Typesense Vector Search 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 Typesense Vector Search through the Vinkius and Mastra agents discover all tools automatically — type-safe, streaming-ready, and deployable anywhere Node.js runs.
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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: {
"typesense-vector-search": {
url: "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp",
},
},
});
const tools = await mcpClient.getTools();
const agent = new Agent({
name: "Typesense Vector Search Agent",
instructions:
"You help users interact with Typesense Vector Search " +
"using 6 tools.",
model: openai("gpt-4o"),
tools,
});
const result = await agent.generate(
"What can I do with Typesense Vector Search?"
);
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 Typesense Vector Search MCP Server
Connect your Typesense Vector Search environment to any AI agent and take full autonomous control over vector collections, indexing processes, and semantic querying through daily conversation.
Mastra's agent abstraction provides a clean separation between LLM logic and Typesense Vector Search 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
- Vector Semantic Search — Issue combined text-filtering alongside vector similarity (
vec) queries natively through chat - Collection Provisioning — Instantly create new semantic schema datasets holding complex vector embedding structures organically
- Document Indexing — Let your AI insert or update JSON payloads into your database, bypassing manual code-level REST integrations
- Schema & Records Insights — Retrieve absolute schema geometries mapping collections to ensure developers map fields correctly
The Typesense Vector Search 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 Typesense Vector Search to Mastra AI via MCP
Follow these steps to integrate the Typesense Vector Search 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 Typesense Vector Search via MCP
Why Use Mastra AI with the Typesense Vector Search MCP Server
Mastra AI provides unique advantages when paired with Typesense Vector Search through the Model Context Protocol.
Mastra's agent abstraction provides a clean separation between LLM logic and tool infrastructure — add Typesense Vector Search 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 Typesense Vector Search 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
Typesense Vector Search + Mastra AI Use Cases
Practical scenarios where Mastra AI combined with the Typesense Vector Search MCP Server delivers measurable value.
Automated workflows: build multi-step agents that query Typesense Vector Search, process results, and trigger downstream actions in a typed pipeline
SaaS integrations: embed Typesense Vector Search as a first-class tool in your product's AI features with Mastra's clean agent API
Background jobs: schedule Mastra agents to query Typesense Vector Search on a cron and store results in your database automatically
Multi-agent systems: create specialist agents that collaborate using Typesense Vector Search tools alongside other MCP servers
Typesense Vector Search MCP Tools for Mastra AI (6)
These 6 tools become available when you connect Typesense Vector Search to Mastra AI via MCP:
create_collection
Provide the schema details as a JSON object. Creates a new search collection with a specific schema
delete_document
This action is irreversible. Permanently removes a document from a collection by its ID
get_collection_details
Retrieves schema and metadata for a specific collection
index_document
Provide the collection name and the document data as a JSON object. Adds or updates a document in a search collection
list_vector_collections
Lists all collections in the Typesense instance
search_vectors
Provide the collection name, a text query, and a vector_query string (e.g., "vec:(0.1, 0.2, ...)"). Performs a vector similarity search combined with optional text filtering
Example Prompts for Typesense Vector Search in Mastra AI
Ready-to-use prompts you can give your Mastra AI agent to start working with Typesense Vector Search immediately.
"List all active collections on this vector cluster. Do I have any collections initialized yet?"
"I have an embedding snippet: [0.34, 0.42, 0.99...]. Delete the document carrying ID 'test-123' and re-index it using this JSON data on collection 'faqs'."
"Explain the schema definitions used inside the 'products_inventory' collection."
Troubleshooting Typesense Vector Search MCP Server with Mastra AI
Common issues when connecting Typesense Vector Search to Mastra AI through the Vinkius, and how to resolve them.
createMCPClient not exported
npm install @mastra/mcpTypesense Vector Search + Mastra AI FAQ
Common questions about integrating Typesense Vector Search 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 Typesense Vector Search with your favorite client
Step-by-step setup guides for every MCP-compatible client and framework:
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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 Typesense Vector Search to Mastra AI
Get your token, paste the configuration, and start using 6 tools in under 2 minutes. No API key management needed.