Elasticsearch Vector MCP Server for Mastra AI 6 tools — connect in under 2 minutes
Mastra AI is a TypeScript-native agent framework built for modern web stacks. Connect Elasticsearch Vector through the Vinkius and Mastra agents discover all tools automatically — type-safe, streaming-ready, and deployable anywhere Node.js runs.
ASK AI ABOUT THIS MCP SERVER
Vinkius supports streamable HTTP and SSE.
import { Agent } from "@mastra/core/agent";
import { createMCPClient } from "@mastra/mcp";
import { openai } from "@ai-sdk/openai";
async function main() {
// Your Vinkius token — get it at cloud.vinkius.com
const mcpClient = await createMCPClient({
servers: {
"elasticsearch-vector": {
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
},
});
const tools = await mcpClient.getTools();
const agent = new Agent({
name: "Elasticsearch Vector Agent",
instructions:
"You help users interact with Elasticsearch Vector " +
"using 6 tools.",
model: openai("gpt-4o"),
tools,
});
const result = await agent.generate(
"What can I do with Elasticsearch Vector?"
);
console.log(result.text);
}
main();
* Every MCP server runs on Vinkius-managed infrastructure inside AWS - a purpose-built runtime with per-request V8 isolates, Ed25519 signed audit chains, and sub-40ms cold starts optimized for native MCP execution. See our infrastructure
About Elasticsearch Vector MCP Server
Connect your Elasticsearch cluster to any AI agent and take full control of your vector search and semantic discovery workflows through natural conversation.
Mastra's agent abstraction provides a clean separation between LLM logic and Elasticsearch Vector tool infrastructure. Connect 6 tools through the 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.
What you can do
- AI-Powered Vector Search — Perform raw K-Nearest Neighbors (kNN) computations mapping absolute semantic similarity across multi-dimensional embedding arrays
- Index Orchestration — Enumerate active storage namespaces and validate physical Elasticsearch clusters tracking explicit dimensional shards securely
- Schema Management — Analyze specific index mapping rules and provision strictly typed data structures enforcing numeric dimensions for cluster readiness
- Document Indexing — Command synchronous bulk insertions attaching exact
dense_vectorembedding payloads to persist data into raw Lucene partitions - Data Invalidation — Enforce immediate hard document vaporization finding specific exact UUIDs stripping records from physical indices seamlessly
- Metadata Auditing — Analyze dimensional constraints and matching similarity thresholds perfectly to verify your vector search configurations
The Elasticsearch Vector MCP Server exposes 6 tools through the Vinkius. Connect it to Mastra AI 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 Elasticsearch Vector to Mastra AI via MCP
Follow these steps to integrate the Elasticsearch Vector MCP Server with Mastra AI.
Install dependencies
Run npm install @mastra/core @mastra/mcp @ai-sdk/openai
Replace the token
Replace [YOUR_TOKEN_HERE] with your Vinkius token
Run the agent
Save to agent.ts and run with npx tsx agent.ts
Explore tools
Mastra discovers 6 tools from Elasticsearch Vector via MCP
Why Use Mastra AI with the Elasticsearch Vector MCP Server
Mastra AI provides unique advantages when paired with Elasticsearch Vector through the Model Context Protocol.
Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure — add Elasticsearch Vector without touching business code
Built-in workflow engine chains MCP tool calls with conditional logic, retries, and parallel execution for complex automation
TypeScript-native: full type inference for every Elasticsearch Vector tool response with IDE autocomplete and compile-time checks
One-command deployment to any Node.js host — Vercel, Railway, Fly.io, or your own infrastructure
Elasticsearch Vector + Mastra AI Use Cases
Practical scenarios where Mastra AI combined with the Elasticsearch Vector MCP Server delivers measurable value.
Automated workflows: build multi-step agents that query Elasticsearch Vector, process results, and trigger downstream actions in a typed pipeline
SaaS integrations: embed Elasticsearch Vector as a first-class tool in your product's AI features with Mastra's clean agent API
Background jobs: schedule Mastra agents to query Elasticsearch Vector on a cron and store results in your database automatically
Multi-agent systems: create specialist agents that collaborate using Elasticsearch Vector tools alongside other MCP servers
Elasticsearch Vector MCP Tools for Mastra AI (6)
These 6 tools become available when you connect Elasticsearch Vector to Mastra AI via MCP:
create_index
Create dense_vector index
delete_document
Delete a document
get_index
Get index info
index_document
Index a document
list_indexes
List all indexes
search
Dense vector knn search
Example Prompts for Elasticsearch Vector in Mastra AI
Ready-to-use prompts you can give your Mastra AI agent to start working with Elasticsearch Vector immediately.
"Perform a kNN search in index 'product-embeddings' with vector [0.1, 0.2, ...]"
"Create a new vector index 'image-features' with 512 dimensions"
"List all vector indexes in my cluster"
Troubleshooting Elasticsearch Vector MCP Server with Mastra AI
Common issues when connecting Elasticsearch Vector to Mastra AI through the Vinkius, and how to resolve them.
createMCPClient not exported
npm install @mastra/mcpElasticsearch Vector + Mastra AI FAQ
Common questions about integrating Elasticsearch Vector MCP Server with Mastra AI.
How does Mastra AI connect to MCP servers?
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?
Does Mastra support workflow orchestration?
Connect Elasticsearch Vector 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 Elasticsearch Vector to Mastra AI
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.