EvoLink MCP

The EvoLink MCP server enables AI agents to generate images, videos, and audio using over 150 models. It allows agents to query model capabilities, check pricing and billing conditions before generation, and execute creative tasks like creating product shots or cinematic short films.

Endpoint and access

OAuth sign-in: the first time you connect, your client opens the vendor's own authorization prompt in a browser.

OAuth sign-inEndpoint checked 2026-10-26Operated by EvoLink

MCP endpoint (Streamable HTTP)

https://mcp.evolink.ai/mcp

Vendor documentation

What you can do with it

Generate images such as product shots or hero illustrations
Create short cinematic videos from text descriptions
Query models to compare input requirements and output capabilities
Check costs and billing conditions before generating content

Connect from your client

Each snippet registers the same endpoint; pick the client you use.

This server is operated by the named third party. Listing and endpoint checks are not an endorsement or a security audit. Review the operator's permissions, terms, and data handling before connecting. How listings are checked and corrected.

Claude Code

Run this once in a terminal. It registers a Streamable HTTP server. Use --scope project to write .mcp.json for the repo.

Claude Code configuration

claude mcp add --transport http evolink-mcp https://mcp.evolink.ai/mcp

Codex

Run this once. Codex stores MCP servers in ~/.codex/config.toml (or .codex/config.toml in a trusted project).

Codex configuration

codex mcp add evolink-mcp --url https://mcp.evolink.ai/mcp

Cursor

Merge this server into .cursor/mcp.json in your project, then enable evolink-mcp in your MCP settings.

Cursor configuration

{
  "mcpServers": {
    "evolink-mcp": {
      "url": "https://mcp.evolink.ai/mcp"
    }
  }
}

Cline

Merge this into cline_mcp_settings.json (Cline → MCP Servers → Configure). The type must be streamableHttp for a remote HTTP server.

Cline configuration

{
  "mcpServers": {
    "evolink-mcp": {
      "type": "streamableHttp",
      "url": "https://mcp.evolink.ai/mcp",
      "disabled": false
    }
  }
}

VS Code

Merge this server into .vscode/mcp.json. Use MCP: List Servers to start evolink-mcp and inspect its tools.

VS Code configuration

{
  "servers": {
    "evolink-mcp": {
      "type": "http",
      "url": "https://mcp.evolink.ai/mcp"
    }
  }
}

Gemini CLI

Run this once. It writes .gemini/settings.json in the current project; pass --scope user for ~/.gemini/settings.json.

Gemini CLI configuration

gemini mcp add --transport http evolink-mcp https://mcp.evolink.ai/mcp

Claude Desktop

Merge this into claude_desktop_config.json (macOS: ~/Library/Application Support/Claude/, Windows: %APPDATA%\Claude\), then restart Claude Desktop.

Claude Desktop configuration

{
  "mcpServers": {
    "evolink-mcp": {
      "url": "https://mcp.evolink.ai/mcp"
    }
  }
}

Windsurf

Merge this into ~/.codeium/windsurf/mcp_config.json, then refresh MCP in Cascade. Windsurf remote servers use serverUrl, not url.

Windsurf configuration

{
  "mcpServers": {
    "evolink-mcp": {
      "serverUrl": "https://mcp.evolink.ai/mcp"
    }
  }
}

Ground your agent in cited data

EvoLink MCP gives your agent tools. Koskamo gives it reviewed, cited facts to check its answers against. Add it as a second MCP server; public reads need no API key.

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