Vectorize

# 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> ## Features ## Installation ### Running with npx ```bash export VECTORIZE_ORG_ID=YOUR_ORG_ID export VECTORIZE_TOKEN=YOUR_TOKEN npx -y @vectorize-io/vectorize-mcp-server ``` ## Configuration on Claude/Windsurf ```json { "mcpServers": { "vectorize": { "command": "npx", "args": ["-y", "@vectorize-io/vectorize-mcp-server"], "env": { "VECTORIZE_ORG_ID": "your-org-id", "VECTORIZE_TOKEN": "your-token" } } } } ``` ## 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": { "pipeline": "your-pipeline-id", "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": { "pipelineId": "your-pipeline-id", "query": "Generate a financial status report about the company", "webSearch": true } } ``` ## Development ```bash # Install dependencies npm install # Build npm run build ``` ### Contributing 1. Fork the repository 2. Create your feature branch 3. Submit a pull request