Vectorize
Official
by vectorize-io
# Vectorize MCP Server
A Model Context Protocol (MCP) server implementation that integrates with [Vectorize](https://vectorize.io/) for advanced Vector retrieval and text extraction.
<a href="https://glama.ai/mcp/servers/pxwbgk0kzr">
<img width="380" height="200" src="https://glama.ai/mcp/servers/pxwbgk0kzr/badge" alt="Vectorize MCP server" />
</a>
## Installation
### Running with npx
```bash
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
```
## Configuration on Claude/Windsurf/Cursor/Cline
```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](https://docs.vectorize.io/api/api-pipelines/api-retrieval)):
```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](https://docs.vectorize.io/api/api-extraction)):
```json
{
"name": "extract",
"arguments": {
"base64document": "base64-encoded-document",
"contentType": "application/pdf"
}
}
```
### Deep Research
Generate a Private Deep Research from your pipeline (see official [API](https://docs.vectorize.io/api/api-pipelines/api-deep-research)):
```json
{
"name": "deep-research",
"arguments": {
"query": "Generate a financial status report about the company",
"webSearch": true
}
}
```
## Development
```bash
npm install
npm run dev
```
### Contributing
1. Fork the repository
2. Create your feature branch
3. Submit a pull request