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Vald MCP Server

Name: Vald
Availability: InStock
Author: Vinkius

vald.vdaas.org

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Power your agent with Vald — query, insert, and manage dense vectors on a highly scalable, distributed nearest-neighbor engine.

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What is the Vald MCP Server?

The Vald MCP Server gives AI agents like Claude, ChatGPT, and Cursor direct access to Vald via 6 tools. Power your agent with Vald — query, insert, and manage dense vectors on a highly scalable, distributed nearest-neighbor engine. Powered by the Vinkius - no API keys, no infrastructure, connect in under 2 minutes.

Built-in capabilities (6)

delete_vectorget_engine_infoget_vector_detailsinsert_vectorsearch_vectorsupdate_vector

Tools for your AI Agents to operate Vald

Ask your AI agent "Is the Vald cluster operational right now?" and get the answer without opening a single dashboard. With 6 tools connected to real Vald data, your agents reason over live information, cross-reference it with other MCP servers, and deliver insights you would spend hours assembling manually.

Works with Claude, ChatGPT, Cursor, and any MCP-compatible client. Powered by the Vinkius - your credentials never touch the AI model, every request is auditable. Connect in under two minutes.

Why teams choose Vinkius

One subscription gives you access to thousands of MCP servers - and you can deploy your own to the Vinkius Edge. Your AI agents only access the data you authorize, with DLP that blocks sensitive information from ever reaching the model, kill switch for instant shutdown, and up to 60% token savings. Enterprise-grade infrastructure and security, zero maintenance.

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Vald MCP Server capabilities

6 tools

delete_vector

This action is irreversible. Permanently removes a vector from the Vald index

get_engine_info

Retrieves operational information and health of the Vald engine

get_vector_details

Retrieves the raw vector data for a specific ID

insert_vector

Provide a unique ID and the vector as a JSON array. Inserts a new vector into the Vald index

search_vectors

Provide a query vector as a JSON array of floats. Performs a nearest neighbor vector similarity search

update_vector

Provide the existing ID and new vector array. Updates an existing vector in the Vald index

What the Vald MCP Server unlocks

Connect your Vald cluster to any AI agent and bring distributed, high-speed approximate nearest neighbor (ANN) vector search directly to your conversational workflow.

What you can do

Vector Search — Perform rapid semantic searches across millions of embedded data points just by querying the agent.
Data Ingestion — Insert new high-dimensional vectors directly into the Vald index for instant future retrievability in your RAG pipelines.
Index Management — Update the vector representations of existing records or permanently remove specific items from the engine cluster.
Cluster Health — Automatically retrieve operational system information, agent health statuses, and node details regarding your active Vald deployment.

How it works

1. Subscribe to this server
2. Enter your Vald Gateway Host address
3. Start performing semantic queries and updates from Claude, Cursor, or any MCP-compatible client

Your AI agent becomes the direct line to your massive vector knowledge base.

Who is this for?

Machine Learning Engineers — rapidly test and visualize embedding changes against a live Vald instance without scripting.
Data Scientists — execute on-the-fly 'top-k' semantic queries directly from an IDE to validate search recall results.
DevOps Engineers — check the active engine health status and cluster info via natural language whenever anomalies happen.
Backend Developers — quickly purge corrupted vectors or update legacy records bypassing native database terminals.

Frequently asked questions about the Vald MCP Server

Can my AI agent do a semantic search across my vector database?

Yes! Provided you supply the embedded query vector, your agent can issue a vector search command to the Vald Engine. It will rapidly scan millions of indexes natively using its ANN algorithms and return the top-K closest neighbors associated with your data.

How do I ensure my Vald cluster is healthy right from my CLI?

Skip complex diagnostics loops. Instruct your agent to get Vald internal engine info. It will interface directly via gRPC/REST and pull down cluster metrics including operational status, agent versions, and basic diagnostic health. This is vital for MLOps managing production RAG pipelines needing constant reassurance.

Can I permanently purge a corrupted vector embedding?

When a document becomes stale in your knowledge base, you must remove its embedding. Ask the AI agent: permanently delete vector ID 'doc-xyz'. Using the removeVector capability, it targets your cluster and ensures the outdated semantic representation is fully expunged without risking other node data.