Integrate Typesense Vector Search with Claude, Cursor, Chatbots & AI Agents MCP Server

Automate vector similarity searches via Typesense — index documents, manage collections, and execute semantic queries directly from your AI agent.

GDPR Free for Subscribers

Compatible with every major AI agent and IDE

Claude

ChatGPT

Cursor

Gemini

Windsurf

VS Code

JetBrains

Vercel

+ other MCP clients

create

Create collection on Typesense Vector Search

Provide the schema details as a JSON object. Creates a new search collection with a specific schema

delete

Delete document on Typesense Vector Search

This action is irreversible. Permanently removes a document from a collection by its ID

get

Get collection details on Typesense Vector Search

Retrieves schema and metadata for a specific collection

index

Index document on Typesense Vector Search

Provide the collection name and the document data as a JSON object. Adds or updates a document in a search collection

list

List vector collections on Typesense Vector Search

Lists all collections in the Typesense instance

Search vectors on Typesense Vector Search

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

Security & Code Integrity Audit

Every tool in the Typesense Vector Search MCP Server is continuously audited by the Vinkius Security Engine. We guarantee zero-trust payload isolation, strict data boundaries, and deterministic execution for enterprise-grade AI agents.

A+Score: 100

How Vinkius protects your data

Can I audit what my AI agents are doing with this integration?

Yes, Vinkius provides an immutable, HMAC-chained audit log. Every tool execution, payload, and response is tracked in real-time on your dashboard, giving you complete visibility into your agent's actions.

How do I make the AI create a semantic collection ready for embeddings (OpenAI 1536 dims)?

Ask the agent to use 'create_collection'. Provide standard JSON declaring the name, the field structure, and explicitly define the float[] field tracking the 1536 dims length. The cluster will spin the framework up instantly.

What if the AI ends up reading customer data or confidential information?

We have a built-in digital "bodyguard" called DLP (Data Loss Prevention). If a tool fetches data and the response contains social security numbers, credit cards, or personal customer info, Vinkius magically blocks and erases that information before it is delivered to the AI. The AI works only with what is strictly necessary, and your sensitive data never leaks.

Does the AI train on my tools or API data?

No. Vinkius enforces a strict Zero-Retention policy. Your data simply passes through our secure servers to complete the requested action and is instantly forgotten. Nothing you do here is ever stored, logged, or used to train any artificial intelligence.

Triggering Typesense Vector Search via Natural Language

Use Typesense Vector Search with any AI agent framework to process, analyze, and mutate data securely via the Model Context Protocol.

Mastering vector search with Agents

The Typesense Vector Search server supports direct MCP connections for vector search. This provides Claude with the required permissions to execute loved by devs functions.

The Future of semantic search

The Typesense Vector Search toolkit provides AI native integration for semantic search. It structures data so Claude Code can accurately process loved by devs requirements.