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seeya-mcp
seeya-mcp/dist/index.mjs

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Readme

seeya-mcp

An MCP server that gives a non-vision agent the ability to analyze images (screenshots, diagrams, UI mockups, photos) using a vision-capable model. Switch freely between one of three providers:

Provider prefix	Backend	Auth
`google/*`	`@google/genai`	`GEMINI_API_KEY`
`anthropic/*`	`@anthropic-ai/sdk`	`ANTHROPIC_API_KEY`, or none — falls back to your local Claude Code CLI subscription
`opencode/`	`@opencode-ai/sdk`	none — reuses your local opencode go/zen subscription

Models are addressed with an opencode-style provider/model id, e.g. google/gemini-2.5-flash, anthropic/claude-sonnet-4-6, opencode-go/kimi-k2.7-code.

Getting started

Add the following to your MCP client config:

{
  "mcpServers": {
    "seeya": {
      "type": "local",
      "command": [
          "npx",
          "-y",
          "seeya-mcp@latest"
      ],
      "env": {
        "GEMINI_API_KEY": "your-google-ai-studio-key",
        "ANTHROPIC_API_KEY": "your-anthropic-api-key (omit to use your Claude Code CLI subscription instead)"
      },
    }
  }
}

The default model is google/gemini-2.5-flash, so a GEMINI_API_KEY gets you running. Provide whichever key(s) match the backend you want (see below).

Tools

Tool	What it does
`analyze_image`	Analyze a local file path or `http(s)` URL, with an optional prompt. Optionally override the model for that one call.
`set_vision_model`	Set and persist the active vision model (`provider/model`).
`get_vision_model`	Return the currently active vision model.
`list_vision_models`	List vision-capable models across all backends.

Configuration

Env var	Purpose
`GEMINI_API_KEY`	Auth for `google/*` models.
`ANTHROPIC_API_KEY`	Auth for `anthropic/*` models. When unset, the backend shells out to the Claude Code CLI instead (see below).
`OPENCODE_BASE_URL`	Point the opencode backend at a specific server (see below). Optional.
`SEEYA_MCP_DEFAULT_MODEL`	Default model when no config file exists (built-in default `google/gemini-2.5-flash`).
`SEEYA_MCP_CONFIG`	Override the config file path.

The active model persists to ~/.seeya-mcp/config.json ({ "model": "provider/model" }) and survives restarts. Switch it at runtime with set_vision_model.

Anthropic without an API key (Claude Code subscription)

If ANTHROPIC_API_KEY is not set, the anthropic/* backend doesn't call the Anthropic SDK — it shells out to the locally installed Claude Code CLI (claude -p), which uses whatever auth Claude Code already has (e.g. your Pro/Max subscription via OAuth). No key needed.

How it works: the loaded image is written to a throwaway temp dir, claude -p --model <id> --allowedTools Read --output-format json runs there with the prompt piped over stdin, and its Read tool loads the image. The result text is returned to the caller.

Requirements & notes:

The claude CLI must be installed and on PATH (npm i -g @anthropic-ai/claude-code) and signed in. If it's missing, analyze_image returns a clear error telling you to install it or set ANTHROPIC_API_KEY.
The CLI path runs an extra model turn (to call the Read tool), so it's a little slower than the direct SDK call.
Set ANTHROPIC_API_KEY to skip the CLI entirely and talk to the API directly.

opencode connectivity

opencode's HTTP server uses a random, undiscoverable port when you run the TUI (only opencode serve defaults to 4096), and there is no env var or lock file that exposes it (opencode#9099). So seeya-mcp does not try to find your running opencode — it resolves a server in one of two ways:

OPENCODE_BASE_URL is set → it talks to that URL verbatim. Use this to point at an opencode serve you manage, or a TUI pinned to a fixed port ({ "server": { "port": 4096 } } in your opencode config).
Otherwise (default) → it spawns its own private opencode serve on a free port, reads the port opencode actually bound, and reuses that server for the process lifetime. This works whether or not a TUI is running — it just needs the opencode CLI on PATH and your existing opencode auth (the spawned server reads the same config, providers, and opencode-go / Zen models).

Notes:

The first analyze_image call pays a ~2–4s cold start while the server spawns; subsequent calls reuse it.
The managed server is torn down on exit/SIGINT/SIGTERM. On a Windows force-kill it may linger as an idle process.
If you set OPENCODE_SERVER_PASSWORD, prefer running your own authed opencode serve and setting OPENCODE_BASE_URL — the spawned server inherits the password but the client won't send it.

Development

npm i
npm run dev

Requirements

Node.js >= 20

License

MIT