Connect Elasticsearch Vector MCP for AI Agents

Q: Can my agent create new vector indexes for me?

It can provision new densevector structures with the exact dimensions you specify in plain English, saving you from manual configuration.

Q: How do I create a new vector index with specific dimensions via chat?

Use the 'createindex' tool. You can specify the index name and the number of dimensions (e.g., 1536 for OpenAI embeddings). The agent will provision the strictly typed data structure in your Elasticsearch cluster.

Manage your vector search and semantic discovery workflows with natural language commands.

We take care of the infrastructure, maintenance, security, and governance. Works with:

Claude

ChatGPT

Cursor

Gemini

Windsurf

VS Code

Vercel

See All Capabilities

No credit card required. Experience the power of this integration risk-free.

Waiting for input…

AI Agent

What AI agents can do with Elasticsearch Vector 6 Tools for Vector Search

Use these tools to search, index, and manage your Elasticsearch vector data through your AI agent.

Search

Run a dense vector kNN search to find semantically similar documents. This helps you find relevant results based on vector similarity.

List indexes

See every active index in your Elasticsearch cluster. This provides a quick overview of your current storage namespaces.

Get index

Look up the specific mapping and dimension details for a single index. Use this to verify your configuration before indexing.

Index document

Add a new document with its dense_vector embedding to your storage. This handles the insertion into your Lucene partitions.

Delete document

Remove a specific record from your physical index using its UUID. This is the fastest way to invalidate specific data.

Create index

Set up a new dense_vector index with the correct number of dimensions. This allows you to provision new search structures quickly.

Frequently Asked Questions

Can the Elasticsearch Vector MCP help me manage my embeddings? +

Yes, it lets your agent handle the indexing and searching of your dense vector data directly, making it easy to manage your embeddings without manual scripts.

How do I connect my Elasticsearch cluster to my AI agent? +

You just need your Host URL and an API Key from your Kibana security settings to link the MCP to your AI client.

Does this MCP support kNN searches? +

It specifically handles dense vector kNN computations to find the most similar items in your data based on semantic similarity.

Can I use this to delete specific records? +

You can use the delete tool to remove documents from your physical indices using their unique UUIDs, which is great for data cleanup.

Is this good for checking my index mappings? +

Yes, it allows your agent to pull and display the specific rules and dimensions for any index in your cluster to ensure your configuration is correct.

Can my agent create new vector indexes for me? +

It can provision new dense_vector structures with the exact dimensions you specify in plain English, saving you from manual configuration.

Can my agent perform kNN searches using raw vector arrays? +

Yes. Use the 'search' tool. Provide the index name and a JSON array representing your query vector. The agent will perform raw K-Nearest Neighbors computations to find the most semantically similar documents.

How do I create a new vector index with specific dimensions via chat? +

Use the 'create_index' tool. You can specify the index name and the number of dimensions (e.g., 1536 for OpenAI embeddings). The agent will provision the strictly typed data structure in your Elasticsearch cluster.

Can I delete a single document from a vector index through the agent? +

Absolutely. Use the 'delete_document' tool with the index and document ID. The agent will enforce immediate document vaporization, stripping the record from the physical Lucene partitions.

Other MCPs in this category

Browse all →

PitchBook MCP

13 tools

AI private market intelligence: research companies, deals, investors, and funds via agents.

MCP Server

Guru

12 tools

Manage enterprise knowledge cards, track collections, and search your wiki via AI agents with Guru.

OpenLaws

14 tools

Access validated legal data via OpenLaws. Search statutes, regulations, case law, validate citations, and track legislative changes directly from any AI agent.

Internet Archive

10 tools

Search 40M+ books, videos, audio, software. Access Wayback Machine and item metadata.

Related MCPs

Browse all →

Ideanote MCP Integration

10 tools

Manage ideas, missions, and innovation workspaces via Ideanote API.

Dryfta MCP Server

10 tools

Equip your AI agent to manage event attendees, track sessions, and monitor abstract submissions via the Dryfta API.

VAT Tax Validator

1 tools

The VAT Tax Validator MCP instantly verifies European and global tax IDs using strict mathematical algorithms. It guarantees B2B compliance by checking tax number formats and checksums, stopping your AI agents from generating invoices or contracts with invalid numbers.

Unleashed MCP Server

43 tools

Unleashed MCP provides your AI client direct access to core inventory, manufacturing, and sales data from Unleashed Software. Use it to query Bills of Materials (BOMs), manage product assemblies, list invoices, and handle customer accounts all through natural conversation.