev · @vectorize-io/vectorize-mcp-server@latest (npm)

★ Featured

AllMCPs Server

Explore Server →

Own this project?

Free dofollow backlink: add your website and place the AllMCPs badge on it — no claim needed. We detect it automatically and keep it verified as long as the badge stays live.

Claim & get free dofollow

Share & Embed

Add our SVG badge (dark/light directory styles) or embeddable widget to your site.

Explore more

More in 🔎 Search & Data Extraction →Best MCP servers for Web Search & Scraping →Alternatives to Vectorize MCP Server →Install in Claude Desktop Install in Cursor Install in VS Code