"Information about PG Vector" matching MCP servers:

Enables controlling a Dirtywave M8 over USB by reading its screen as text, pressing buttons, playing notes, and retrieving system information through MCP tools.

Enables AI agents to design hardware by writing C-like HDL and compiling it to Verilog, with real toolchain verification including synthesis checks.

MCP server for managing large fleets of BLE devices with connection pooling, scheduling, retries, and partial-failure handling. Enables AI agents to run fleet-level reads/writes without worrying about radio connection limits.

Enables agents to discover and manage Raspberry Pis and other SSH devices on a LAN, including authentication, command execution, file and directory operations, reboots, and ctrlPi API installation.

MCP server for managing Raspberry Pi K3s clusters via AI assistants like Claude Code.

Talk to your Flipper Zero from Claude Code — or any MCP client. Storage, app deployment, screen capture, button automation, JavaScript execution on the device, and honest answers about what is nearby.

An MCP server that exposes WLAN Pi capabilities like device info, Wi-Fi scanning, service management, and VLANs to AI assistants via the wlanpi-core REST API.

MCP server for inspecting PX4 ULog flight logs, enabling AI assistants to understand, debug, and reason about drone systems.

Gives AI assistants a fully offline toolchain for FlyThings OS human-machine interface development: converting HTML prototypes into JSON/FTU layouts, packaging and deploying firmware to devices, capturing real-device screenshots for pixel-diff acceptance, and generating i18n, tests, and bug reports. It also bundles a local vector-plus-BM25 knowledge base covering hardware models, UI control semantics, dependency manifests, and reusable components.

Enables AI agents to query a verified, sourced knowledge base about NVIDIA Jetson devices via the Model Context Protocol, with every claim cited and knowledge gaps explicitly stated.

A Model Context Protocol (MCP) based server that efficiently manages PDF files, allowing AI coding tools like Cursor to read, summarize, and extract information from PDF datasheets to assist embedded development work.

Connects AI assistants to physical devices via MCP, enabling LLMs to reason about sensor data, perform cross-device correlation, and interpret anomalies.

Wraps Vector DaVinci Configurator 6/5 and DaVinci Developer Classic command-line tools into MCP tools so AI agents can validate, update, generate, compare, and inspect AUTOSAR projects with structured operations, background jobs, Groovy automation, ECUC analysis, version detection, and generated-file reporting.

Linkr KVM MCP Server exposes Radxa Linkr KVM controls through the Model Context Protocol (MCP). It lets an MCP client capture screenshots, crop screen areas, send keyboard and mouse events, type text, wait for on-screen text, and ask vision/OCR models about the current screen.

MCP server that enables AI agents to interact with Vector CANoe for automotive bus testing and diagnostics using natural language commands.