Vinkius

DataStax Astra DB Vector MCP for AI Agents. Run semantic searches and manage unstructured data collections.

DataStax Astra DB Vector gives your AI client direct conversational access to complex NoSQL databases and vector embeddings. It lets you perform everything from counting records to running semantic searches on unstructured data, all without writing code.

DataStax Astra DB Vector MCP for AI Agents MCP is compatible with Claude Claude
DataStax Astra DB Vector MCP for AI Agents MCP is compatible with ChatGPT ChatGPT
DataStax Astra DB Vector MCP for AI Agents MCP is compatible with Cursor Cursor
DataStax Astra DB Vector MCP for AI Agents MCP is compatible with Gemini Gemini
DataStax Astra DB Vector MCP for AI Agents MCP is compatible with Windsurf Windsurf
DataStax Astra DB Vector MCP for AI Agents MCP is compatible with VS Code VS Code
DataStax Astra DB Vector MCP for AI Agents MCP is compatible with JetBrains JetBrains
DataStax Astra DB Vector MCP for AI Agents MCP is compatible with Vercel Vercel
See Vinkius in Action

Give Claude and any AI agent real-world access

List available collections

You can ask the MCP to list every collection currently active in your configured database namespace.

Perform vector similarity searches

The agent runs Approximate Nearest Neighbor (ANN) searches, letting you find documents based on meaning rather than just matching keywords.

Retrieve specific JSON records

You can ask the MCP to pull back one or multiple standard NoSQL JSON documents from any active collection.

Insert new structured data

The agent creates and inserts a brand-new document, including pre-generated vector keys for embedding searches.

Delete existing records

You can instruct the MCP to safely remove specific documents from a collection when they are no longer needed.

Count total documents

The agent provides an accurate count of all active JSON documents across a specified Astra DB collection.

Waiting for input…

AI Agent
DataStax Astra DB Vector MCP for AI Agents

What AI agents can do with 7 Tools for DataStax Astra DB Vector: Document Operations & Embeddings

These tools let your AI client list collections, count records, perform semantic vector searches, or insert and delete specific documents in a NoSQL environment.

Make your AI actually useful.

Add this MCP to Claude, Cursor, or Windsurf and your AI stops guessing. It gets real tools to look things up, take action, and handle the stuff you keep doing by hand.

Start using DataStax Astra DB Vector MCP

List Collections

Lists all available data containers (collections) within the connected Astra DB namespace.

Find Documents

Retrieves multiple standard NoSQL JSON documents from a specified collection using...

Find One Document

Finds and returns a single, specific document within an Astra DB collection.

Vector Search

Performs an Approximate Nearest Neighbor (ANN) search to find semantically related...

Insert Document

Creates and adds a new document into a collection, optionally including...

Delete Document

Removes targeted documents from an Astra DB collection after confirmation.

Count Documents

Counts the total number of active JSON records present in a given collection.

Security and governance baked right in.

Pick your AI client below to get set up. Just create a Vinkius account, subscribe, and you're instantly up and running. We handle the entire backend infrastructure, delivering out-of-the-box support for HTTPS Streamable, SSE, and OAuth2—zero messy routing required.

DataStax Astra DB Vector MCP for AI Agents MCP is compatible with Claude

Claude AI

1

Open Claude Settings

Go to claude.ai, click your profile icon, then navigate to Customize → Connectors.

2

Add Custom Connector

Click the "+" button and select Add custom connector. Paste your Vinkius endpoint URL:

https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp

Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. For OAuth-protected servers, expand Advanced settings to add credentials.

3

Start a conversation

Open a new chat. The DataStax Astra DB Vector MCP for AI Agents integration is available immediately — no restart needed.

Choose How to Get Started

Build a custom MCP for your own tools, or connect a ready-made integration from our catalog.

Build Your Own

Turn any API into an MCP. Import a spec, define Agent Skills, or deploy with MCPFusion.

  • Import from OpenAPI, Swagger, or YAML specs
  • Create Agent Skills with progressive disclosure
  • Deploy to edge with MCPFusion framework
  • Built in DLP, auth, and compliance on each call
  • Real time usage dashboard and cost metering
  • Publish to catalog or keep private
Start building

Make Your AI Do More

Start with DataStax Astra DB Vector, then connect any of our 5,200+ other servers whenever your AI needs more. One click, no limits.

  • Use this MCP plus 5,200+ others, all in one place
  • Add new capabilities to your AI anytime you want
  • Connections are secured and governed automatically
  • Track usage and costs across all your servers
  • Works with Claude, ChatGPT, Cursor, and more
  • New servers added to the catalog weekly
DataStax Astra DB Vector MCP for AI Agents MCP server cover

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by DataStax Astra DB. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Policy on each call

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DataStax Astra DB Vector MCP: Semantic Search for Unstructured Data

Currently, running deep analysis on a database means jumping between multiple systems. You run a count query in one place, use a keyword filter in another, and then manually export data to a third tool just to perform vector lookups. It's slow, it involves tons of copy-pasting, and you always risk missing crucial context.

With this MCP, the whole process happens conversationally. You ask your agent to find documents related to 'customer retention strategies.' The system executes a `vector_search`, giving you immediate, semantically accurate results right in your chat. It’s pure, conversational insight.

DataStax Astra DB Vector MCP: Managing NoSQL Document Collections

If your data is decentralized—meaning you have records spread across dozens of different collections—you spend time just mapping the schema. You're always running `list_collections` to remember where that specific type of document lives, or trying to figure out if a record was created correctly using `insert_document`.

Now, your agent handles the overhead. It knows what collections are available and can help you manage them. Need to audit data? You tell it to count documents; need to test new inputs? Use the MCP to insert them for review. Everything is centralized.

What DataStax Astra DB Vector MCP for AI Agents MCP does for your AI

Think of this MCP as a direct line into your database's guts. Instead of pulling up a console or writing multi-line queries, your AI agent talks to Astra DB naturally. You can ask it to count documents in an entire collection or find specific records using simple language.

Need to understand what’s lurking in your unstructured data? Your agent runs vector similarity searches, finding documents that mean the same thing as a prompt, even if they don't share keywords. It also lets you manage the structure itself—you can list available collections and insert brand new JSON records with pre-generated embeddings.

This kind of deep, contextual access is huge for developers and data teams alike. When you connect this to Vinkius, your AI client gets a single point of entry to power all those complex operations. You're not just querying; you’re managing the entire data lifecycle right from your chat window.

Built · Hosted · Managed by Vinkius DataStax Astra DB Vector MCP for AI Agents — Unstructured Data Search
Server ID 019d7553-eb3a-736b-9627-acf7d69ef862
Vinkius Inspector
Compliance Grade A+
Score 100/100
Vinkius Inspector Badge — Score 100/100

Frequently asked questions about DataStax Astra DB Vector MCP for AI Agents MCP

How can I use DataStax Astra DB Vector MCP to search documents by meaning, not just keywords? +

You simply ask your agent to run a vector similarity search. Instead of matching 'car,' it finds documents related to 'automobiles' or 'vehicle.' This gives you much deeper, contextual results from your unstructured data.

Is DataStax Astra DB Vector MCP good for managing my database structure? +

Yes. You can use the agent to list all existing collections and count records across them. It lets you manage the overall shape of your NoSQL data without needing manual console access.

Do I need a developer background to use DataStax Astra DB Vector MCP? +

No. You don't write code. You just talk to the agent using natural language, telling it what records you want to find or what data you want to add.

Can I test new documents in DataStax Astra DB Vector MCP before going live? +

Absolutely. The agent allows you to insert and manage mock documents using the insert_document tool, letting you validate your data pipelines without touching production records.

What if I want to find a single, very specific record? +

You can ask the agent to run a precise retrieval command (find_one_document). This is faster and more directed than searching through an entire collection of documents.