vision-mcp
MCP server that provides vision understanding to non-multimodal agents via 4 tools (analyze/describe/OCR image, list providers), supporting 13 vision providers with automatic fallback and secure URL handling.
README
Vision MCP Server
A Model Context Protocol (MCP) server that gives vision understanding to agents connected to non-multimodal models (DeepSeek, older GPT-4, local small models, etc.): the agent hands an image to the MCP tool, the server calls a vision model, and returns text.
Supports major providers in China and the US plus any OpenAI-compatible endpoint. Official SDKs first, abstraction before implementation, zero-intrusion provider additions.
中文文档见 README.zh-CN.md
Features
- 4 tools:
analyze_image/describe_image/ocr_image/list_providers, all returning plain Markdown text - 13 built-in providers: OpenAI / Anthropic / Google Gemini / Qwen (DashScope) / Zhipu / Doubao (Volcengine) / ERNIE (Qianfan) / StepFun / Ollama / Alibaba Bailian / SiliconFlow / OpenRouter / custom OpenAI-compatible endpoint
- Three image inputs: local path / http(s) URL / base64 (data URI or raw base64), auto-sniffed
- Three-tier fallback chain: official SDK → OpenAI-compatible endpoint → native fetch (see SPEC §1)
- Stateless: every call is independent; images and results are never cached; keys are read from environment variables only
Quick start
Option A: npx (published to npm, no repo needed)
npx -y @inferai/vision-mcp
Option B: local build
git clone <repo> && cd vision-mcp
pnpm install
pnpm build
node dist/index.js
MCP configuration examples (stdio)
The server speaks the stdio transport: the MCP client spawns the process and exchanges JSON-RPC messages over stdin/stdout. Configure it wherever your client defines MCP servers:
- Claude Code: project-level
.mcp.jsonor user-level~/.claude.json(mcpServerskey) - Claude Desktop:
claude_desktop_config.json - Any MCP client (Cursor, self-built agents, etc.): same structure
npx version (available after the package is published):
{
"mcpServers": {
"vision-mcp": {
"command": "npx",
"args": ["-y", "@inferai/vision-mcp"],
"env": {
"OPENAI_API_KEY": "sk-...",
"DASHSCOPE_API_KEY": "sk-..."
}
}
}
}
Local development (adjust the path; --env-file-if-exists=.env loads .env natively):
{
"mcpServers": {
"vision-mcp": {
"command": "node",
"args": ["--env-file-if-exists=.env", "/absolute/path/to/vision-mcp/dist/index.js"],
"env": {
"OPENAI_API_KEY": "sk-..."
}
}
}
}
With startup arguments (override provider defaults via argv, see below):
{
"mcpServers": {
"vision-mcp": {
"command": "npx",
"args": [
"-y",
"@inferai/vision-mcp",
"--default-provider=dashscope",
"--siliconflow-api-key=sk-...",
"--siliconflow-model=Qwen/Qwen2.5-VL-7B-Instruct"
],
"env": {
"DASHSCOPE_API_KEY": "sk-..."
}
}
}
}
stdio notes:
- stdout carries the MCP protocol only — the server never prints logs there; diagnostics go to stderr
- the client manages the process lifecycle (spawn on start, kill on exit); no daemon needed
- first
npxrun downloads the package and may take a few seconds - env variables can also come from the shell environment if the client inherits it (no
envblock needed)
Debug with MCP Inspector:
pnpm dlx @modelcontextprotocol/inspector node dist/index.js --xxx-api-key=xxx --xxx2-api-key=xxx
Setting variables
- MCP config
envblock (recommended, most reliable across platforms) — write the variables into theenvobject above .envfile (local development) — copy.env.exampleto.env, fill it in, thennode --env-file-if-exists=.env dist/index.js(Node 22 native, no dotenv needed)- Shell export —
export OPENAI_API_KEY=sk-xxxthen run
Providers without keys show as unavailable in list_providers and report the missing variable when called.
Publishing (before npx works)
pnpm publish # or pnpm release (changeset flow)
Environment variables
Every provider's API_KEY, BASE_URL, and MODEL support environment overrides (convention: <PROVIDER_PREFIX>_API_KEY / <PROVIDER_PREFIX>_BASE_URL / <PROVIDER_PREFIX>_MODEL):
| Provider | Environment variables | Default model |
|---|---|---|
| OpenAI | OPENAI_API_KEY, OPENAI_BASE_URL, OPENAI_MODEL |
gpt-4o |
| Anthropic | ANTHROPIC_API_KEY, ANTHROPIC_BASE_URL, ANTHROPIC_MODEL |
claude-sonnet-4-5 |
| Google Gemini | GEMINI_API_KEY, GEMINI_BASE_URL, GEMINI_MODEL |
gemini-2.5-flash |
| Alibaba DashScope | DASHSCOPE_API_KEY, DASHSCOPE_BASE_URL, DASHSCOPE_MODEL |
qwen-vl-max |
| Zhipu | ZHIPU_API_KEY, ZHIPU_BASE_URL, ZHIPU_MODEL |
glm-4v-flash (free) |
| Volcengine Doubao | VOLCENGINE_ARK_API_KEY, VOLCENGINE_ARK_BASE_URL, VOLCENGINE_ARK_MODEL |
doubao-1.5-vision-pro |
| Baidu Qianfan | QIANFAN_API_KEY, QIANFAN_SECRET_KEY, QIANFAN_BASE_URL, QIANFAN_MODEL |
ernie-4.5-vl-8k |
| StepFun | STEPFUN_API_KEY, STEPFUN_BASE_URL, STEPFUN_MODEL |
step-1v |
| Ollama (local) | OLLAMA_BASE_URL, OLLAMA_MODEL |
— (no built-in default; endpoint and model must be set) |
| Alibaba Bailian | BAILIAN_API_KEY, BAILIAN_BASE_URL (default DashScope compatible mode), BAILIAN_MODEL |
qwen-vl-max |
| SiliconFlow | SILICONFLOW_API_KEY, SILICONFLOW_BASE_URL (default https://api.siliconflow.cn/v1), SILICONFLOW_MODEL |
Qwen/Qwen2.5-VL-72B-Instruct |
| OpenRouter | OPENROUTER_API_KEY, OPENROUTER_BASE_URL (default https://openrouter.ai/api/v1), OPENROUTER_MODEL |
openai/gpt-4o |
| Custom compatible | OPENAI_COMPAT_BASE_URL, OPENAI_COMPAT_API_KEY?, OPENAI_COMPAT_MODEL |
— |
?= optional (has a built-in default);*= required.
Global configuration:
| Environment variable | Default | Description |
|---|---|---|
VISION_MCP_DEFAULT_PROVIDER |
first available | Default provider |
VISION_MCP_DEFAULT_MODEL |
provider default | Default model |
VISION_MCP_PROVIDER_PRIORITY |
table order | Provider priority (comma-separated, high first, e.g. openai,dashscope,zhipu) |
VISION_MCP_MAX_RETRIES |
0 (off) | Per-provider retry count before falling back |
VISION_MCP_MAX_FALLBACKS |
0 (off) | Max provider fallbacks before giving up |
VISION_MCP_MAX_IMAGE_BYTES |
20 MB | Image size limit |
VISION_MCP_TIMEOUT_MS |
60000 | Download & request timeout (ms) |
Fallback chain
When multiple providers are available, calls walk the priority chain: configured default → VISION_MCP_PROVIDER_PRIORITY list → table order (unavailable providers are skipped).
- each provider is retried up to
VISION_MCP_MAX_RETRIEStimes on provider errors (upstream failures, timeouts) - after a provider exhausts its retries, the next available provider in the chain is tried, up to
VISION_MCP_MAX_FALLBACKSfallbacks - only provider errors trigger retry/fallback; config or image errors fail fast
- an explicitly requested
providerargument is tried alone (no fallback) - when everything fails, the error lists every provider attempted and its last error
Also available as argv: --provider-priority=..., --max-retries=N, --max-fallbacks=N (beat env vars).
MCP startup arguments (argv)
Every provider's apiKey / baseUrl / model can be overridden via startup arguments (higher priority than environment variables), format --<provider>-<field>:
node dist/index.js \
--openai-api-key=sk-xxx \
--openai-base-url=https://my-gateway.example.com/v1 \
--openai-model=gpt-4o-mini \
--dashscope-api-key=sk-xxx \
--default-provider=dashscope
- Global:
--default-provider <name>/--default-model <name> - Per provider:
--<provider>-api-key,--<provider>-base-url,--<provider>-model(equals or space form both work) - Any OpenAI-compatible third-party service: wire it up in one line with
--openai-compat-base-url+--openai-compat-api-key+--openai-compat-model; or point any built-in provider'sbase-urlat a mirror/proxy
Priority: tool args provider/model > startup args (per-provider > global default) > environment variables > provider built-in defaults.
Tools
| Tool | Arguments | Description |
|---|---|---|
analyze_image |
image*, prompt?, provider?, model? |
General image analysis |
describe_image |
image*, provider?, model? |
Describe image content (default instruction) |
ocr_image |
image*, language? (auto/zh/en/zh-en), provider?, model? |
OCR, preserving layout |
list_providers |
— | Provider list and configuration status |
image accepts: local path / http(s):// URL / data: URI / raw base64, auto-sniffed.
Security note: URL downloads are SSRF-protected — every hop (including redirects) is validated and URLs resolving to loopback, private, or link-local addresses are blocked (hint in the error explains why).
Provider integration (three-tier fallback chain)
| provider | Integration | Notes |
|---|---|---|
openai / stepfun / ollama / bailian / siliconflow / openrouter / openai-compat |
OpenAI-compatible adapter (openai SDK) | One adapter, configurable baseURL |
anthropic |
Official SDK @anthropic-ai/sdk | messages + image content block |
gemini |
Official SDK @google/generative-ai | generateContent + inlineData |
dashscope |
Native fetch | official npm package has no vision; direct multimodal-generation API |
zhipu |
Native fetch | official SDK accepts string content only; direct v4 API |
volcengine |
Native fetch | official openapi is a management plane; direct Ark API |
qianfan |
Native fetch | official SDK is string-only; AK/SK → token → v2 API |
Adding a provider: for OpenAI-compatible endpoints, add one row to RULES in src/core/config.ts plus one mapping in the factory table in src/index.ts — zero new code. Official SDK or native fetch implementations: see SPEC §1.
Development
pnpm check # biome checks
pnpm test # rstest unit tests (injected mocks, no network)
pnpm build # rslib build
Real-call smoke tests (only run against providers whose keys are configured; skipped otherwise):
OPENAI_API_KEY=sk-... pnpm exec rstest tests/e2e
Architecture
src/
├── index.ts # Entry: composition root, stdio startup
├── core/ # Abstraction: interfaces / image loading / config / registry
├── providers/ # Adapters: official SDK or compatible endpoints, protocol conversion only
└── server/tools.ts # MCP tool layer: zod validation + error mapping
Full spec: SPEC.md.
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