Bring Vector Database
to Mastra AI
Create your Vinkius account to connect OpenSearch Vector to Mastra AI and start using all 6 AI tools in minutes. Fully managed, enterprise secure, and ready to use without writing a single line of code. No hosting, no server setup — just connect and start using.
GDPR Free for SubscribersCompatible with every major AI agent and IDE
Gemini
What is the OpenSearch Vector MCP Server?
Turn your OpenSearch cluster into an AI-native vector database. Create k-NN indexes, upsert embeddings, run similarity searches, and inspect index configurations — all through natural conversation with your AI agent.
What you can do
- Vector Search — Execute k-Nearest Neighbors queries against any k-NN index with custom top-K limits and dense float vectors
- Index Management — List all cluster indexes with health status and document counts, or inspect a specific index's vector dimension, engine config, and distance metric
- Create Index — Provision new k-NN indexes optimized for cosine similarity with configurable vector dimensions (384, 768, 1536, etc.)
- Document Operations — Upsert vector documents with metadata, or delete documents from the embedding space by ID
How it works
- Subscribe to this server
- Enter your OpenSearch Host, Username, and Password
- Start managing your vector store from Claude, Cursor, or any MCP-compatible client
Who is this for?
- ML engineers — test similarity queries against production embeddings without writing curl commands
- RAG developers — index and retrieve context documents for retrieval-augmented generation pipelines
- Data teams — inspect index health, document counts, and vector configurations through conversation instead of Kibana dashboards
Built-in capabilities (6)
knn: true` and mapping a rigid dynamic dense vector field optimized for cosine similarity. Create a new native OpenSearch KNN index ready for vector embeddings
Delete an explicit vector document bounding from OpenSearch
Retrieve explicit OpenSearch index mapping and settings
This executes a fast transactional atomic insertion into the embedding space. Upsert a singular vector document directly into an OpenSearch KNN index
List all explicit indexes residing on the OpenSearch cluster
Provide the exact index name and a JSON-stringified dense float vector array to find conceptually similar embeddings natively. Execute a K-Nearest Neighbors (k-NN) vector search against OpenSearch
Why Mastra AI?
Mastra's agent abstraction provides a clean separation between LLM logic and OpenSearch Vector tool infrastructure. Connect 6 tools through Vinkius and use Mastra's built-in workflow engine to chain tool calls with conditional logic, retries, and parallel execution. deployable to any Node.js host in one command.
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Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure. add OpenSearch Vector without touching business code
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Built-in workflow engine chains MCP tool calls with conditional logic, retries, and parallel execution for complex automation
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TypeScript-native: full type inference for every OpenSearch Vector tool response with IDE autocomplete and compile-time checks
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One-command deployment to any Node.js host. Vercel, Railway, Fly.io, or your own infrastructure
OpenSearch Vector in Mastra AI
Why run OpenSearch Vector with Vinkius?
The OpenSearch Vector connection runs on our fully managed, secure cloud infrastructure. We handle the hosting, maintenance, and security so you don't have to deal with servers or code. All 6 tools are ready to work instantly without any complex setup.
You stay in complete control of your data. Your AI only accesses the information you approve, keeping your sensitive passwords and private details completely safe. Plus, with automatic optimizations, your AI works faster and more efficiently.
* Every connection is hosted and maintained by Vinkius. We handle the security, updates, and infrastructure so you don't have to write code or manage servers. See our infrastructure
Over 4,000 integrations ready for AI agents
Explore a vast library of pre-built integrations, optimized and ready to deploy.
Connect securely in under 30 seconds
Generate tokens to authenticate and link external services in a single step.
Complete visibility into every agent action
Audit live requests, latency, success rates, and active security compliance policies.
Optimize spending and track token ROI
Analyze real-time token consumption and cost metrics detailed by connection.
Explore our live AI Agents Analytics dashboard to see it all working
This dashboard is included when you connect OpenSearch Vector using Vinkius. You will never be left in the dark about what your AI agents are doing with your tools.
OpenSearch Vector and 4,000+ other AI tools. No hosting, no code, ready to use.
Professionals who connect OpenSearch Vector to Mastra AI through Vinkius don't need to write code, manage servers, or worry about security. Everything is pre-configured, secure, and runs automatically in the background.
Raw MCP | Vinkius | |
|---|---|---|
| Ready-to-use MCPs | Find and configure each manually | 4,000+ MCPs ready to use |
| Connection Setup | Manual coding & server setup | 1-click instant connection |
| Server Hosting | You host it yourself (needs 24/7 uptime) | 100% hosted & managed by Vinkius |
| Security & Privacy | Stored in plaintext config files | Bank-grade encrypted vault |
| Activity Visibility | Blind execution (no logs or tracking) | Live dashboard with real-time logs |
| Cost Control | Runaway AI token spend risk | Automatic budget limits |
| Revoking Access | Must delete files or code to stop | 1-click disconnect button |
How Vinkius secures
OpenSearch Vector for Mastra AI
Every request between Mastra AI and OpenSearch Vector is protected by our secure gateway. We automatically keep your sensitive data private, prevent unauthorized access, and let you disconnect instantly at any time.
Frequently asked questions
What vector dimensions does it support?
Any dimension supported by OpenSearch k-NN. Common values: 384 (MiniLM), 768 (BERT/all-mpnet), 1536 (OpenAI text-embedding-ada-002), 3072 (text-embedding-3-large). When creating an index, specify the exact dimension and the agent provisions the mapping automatically.
Can I delete an entire index or just individual documents?
Currently, the agent supports deleting individual documents by ID from an index. Full index deletion is not exposed through this integration to prevent accidental data loss. If you need to drop an index, use the OpenSearch Dashboards or direct API calls.
Does this work with Amazon OpenSearch Service (managed)?
Yes. Provide the Amazon OpenSearch Service endpoint as the host (e.g., https://search-xxx.us-east-1.es.amazonaws.com) along with the master username and password. The integration uses standard REST APIs that work identically on managed and self-hosted clusters.
How does Mastra AI connect to MCP servers?
Create an MCPClient with the server URL and pass it to your agent. Mastra discovers all tools and makes them available with full TypeScript types.
Can Mastra agents use tools from multiple servers?
Yes. Pass multiple MCP clients to the agent constructor. Mastra merges all tool schemas and the agent can call any tool from any server.
Does Mastra support workflow orchestration?
Yes. Mastra has a built-in workflow engine that lets you chain MCP tool calls with branching logic, error handling, and parallel execution.
createMCPClient not exported
Install: npm install @mastra/mcp
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