{
  "display_name": "Vectorize MCP Server",
  "repository": {
    "type": "git",
    "url": "https://github.com/vectorize-io/vectorize-mcp-server"
  },
  "homepage": "https://vectorize.io/",
  "author": {
    "name": "vectorize-io"
  },
  "license": "MIT",
  "tags": [
    "vector retrieval",
    "text extraction"
  ],
  "arguments": {
    "VECTORIZE_ORG_ID": {
      "description": "Vectorize Organization ID",
      "required": true,
      "example": "your-org-id"
    },
    "VECTORIZE_TOKEN": {
      "description": "Vectorize Token",
      "required": true,
      "example": "your-token"
    },
    "VECTORIZE_PIPELINE_ID": {
      "description": "Vectorize Pipeline ID",
      "required": true,
      "example": "your-pipeline-id"
    }
  },
  "installations": {
    "npm": {
      "type": "npm",
      "command": "npx",
      "args": [
        "-y",
        "@vectorize-io/vectorize-mcp-server@latest"
      ],
      "package": "@vectorize-io/vectorize-mcp-server",
      "env": {
        "VECTORIZE_ORG_ID": "${VECTORIZE_ORG_ID}",
        "VECTORIZE_TOKEN": "${VECTORIZE_TOKEN}",
        "VECTORIZE_PIPELINE_ID": "${VECTORIZE_PIPELINE_ID}"
      },
      "description": "Run with npx",
      "recommended": true
    }
  },
  "examples": [
    {
      "title": "Retrieve documents",
      "description": "Perform vector search and retrieve documents",
      "prompt": "{\"name\":\"retrieve\",\"arguments\":{\"question\":\"Financial health of the company\",\"k\":5}}"
    },
    {
      "title": "Text extraction and chunking",
      "description": "Extract text from a document and chunk it into Markdown format",
      "prompt": "{\"name\":\"extract\",\"arguments\":{\"base64document\":\"base64-encoded-document\",\"contentType\":\"application/pdf\"}}"
    },
    {
      "title": "Deep Research",
      "description": "Generate a Private Deep Research from your pipeline",
      "prompt": "{\"name\":\"deep-research\",\"arguments\":{\"query\":\"Generate a financial status report about the company\",\"webSearch\":true}}"
    }
  ],
  "name": "vectorize-mcp-server",
  "description": "A Model Context Protocol (MCP) server implementation that integrates with [Vectorize](https://vectorize.io/) for advanced Vector retrieval and text extraction.",
  "categories": [
    "Databases"
  ],
  "tools": [
    {
      "name": "retrieve",
      "description": "Retrieve documents from the configured pipeline.",
      "inputSchema": {
        "type": "object",
        "properties": {
          "question": {
            "type": "string",
            "description": "The term to search for."
          },
          "k": {
            "type": "number",
            "description": "The number of documents to retrieve.",
            "default": 4
          }
        },
        "required": [
          "question"
        ]
      }
    },
    {
      "name": "extract",
      "description": "Perform text extraction and chunking on a document.",
      "inputSchema": {
        "type": "object",
        "properties": {
          "base64Document": {
            "type": "string",
            "description": "Document encoded in base64."
          },
          "contentType": {
            "type": "string",
            "description": "Document content type."
          }
        },
        "required": [
          "base64Document",
          "contentType"
        ]
      }
    },
    {
      "name": "deep-research",
      "description": "Generate a deep research on the configured pipeline.",
      "inputSchema": {
        "type": "object",
        "properties": {
          "query": {
            "type": "string",
            "description": "The deep research query."
          },
          "webSearch": {
            "type": "boolean",
            "description": "Whether to perform a web search."
          }
        },
        "required": [
          "query",
          "webSearch"
        ]
      }
    }
  ],
  "prompts": [],
  "resources": [],
  "is_official": true
}