mcpField
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Emero

Emero

Remote
emero.studioMedia & Design0Updated 2d ago

About Emero

Emero is a hosted creative MCP server for people using AI assistants to generate images, video, music and speech. It lets users select models and retains brand-specific generation lessons, settings and workflows for later use.

Key features

  1. 01Generate images, video, music and speech
  2. 02Choose from listed generation models
  3. 03Combine video clips
  4. 04Search and inspect past creations
  5. 05Save and manage brand guidance
  6. 06Check model prices and job guidance

Use cases

  1. 01Create media through an AI assistant using plain-language requests
  2. 02Combine generated clips into a continuous video
  3. 03Find and review previous generations
  4. 04Reuse brand rules and prior generation lessons

MCP support

Emero exposes generation, video-combination, search, asset viewing, settings and brand-memory tools through a hosted Streamable HTTP MCP server. MCP clients connect at `https://mcp.emero.studio/mcp` and authenticate with an Emero account using OAuth 2.1.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://mcp.emero.studio/mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

Tools

Details

From the project README

Emero MCP server

Teach your AI assistant to make pro images and video.

Emero turns your AI assistant, like Claude or ChatGPT, into a creative director. Connect it once and ask for images, video, music or speech in plain words. It runs the model you pick: Kling 4.0, Seedance 2.5, Nano Banana Pro, GPT Image 2.5 and more.

Behind it is a second brain. Every generation teaches it something: what a model is good at, which prompt fixed a problem, which look your brand keeps. Emero saves those lessons for your brand and uses them on the next prompt, so results get better the more you make.

It starts smart. Emero is built on 6,000+ tested generations and counting, and 100+ of those workflows are public with the exact prompts and real costs at emero.studio/workflows.

This repository holds the public documentation and the MCP Registry metadata for Emero's hosted MCP server. The server itself is run by Emero; its source is not published here.

Connect

Server URLhttps://mcp.emero.studio/mcp
TransportStreamable HTTP (remote)
Sign-inOAuth 2.1, with your Emero account
Registry nameio.github.EmeroAI/emero
Server card/.well-known/mcp/server-card.json

Claude: Settings → Connectors → Add custom connector, paste the server URL, then sign in.

Other MCP clients: add a remote MCP server with the URL above. The client opens Emero's sign-in page the first time it connects.

What it can do

ToolWhat it does
generateMake an image, video clip, music track, voiceover or upscale, billed at model cost
combine_videosJoin clips into one continuous video
check_generationFetch the result of a running generation
search_creationsFind past generations by description
view / inspectShow assets to you, or let the assistant look at them
ingest_url / request_uploadBring your own images and video in as references
get_settings / set_settingsRead or change model, aspect ratio, duration and other settings
get_emero_brain / save_to_emero_brain / manage_emero_brainThe brand's second brain: look, rules, subjects and decisions
get_pricelistCurrent price per model
load_skillEmero's step-by-step guidance for each kind of job

Pricing

A flat $10/month for the second brain and the prompting workflows, plus each generation at the real model cost with no markup. New accounts start with $2 of generations free. Details: emero.studio/pricing.

Links

Comments

Markdown supported

New to MCP?

From what the protocol is to installing your first server, these answers cover most first questions.

An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.