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Shadylukin
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neumann-client

Connect Rust, Python, and TypeScript apps to Neumann via gRPC for queries and vector operations.

74|6|Updated Dec 23, 2025
Search Tags:#typescript#integration#python#sdk#grpc#vector-search#neumann
One-click install
npx skills add https://github.com/Shadylukin/Neumann --skill neumann-client
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: neumann-client
Source: https://github.com/Shadylukin/Neumann/tree/main/.claude/skills/neumann-client
Command: npx skills add https://github.com/Shadylukin/Neumann --skill neumann-client

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill provides clear, actionable guidance for connecting applications to the Neumann database so developers can reliably open connections, execute queries, manage vectors and blobs, and safely handle results across supported languages.

Core Features & Use Cases

  • Official SDK patterns for Rust, Python, and TypeScript with gRPC transport and embedded mode options where supported.
  • Query execution modes: single, batch, streaming, and paginated; plus a dedicated VectorClient for collection and point operations and a Blob API for artifact upload/download.
  • Error and retry guidance with mapped error codes, configuration presets for timeouts and retries, and examples for transaction and streaming usage.
  • Use Case: Build a Python microservice that queries user data, runs vector similarity searches, and streams large query results to a client while respecting retry and timeout policies.

Quick Start

Connect to a local Neumann instance using the Python SDK, execute a SELECT users query, and return the parsed rows as JSON.

Frequently Asked Questions about neumann-client

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I connect a Python application to a Neumann database using gRPC?▼

To connect a Python application to a Neumann database, use the Neumann client SDK to establish a remote gRPC connection on port 9200 with x-api-key authentication. You can then execute queries and manage collections directly.

Can I run vector similarity searches and manage blob storage in TypeScript?▼

Yes, you can run vector similarity searches and manage blob storage in TypeScript using the dedicated VectorClient for collection operations and the Blob API for artifact upload and download within the Neumann SDK.

What is the best way to handle large query results from a Neumann database?▼

The best way to handle large query results from a Neumann database is by using streaming or paginated query execution modes. These consumption patterns allow you to process rows incrementally rather than loading entire datasets into memory.

Does the Neumann SDK support configurable timeout and retry policies for microservices?▼

Yes, the Neumann SDK supports configurable timeout and retry policies for microservices. It provides configuration presets and mapped error codes to help safely handle transaction failures and streaming operations.

How do I parse discriminated-union results from batch Neumann queries in Rust?▼

To parse discriminated-union results from batch Neumann queries in Rust, apply the SDK's discriminated-union result handling patterns. This allows you to safely map and extract typed rows returned from single or batch query executions.

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