"How to Retrieve Data from Weaviate" matching MCP servers:

The MCP Server for Weaviate facilitates integration with Weaviate using a customizable Python-based server, enabling interaction with Weaviate databases and OpenAI APIs via configurable URL and API keys.

An MCP server for indexing and searching local text files using late-interaction retrieval (ColBERT-style MaxSim), enabling token-level relevance matching.

An MCP server and document upload API designed for RAG workflows with Weaviate vector databases. It enables users to search, retrieve, and manage documents across specialized collections like account notes, product promos, and contracts.

MCP server that renders bar, line, and pie charts from data using QuickChart, returning PNG file paths.

Enables seamless integration with Weaviate vector databases, providing tools for semantic, keyword, and hybrid search across local or cloud instances. It supports schema management, collection retrieval, and multi-tenancy configurations through the Model Context Protocol.

A minimal MCP server with get_weather and create_ticket tools, used for testing MCP servers across protocol, unit, eval, transport, and auth layers.

An AI recipe recommendation server based on the MCP protocol, providing functions such as recipe query, classification filtering, intelligent dietary planning, and daily menu recommendation.

Enables agents to discover how a website serves its data, verify sources with evidence, export OpenAPI 3.1, and generate tested TypeScript or Python clients.

A server that enables Claude AI to interact with Weaviate vector databases, supporting both search and storage operations through Anthropic's MCP protocol.

Enables semantic search of Weaviate documentation using vector search, providing relevant documents and code snippets.

An MCP server that exposes any REST API to LLMs through runtime discovery, providing tools to browse endpoints, fetch schemas, and apply business rules without hardcoding or schema duplication.

A personal MCP bridge that lets ChatGPT drive a local Codex CLI, translating instructions into Codex app-server threads and returning compact summaries of what Codex did.

Enables semantic search across multiple Qdrant vector database collections, supporting multi-query capability and providing semantically relevant document retrieval with configurable result counts.

Enables clients to interact with a bundled documentation corpus through MCP tools and resources over HTTP or stdio, and provides a trajectory evaluation harness for grading agent performance.

A fully working MCP server built from scratch in plain Node.js, implementing tools, resources, prompts, notifications, and sampling according to the MCP specification, designed to connect to Claude Desktop or any MCP client.

Enables users to expose arbitrary HTTP APIs as configurable MCP tools by defining tool specifications in a JSON configuration file.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

Enables MCP clients to turn Make blueprints and Zapier exports into n8n workflow files, with a per-step report of what converted, what to review, and what must be finished by hand. Also lists zaps, explains how individual steps are handled, checks workflow files for broken links or placeholders, and can upload the result to an n8n instance as an inactive workflow.

MCP server for AI agents to send notifications, copy to clipboard, request confirmations, and collect text input from users across their devices.

AI-powered MCP server for file renaming, organization, and PDF splitting using natural language prompts and content analysis.