Redis 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 Redis Vector through 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: {
"redis-vector": {
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
},
});
const tools = await mcpClient.getTools();
const agent = new Agent({
name: "Redis Vector Agent",
instructions:
"You help users interact with Redis Vector " +
"using 6 tools.",
model: openai("gpt-4o"),
tools,
});
const result = await agent.generate(
"What can I do with Redis 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 Redis Vector MCP Server
Connect your Redis database (equipped with the RediSearch module) to your AI agent, turning it into an advanced Vector Database administrator. Activating this integration grants your conversational interface the power to interact directly with your semantic search engine, enabling tasks like querying mathematical embeddings for similar records, configuring fresh vector indexes, and managing geometric data structures without needing dedicated external database clients.
Mastra's agent abstraction provides a clean separation between LLM logic and Redis 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.
What you can do
- Similarity Vector Search (KNN) — Let the AI perform rapid native vector comparisons (
search_vectors). Provide an embedding array via prompt or code, and retrieve the absolute nearesttop_kneighbors securely cached in your infrastructure. - Index Management — Actively discover all loaded RediSearch vector indexes, investigate their configured dimensions (
get_index_info), or command the AI to instantiate new KNN indexes (create_vector_index) tailored for fresh AI workloads. - Embedding Administration — Inject and modify geometric vector components associated with a document key (
upsert_vector), or purge legacy embeddings efficiently (delete_vector) to keep semantic records clean and operational.
The Redis 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 Redis Vector to Mastra AI via MCP
Follow these steps to integrate the Redis 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 Redis Vector via MCP
Why Use Mastra AI with the Redis Vector MCP Server
Mastra AI provides unique advantages when paired with Redis Vector through the Model Context Protocol.
Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure. add Redis 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 Redis 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
Redis Vector + Mastra AI Use Cases
Practical scenarios where Mastra AI combined with the Redis Vector MCP Server delivers measurable value.
Automated workflows: build multi-step agents that query Redis Vector, process results, and trigger downstream actions in a typed pipeline
SaaS integrations: embed Redis 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 Redis Vector on a cron and store results in your database automatically
Multi-agent systems: create specialist agents that collaborate using Redis Vector tools alongside other MCP servers
Redis Vector MCP Tools for Mastra AI (6)
These 6 tools become available when you connect Redis Vector to Mastra AI via MCP:
create_vector_index
Specify the name and vector dimensions. Creates a new RediSearch vector index
delete_vector
Deletes a vector document from Redis
get_index_info
Retrieves details for a specific vector index
list_indexes
Lists all RediSearch vector indexes
search_vectors
Provide the query vector as a JSON array of floats. Performs a KNN similarity search in a vector index
upsert_vector
Specify the document key and the vector as a JSON array. Inserts or updates a vector in a Redis hash
Example Prompts for Redis Vector in Mastra AI
Ready-to-use prompts you can give your Mastra AI agent to start working with Redis Vector immediately.
"Search the index 'customer-support-vector' for the top 3 similar records to this embedding vector: [0.12, -0.45, 0.08, 0.99...]"
"Insert a new embedding into the database with the key 'user:439:preference' containing the vector `[0.2, -0.1...]`."
"Retrieve the index information logic and schema mapping for 'docs-semantic-index'."
Troubleshooting Redis Vector MCP Server with Mastra AI
Common issues when connecting Redis Vector to Mastra AI through the Vinkius, and how to resolve them.
createMCPClient not exported
npm install @mastra/mcpRedis Vector + Mastra AI FAQ
Common questions about integrating Redis 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 Redis 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 Redis Vector to Mastra AI
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.