Marqo AI (Vector Search & Embeddings) MCP Server for Cursor 6 tools — connect in under 2 minutes
Cursor is an AI-first code editor built on VS Code that integrates LLM-powered coding assistance directly into the development workflow. Its Agent mode enables autonomous multi-step coding tasks, and MCP support lets agents access external data sources and APIs during code generation.
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{
"mcpServers": {
"marqo-ai-vector-search-embeddings": {
"url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
}
}
}
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About Marqo AI (Vector Search & Embeddings) MCP Server
Connect your Marqo instance to any AI agent and take full control of your semantic search infrastructure, vector embeddings, and real-time document indexing through natural conversation.
Cursor's Agent mode turns Marqo AI (Vector Search & Embeddings) into an in-editor superpower. Ask Cursor to generate code using live data from Marqo AI (Vector Search & Embeddings) and it fetches, processes, and writes — all in a single agentic loop. 6 tools appear alongside file editing and terminal access, creating a unified development environment grounded in real-time information.
What you can do
- Tensor Search Orchestration — Execute dense semantic similarity searches against your indices using natural language queries, with Marqo handling embedding extraction automatically
- Dynamic Document Ingestion — Write new JSON records into your vector indices directly from your agent, allowing for instant searchability of fresh data mappings
- Index Lifecycle Management — Create explicitly bounded new vector indices with custom model settings and dimension constraints to optimize your search architecture
- Vector Audit & Stats — Retrieve detailed configuration metrics for your indices, including document counts, embedding model types, and underlying schema mappings
- Precision Deletion — Physically eradicate vectorized representations by targeting specific scalar identifiers to maintain a clean and relevant search index
- Resource Inventory — List all available vector indices on your Marqo instance to identify collection boundaries before executing search queries
The Marqo AI (Vector Search & Embeddings) MCP Server exposes 6 tools through the Vinkius. Connect it to Cursor in under two minutes — no API keys to rotate, no infrastructure to provision, no vendor lock-in. Your configuration, your data, your control.
How to Connect Marqo AI (Vector Search & Embeddings) to Cursor via MCP
Follow these steps to integrate the Marqo AI (Vector Search & Embeddings) MCP Server with Cursor.
Open MCP Settings
Press Cmd+Shift+P (macOS) or Ctrl+Shift+P (Windows/Linux) → search "MCP Settings"
Add the server config
Paste the JSON configuration above into the mcp.json file that opens
Save the file
Cursor will automatically detect the new MCP server
Start using Marqo AI (Vector Search & Embeddings)
Open Agent mode in chat and ask: "Using Marqo AI (Vector Search & Embeddings), help me..." — 6 tools available
Why Use Cursor with the Marqo AI (Vector Search & Embeddings) MCP Server
Cursor AI Code Editor provides unique advantages when paired with Marqo AI (Vector Search & Embeddings) through the Model Context Protocol.
Agent mode turns Cursor into an autonomous coding assistant that can read files, run commands, and call MCP tools without switching context
Cursor's Composer feature can generate entire files using real-time data fetched through MCP — no copy-pasting from external dashboards
MCP tools appear alongside built-in tools like file reading and terminal access, creating a unified agentic environment
VS Code extension compatibility means your existing workflow, keybindings, and extensions all work alongside MCP tools
Marqo AI (Vector Search & Embeddings) + Cursor Use Cases
Practical scenarios where Cursor combined with the Marqo AI (Vector Search & Embeddings) MCP Server delivers measurable value.
Code generation with live data: ask Cursor to generate a security report module using live DNS and subdomain data fetched through MCP
Automated documentation: have Cursor query your API's tool schemas and generate TypeScript interfaces or OpenAPI specs automatically
Infrastructure-as-code: Cursor can fetch domain configurations and generate corresponding Terraform or CloudFormation templates
Test scaffolding: ask Cursor to pull real API responses via MCP and generate unit test fixtures from actual data
Marqo AI (Vector Search & Embeddings) MCP Tools for Cursor (6)
These 6 tools become available when you connect Marqo AI (Vector Search & Embeddings) to Cursor via MCP:
add_documents
Write new documents into Marqo
create_index
Create an explicitly bounded new vector index
delete_documents
Delete specific documents from Marqo by targeting their IDs
get_index_stats
Get configuration and stats for an index
list_indexes
Crucial before writing queries hitting arbitrary collections. List all Marqo vector indexes
tensor_search
Perform natural language tensor search on Marqo
Example Prompts for Marqo AI (Vector Search & Embeddings) in Cursor
Ready-to-use prompts you can give your Cursor agent to start working with Marqo AI (Vector Search & Embeddings) immediately.
"Semantic search in index 'products' for 'lightweight running shoes for trails'"
"List all vector indexes in my Marqo instance"
"Add this document to the 'support-docs' index: {"title": "API Auth", "content": "Use Marqo-API-Key header"}"
Troubleshooting Marqo AI (Vector Search & Embeddings) MCP Server with Cursor
Common issues when connecting Marqo AI (Vector Search & Embeddings) to Cursor through the Vinkius, and how to resolve them.
Tools not appearing in Cursor
Server shows as disconnected
Marqo AI (Vector Search & Embeddings) + Cursor FAQ
Common questions about integrating Marqo AI (Vector Search & Embeddings) MCP Server with Cursor.
What is Agent mode and why does it matter for MCP?
Where does Cursor store MCP configuration?
mcp.json file. You can configure servers at the project level (.cursor/mcp.json in your project root) or globally (~/.cursor/mcp.json). Project-level configs take precedence.Can Cursor use MCP tools in inline edits?
How do I verify MCP tools are loaded?
Connect Marqo AI (Vector Search & Embeddings) with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
Anthropic's native desktop app for Claude with built-in MCP support.
AI-first code editor with integrated LLM-powered coding assistance.
GitHub Copilot in VS Code with Agent mode and MCP support.
Purpose-built IDE for agentic AI coding workflows.
Autonomous AI coding agent that runs inside VS Code.
Anthropic's agentic CLI for terminal-first development.
Python SDK for building production-grade OpenAI agent workflows.
Google's framework for building production AI agents.
Type-safe agent development for Python with first-class MCP support.
TypeScript toolkit for building AI-powered web applications.
TypeScript-native agent framework for modern web stacks.
Python framework for orchestrating collaborative AI agent crews.
Leading Python framework for composable LLM applications.
Data-aware AI agent framework for structured and unstructured sources.
Microsoft's framework for multi-agent collaborative conversations.
Connect Marqo AI (Vector Search & Embeddings) to Cursor
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.