"Understanding the term 'flux' or its various applications" matching MCP servers:

Enables AI agents to maintain persistent, inspectable understanding through typed, revisable updates, and to coordinate multi-agent work via shared graph-based stigmergy.

Enables high-quality image generation using FLUX.1-dev through Claude Desktop or CLI, with automatic model unloading to save VRAM and memory-efficient bfloat16 processing.

Enables structured learning with a verified loop: define goals as observable claims, learn through teach-lab-test-gate per claim, and get independently graded by an adversarial examiner to ensure genuine progress.

Implements a Model Context Protocol (MCP) server powered by Flux API from Cephalon Cloud, enabling users to utilize advanced AI capabilities through standardized communication.

A server that enables generating images through the Replicate API by calling the Flux Schnell model via the Model Context Protocol (MCP).

MCP server for The Commons (jointhecommons.space), a persistent, noncommercial space where AI voices from different models post and reply to each other with persistent identities. 48 tools; reading needs no token, writing uses a facilitator-issued token.

An MCP server that generates images based on text prompts using Black Forest Lab's FLUX model, allowing for customized image dimensions, prompt upsampling, safety settings, and batch generation.

Enables an agent to run a single planning request past seats drawn from multiple AI labs, which ask clarifying questions, propose independently, debate each other's anonymised proposals, and panel-review a draft against yes/no acceptance criteria until it passes or hits the round cap. Each run writes a local folder with the deliverable, the full debate board, a handoff document, per-lab scores, and real token/cost accounting, all driven with your own API keys.

Give any LLM agent a real Android or iPhone. 62 MCP tools: tap, swipe, type, screenshot, screen-tree reading, app launch, camera, TTS, crash reports, batched execution. Android via ADB, iPhone via WebDriverAgent, on-device inference, Docker+KVM emulators. Works with Claude Code, Cursor, LangChain, LlamaIndex, and any MCP client. MIT.

Connects AI agents to The Agents Hub, visualizing them as pixel characters on a tile-based property with tools for state, assets, inboxes, and multi-agent orchestration.

Enables AI-assisted gameplay for Slay the Spire by reading game state and providing strategy advice or automated actions via Claude Code.

Enables AI assistants like Claude to interact with humans through intuitive GUI dialogs, supporting text input, choices, confirmations, and information displays.

Provides persistent long-term memory for AI agents with semantic search and activation-based decay. Enables AI systems to remember across sessions through layered memory architecture and automatic context-aware retrieval.

Your coding agent remembers how it solved past tasks and reuses it next time: trigger, steps, outcome, lessons. Hooks recall the right skill before a task; skills strengthen with confirmed use and unused ones decay. Local SQLite, no API key, nothing leaves your machine. 9 MCP tools, works with Claude Code, Codex and Cursor. Agent-written memory stays untrusted until you approve it.

An oracle for machines that need to think sideways. Feed it a creative problem; it returns something you can't quite explain but can't stop using. Three free consultations.

An MCP server that lets AI agents autonomously buy physical hats using USDC on Base — no credit card, no checkout, no human required. Browse the catalog, get a real-time shipping quote, send crypto, and we ship the hat.

Enables AI agents to analyze videos and images using Qwen3-VL deployed on Modal, supporting hours-long videos with timestamp grounding, text extraction, video summarization, and Q\&A with 256K context window.

Enables persistent, portable memory for AI agents across sessions, devices, and providers with token-efficient 5-level lazy loading and automatic session capture.

Enables autonomous agents and MCP-compatible clients to enforce policy-approved actions using risk tiers, reversible checkpoints, and token approval bounds.

Enables autonomous agents and multi-agent frameworks to route actions through deterministic human approval gates before execution. Enforces risk tiers, reversible checkpoints, and token approval bounds so that risky or costly operations can be reviewed, bounded, and rolled back without LLM round-trips.