Image, video and audio · MCP server
Runapi ai MCP: MCP server, setup and security
Runapi ai MCP is an open-source MCP server published on GitHub that lets an AI agent browse AI models and create multimedia tasks or call LLMs. Its repository has 56 stars and its last commit is from October 23, 2026 and it is licensed under Apache-2.0.
What Runapi ai MCP does
According to its repository: “Unified API for AI models across providers: browse models and prices, create image, video, music and audio tasks, poll results and call LLM endpoints.”
The Model Context Protocol (MCP) is a standard plug between an AI agent and an outside service: once the server is connected, its tools show up in the agent, which decides when to call them. Runapi ai MCP is listed under Image, video and audio, a category of 67 servers in the directory, where it ranks #37 by stars.
Topics declared by the repository: claude-code, cursor, image-generation, music-generation, runapi, video-generation.
Installing and connecting Runapi ai MCP
Distribution modes declared in the official MCP registry:
- npm package (Node.js, usually started with
npx) - remote server (streamable-http): you connect to it by URL, with nothing to install locally
It works with any MCP-compatible client (Claude Desktop, Claude Code, Cursor, VS Code, Codex and most recent agents). You add one entry to the client's MCP configuration: server name, start command or URL, environment variables. Project language: TypeScript.
The registry lists one secret variable to provide (API key, access token). Keep them in the client's environment variables, never in a shared file or a repository.
Security: what to check
Connecting an MCP server means installing software that talks straight to your agent: it runs with your rights and the model trusts its tool descriptions. The risk therefore depends on what it can touch and how far its code can be trusted.
Points found for Runapi ai MCP:
- Secrets: the server acts with your credentials. Create a dedicated key with minimum rights and an expiry date.
Good practice: grant only the rights needed (least privilege), require human approval for irreversible actions, and run the AI agent security check.
Project activity and maintenance
Created on June 3, 2026, the runapi-ai/mcp repository has 56 stars and 0 forks, with 2 open issues. It has more stars than 54% of the servers in the directory. It received changes this month. Version published in the registry: 0.16.2 (October 23, 2026).
Stars measure attention, not quality: a recent, heavily promoted project can collect them fast, while a useful but niche server will have few.
Verdict
Runapi ai MCP is a reasonable choice; check the points below before connecting it.
Strengths
- Active project: recent commit
- Listed in the official MCP registry
- Usable remotely, without installation
- Permissive licence (Apache-2.0)
Limitations
- Requires an API key or token
Avoid if…
- You do not want to give credentials to an agent
Alternatives
- OpenScreen4.9K ★
- Remove AI Watermarks6.1K ★
- FunASR20.8K ★
- Oh My Cassette117 ★
- FableCut746 ★
- WeftCut261 ★
Learn more
Frequently asked questions
How do I install Runapi ai MCP?
Runapi ai MCP is distributed as npm package (Node.js, usually started with npx) and a remote server. Add it to your client's MCP configuration (Claude Desktop, Cursor, VS Code…) following the README of runapi-ai/mcp.
Is Runapi ai MCP free?
The code is published under the Apache-2.0 licence and can be used free of charge. It needs an API key: the service it connects to may be paid.
Is Runapi ai MCP safe?
Points to watch: secrets. Give it minimum rights and approve sensitive actions.
Is it an official server?
Nothing says so: it is a project published by runapi-ai on GitHub. Check who maintains it before giving it access.
What are the alternatives to Runapi ai MCP?
In the same category: OpenScreen, Remove AI Watermarks, FunASR, and Oh My Cassette. OpenScreen and Remove AI Watermarks score higher on our grid.
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Neutrality. No affiliate links. No vendor pays to be reviewed, rated or ranked. Reviews are directed by François Chollet, neutral and factual, and every data point is dated and sourced. How we score