What can you do with this server?

MCP server that connects clients to OpenRouter for multimodal AI chat, analysis, generation, and model discovery. * Chat with OpenRouter models via chat_completion, with optional model, token limit, and temperature. * Analyze images, audio, and video from local paths, URLs, or data URLs, with optional questions/model overrides. * Generate images from prompts with optional reference images, size, aspect ratio, and sandboxed save path. * Generate audio and video; video jobs are async and can be resumed via get_video_status. * Search, inspect, and validate OpenRouter model IDs and capabilities. * README-wide capabilities also include embeddings, reranking, TTS/STT, structured decisions, async chat jobs, health checks, and access to 300+ models.

Which integrations are available for this server?

Offers deployment through Docker containers, with support for environment variables and seamless integration with MCP configurations. Enables use of Google's Gemini models through OpenRouter for text chat and multimodal conversations, with support for vision capabilities and model customization. Provides Node.js-based installation and execution options with NPX support for easy integration into MCP environments. Supports Python-based installation and execution using UV package manager for those preferring Python environments.

How do I use OpenRouter MCP Multimodal Server?

1. Click on "Deploy Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@OpenRouter MCP Multimodal Server analyze this product photo and suggest improvements for the lighting" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

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OpenRouter MCP Multimodal Server

by stabgan

Overview Schema Source Related Servers Discussions Admin

TypeScript

Hybrid

What is this?

OpenRouter MCP Multimodal is a production-grade Model Context Protocol (MCP) server — listed on the official MCP Registry as io.github.stabgan/openrouter-multimodal. It connects AI coding agents (Cursor, Claude Desktop, VS Code, Windsurf, Cline, and others) to OpenRouter's unified LLM API over stdio.

Unlike text-only MCP servers, one install covers the full multimodal surface:

Capability	Tools	Highlights
Chat	`chat_completion`, `start_chat_completion`, `get_chat_completion_status`	300+ models, `:nitro` / `:floor` / `:free` / `:online` / `:exacto` suffixes, provider routing, web search, response caching, reasoning tokens, reasoning effort control, structured output (JSON Schema), async jobs, multi-model fusion, subagent delegation, response healing
Vision	`analyze_image`, `generate_image`, `generate_image_dedicated`	OCR, captioning, VQA, image generation with reference inputs, dedicated Image API with resolution/quality/format control
Audio	`analyze_audio`, `generate_audio`, `text_to_speech`, `speech_to_text`	Transcription, speech/music generation, dedicated TTS (Deepgram, ElevenLabs, OpenAI; free Deepgram default, voices, mp3/pcm), dedicated STT (Whisper, GPT-4o Transcribe, Voxtral, ElevenLabs Scribe)
Video	`analyze_video`, `generate_video`, `generate_video_from_image`, `get_video_status`	Clip understanding, Veo 3.1 / Seedance 2.5 / Kling v3.0 / Wan 2.7 / Grok Imagine Video generation with progress notifications
Embedding	`embed_text`	37+ embedding models (text-embedding-3-small/large, Nomic, Jina, Voyage, etc.)
Decisions	`decide`	Structured yes/no, choice, or score decisions with calibrated probabilities (System One models)
Catalog	`search_models`, `get_model_info`, `validate_model`, `rerank_documents`, `health_check`	Model discovery, validation, reranking, ops health

Production hardening: input/output path sandboxes (including analyze_* local files as of v4.5.2), SSRF guards, structured errors with _meta.code, MCP 2025-11-25 structured outputs + tool icons, async video progress notifications, and 3929 automated tests (3905 unit/mock + 7 regression + 17 live integration).

Related MCP server: OpenRouter MCP Multimodal Server

Quick start

1. Get an API key (free tier works) → openrouter.ai/keys

2. Run the server

export OPENROUTER_API_KEY=sk-or-v1-...
npx -y @stabgan/openrouter-mcp-multimodal

3. Add to your MCP client — copy one JSON block from Install into your client config:

Client	Config location
Cursor	Project: `.cursor/mcp.json` · User: Cursor Settings → MCP
Claude Desktop	macOS: `~/Library/Application Support/Claude/claude_desktop_config.json` · Windows: `%APPDATA%\Claude\claude_desktop_config.json`
VS Code	`.vscode/mcp.json` (workspace) or User Settings → MCP
Windsurf	Windsurf Settings → MCP (same `mcpServers` JSON shape as Cursor)

Use the mcpServers object from Manual config below.

No credits required to start. Free models such as google/gemma-4-26b-a4b-it:free work for chat and vision. Video/audio generation typically needs credits.

Install

MCP servers are distributed through several packaging models. This server is implemented in Node.js/TypeScript; the table below maps each ecosystem method to how you run it here.

Method	Runtime	Best for	This server
npx	Node.js 22+	Most MCP clients (default)	✅ `@stabgan/openrouter-mcp-multimodal`
uvx / pipx	Python 3.10+ and Node.js 22+	Python-first workflows, same pattern as PyPI MCP servers	✅ `mcp-server-openrouter-multimodal`
npm global	Node.js 22+	Pin a version without re-downloading	✅
node (local)	Node.js 22+	Contributors / air-gapped builds	✅
Docker Hub	Docker	Isolation, no Node on host	✅ `stabgan/openrouter-mcp-multimodal`
GHCR	Docker	GitHub-native OCI pulls	✅ `ghcr.io/stabgan/openrouter-mcp-multimodal`
Smithery CLI	Node.js (via installer)	Interactive install into Claude/Cursor/etc.	✅
MCP Registry	npm or OCI	Official discovery (`io.github.stabgan/openrouter-multimodal`)	✅ listing
One-click deeplinks	Node.js	Cursor, VS Code, Kiro	✅
Claude Code CLI	Node.js	Terminal-first Claude Code users	✅
MCP Inspector	Node.js	Debug / list tools locally	✅
Windows `cmd /c npx`	Node.js	Claude Desktop / Cursor when `npx` not on GUI PATH	✅ see below
pip / uv (direct)	—	Native Python MCP servers only	— use uvx row above
DXT desktop extensions	—	Bundled Claude Desktop `.dxt`	not yet
Remote HTTP / SSE	—	Hosted Smithery / Cloudflare endpoints	via Smithery

uvx vs npx: In the MCP ecosystem, npx runs npm (Node) packages and uvx runs PyPI (Python) packages. Because this server is Node-based, uvx uses a thin Python launcher that execs npx -y @stabgan/openrouter-mcp-multimodal — you still need Node installed.

One-click

Paste your OPENROUTER_API_KEY when prompted — deeplinks use placeholders so secrets never appear in URLs.

Manual config

export OPENROUTER_API_KEY=sk-or-v1-...
npx -y @stabgan/openrouter-mcp-multimodal

{
  "mcpServers": {
    "openrouter": {
      "command": "npx",
      "args": ["-y", "@stabgan/openrouter-mcp-multimodal"],
      "env": {
        "OPENROUTER_API_KEY": "sk-or-v1-..."
      }
    }
  }
}

Pin a release: "args": ["-y", "@stabgan/openrouter-mcp-multimodal@5.1.3"]

Install uv (includes uvx), ensure Node.js 22+ is also on your PATH, then:

export OPENROUTER_API_KEY=sk-or-v1-...
uvx mcp-server-openrouter-multimodal
# pin npm version: OPENROUTER_MCP_NPM_VERSION=5.1.3 uvx mcp-server-openrouter-multimodal

{
  "mcpServers": {
    "openrouter": {
      "command": "uvx",
      "args": ["mcp-server-openrouter-multimodal"],
      "env": {
        "OPENROUTER_API_KEY": "sk-or-v1-..."
      }
    }
  }
}

pipx equivalent: pipx run mcp-server-openrouter-multimodal

Optional: OPENROUTER_MCP_NPM_VERSION=5.1.3 pins the underlying npm package.

npm install -g @stabgan/openrouter-mcp-multimodal

{
  "mcpServers": {
    "openrouter": {
      "command": "openrouter-multimodal",
      "env": { "OPENROUTER_API_KEY": "sk-or-v1-..." }
    }
  }
}

git clone https://github.com/stabgan/openrouter-mcp-multimodal.git
cd openrouter-mcp-multimodal
npm ci && npm run build

{
  "mcpServers": {
    "openrouter": {
      "command": "node",
      "args": ["/absolute/path/to/openrouter-mcp-multimodal/dist/index.js"],
      "env": { "OPENROUTER_API_KEY": "sk-or-v1-..." }
    }
  }
}

docker run --rm -i -e OPENROUTER_API_KEY=sk-or-v1-... stabgan/openrouter-mcp-multimodal:latest

{
  "mcpServers": {
    "openrouter": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "-e",
        "OPENROUTER_API_KEY=sk-or-v1-...",
        "stabgan/openrouter-mcp-multimodal:latest"
      ]
    }
  }
}

Use -i (interactive stdio). Avoid -t (TTY corrupts MCP framing on some hosts).

docker run --rm -i -e OPENROUTER_API_KEY=sk-or-v1-... \
  ghcr.io/stabgan/openrouter-mcp-multimodal:5.1.3

{
  "mcpServers": {
    "openrouter": {
      "command": "docker",
      "args": [
        "run",
        "--rm",
        "-i",
        "-e",
        "OPENROUTER_API_KEY=sk-or-v1-...",
        "ghcr.io/stabgan/openrouter-mcp-multimodal:5.1.3"
      ]
    }
  }
}

Interactive install (writes config for your client):

npx -y @smithery/cli install @stabgan/openrouter-mcp-multimodal --client claude
# or: --client cursor | vscode | windsurf | ...

Listing: smithery.ai/server/@stabgan/openrouter-mcp-multimodal

Official name: io.github.stabgan/openrouter-multimodal

Registry: registry.modelcontextprotocol.io
npm package: @stabgan/openrouter-mcp-multimodal
OCI image: docker.io/stabgan/openrouter-mcp-multimodal

Clients that support registry-driven install will offer npm or Docker; otherwise use the JSON blocks above.

claude mcp add openrouter -- npx -y @stabgan/openrouter-mcp-multimodal
# project scope:
claude mcp add --scope project openrouter -- npx -y @stabgan/openrouter-mcp-multimodal

Set OPENROUTER_API_KEY in your shell or client env before starting Claude Code.

Debug tools/list and tool calls against a live OpenRouter key:

export OPENROUTER_API_KEY=sk-or-v1-...
npx -y @modelcontextprotocol/inspector npx -y @stabgan/openrouter-mcp-multimodal

When Claude Desktop or Cursor cannot find npx (GUI apps often miss shell PATH), wrap with cmd:

{
  "mcpServers": {
    "openrouter": {
      "command": "cmd",
      "args": ["/c", "npx", "-y", "@stabgan/openrouter-mcp-multimodal"],
      "env": { "OPENROUTER_API_KEY": "sk-or-v1-..." }
    }
  }
}

If still failing, use the full path from where npx as the command.

Why this server?

Capability	This server	Typical MCP LLM servers
Text chat (300+ models)	✅	✅
Image analysis + generation	✅	partial
Audio analysis + TTS + STT	✅	❌
Video analysis + generation	✅	❌
Vector embeddings (37+ models)	✅	❌
Structured decisions (System One)	✅	❌
Model search / validate / rerank	✅	❌
Path sandbox + SSRF protection	✅	rare
MCP 2025 structured outputs	✅	rare
Async video + progress notifications	✅	❌

Tools

21 MCP tools. Each description includes Use when, Good/Bad examples, Fails when, and Works with so agents pick the right tool and recover from errors.

Tool	Purpose
`chat_completion`	Text chat, web search, provider routing, caching, reasoning, structured output
`start_chat_completion`	Async background job for long-running reasoning models
`get_chat_completion_status`	Poll / retrieve async completion results
`analyze_image`	Vision — local path, URL, or data URL + `question`
`analyze_audio`	Transcribe / analyze audio files
`analyze_video`	Describe / Q&A over video files
`generate_image`	Text-to-image via chat completions with reference images
`generate_image_dedicated`	Text-to-image via dedicated `/api/v1/images` (resolution, quality, format)
`generate_audio`	Text-to-speech / music via chat completions
`text_to_speech`	Dedicated TTS (`/api/v1/audio/speech`) — Deepgram, ElevenLabs, OpenAI; voices, speed, mp3/pcm
`speech_to_text`	Dedicated STT (`/api/v1/audio/transcriptions`) — Whisper, GPT-4o Transcribe, Voxtral, ElevenLabs Scribe
`generate_video`	Text-to-video (async, resumable)
`generate_video_from_image`	Image-to-video (narrower schema)
`get_video_status`	Poll / resume video jobs
`search_models`	Paginated model catalog search
`get_model_info`	Pricing, context, modalities
`validate_model`	Cheap model ID existence check
`rerank_documents`	Relevance ranking for RAG
`embed_text`	Vector embeddings (37+ models: text-embedding-3-small/large, Nomic, etc.)
`decide`	Structured decisions with calibrated probabilities (System One models)
`health_check`	API key + reachability probe

Every error carries _meta.code from a closed taxonomy (13 codes). Switch on these for programmatic handling:

`_meta.code`	Meaning	Recovery
`INVALID_INPUT`	Bad or missing arguments	Check tool description for correct schema
`INVALID_CREDENTIALS`	API key missing, invalid, or revoked	Regenerate at openrouter.ai/keys
`UNSAFE_PATH`	Local path escaped the input/output sandbox	Move files under `OPENROUTER_INPUT_DIR` / `OPENROUTER_OUTPUT_DIR`
`UPSTREAM_HTTP`	Non-auth HTTP error from OpenRouter (4xx/5xx)	Check `_meta.details.status`; retry if transient
`UPSTREAM_TIMEOUT`	Upstream did not respond in time	Retry, or use `start_chat_completion` for slow models
`UPSTREAM_REFUSED`	Content policy, rate limit, or insufficient credits	Check `_meta.retry_after_seconds`; review prompt or add credits
`UNSUPPORTED_FORMAT`	File is not a recognized media format	Verify file type matches tool expectations
`RESOURCE_TOO_LARGE`	File exceeds fetch/inline size cap	Trim file or use `save_path` to skip inline
`ZDR_INCOMPATIBLE`	Model/provider requires zero data retention	Use a ZDR-compatible provider or different model
`MODEL_NOT_FOUND`	Model slug not in OpenRouter catalog	Run `validate_model` or `search_models` first
`JOB_FAILED`	Async job (video/chat) failed on provider side	Check `_meta.details`; retry or change model
`JOB_STILL_RUNNING`	Async job not yet complete (not an error)	Call `get_video_status` / `get_chat_completion_status` to poll
`INTERNAL`	Unexpected server-side error	Report if reproducible

Errors include _meta.suggestions with agent-oriented next steps when available.

Binary tool results (v4.7.0+)

Generate tools (generate_image, generate_image_dedicated, generate_audio, text_to_speech, generate_video, generate_video_from_image, get_video_status) return image, audio, or video bytes. As of 4.7.0 the behavior is explicit:

`save_path`	Tool result
Set	Text pointer only — e.g. `Image saved to: out.png (… bytes, image/png)` plus `_meta.save_path`. No inline base64 (avoids duplicating large payloads in the MCP channel).
Unset, under byte ceiling	Inline media block and summary text (images/audio use MCP `image` / `audio` types; video uses MCP `resource` blocks).
Unset, over ceiling	Text only with a hint to pass `save_path`.

Default inline ceilings (override per kind or globally):

Kind	Default	Env vars (precedence: per-kind → global)
Image	1 MiB	`OPENROUTER_IMAGE_INLINE_MAX_BYTES` → `OPENROUTER_INLINE_MAX_BYTES`
Audio	1 MiB	`OPENROUTER_AUDIO_INLINE_MAX_BYTES` → `OPENROUTER_INLINE_MAX_BYTES`
Video	10 MiB	`OPENROUTER_VIDEO_INLINE_MAX_BYTES` → `OPENROUTER_INLINE_MAX_BYTES`

If you previously relied on both a saved file and inline media in the same tool result, read the file from _meta.save_path (or omit save_path to get inline media when under the ceiling).

Examples

Chat (free model)

{
  "tool": "chat_completion",
  "arguments": {
    "model": "google/gemma-4-26b-a4b-it:free",
    "messages": [{ "role": "user", "content": "Summarize MCP in one sentence." }]
  }
}

Chat with structured output (JSON Schema)

{
  "tool": "chat_completion",
  "arguments": {
    "model": "openai/gpt-4o",
    "messages": [{ "role": "user", "content": "Extract the name and age from: 'Alice is 30 years old.'" }],
    "response_format": {
      "type": "json_schema",
      "json_schema": {
        "name": "person",
        "schema": {
          "type": "object",
          "properties": {
            "name": { "type": "string" },
            "age": { "type": "integer" }
          },
          "required": ["name", "age"]
        }
      }
    }
  }
}

For simpler JSON without a schema, use "response_format": { "type": "json_object" }. Add "response_healing": true to auto-fix malformed JSON.

Analyze an image

{
  "tool": "analyze_image",
  "arguments": {
    "image_path": "diagram.png",
    "question": "List every label in this diagram."
  }
}

Use image_path and question — not image / prompt.

Search models (vision + free)

{
  "tool": "search_models",
  "arguments": {
    "query": "gemma",
    "capabilities": { "vision": true },
    "limit": 10,
    "offset": 0
  }
}

Generate video (async)

{
  "tool": "generate_video",
  "arguments": {
    "model": "google/veo-3.1",
    "prompt": "Ocean waves at sunrise, cinematic drone shot",
    "duration": 4,
    "save_path": "river.mp4"
  }
}

If the job is still running when max_wait_ms elapses, the response succeeds with _meta.code: JOB_STILL_RUNNING and a video_id — call get_video_status to resume. This is not an error.

With save_path set (as above), the result is a text pointer to the saved file once complete — not inline video. See Binary tool results.

Embed text (vector embeddings)

{
  "tool": "embed_text",
  "arguments": {
    "texts": ["What is MCP?", "Model Context Protocol enables tool use for LLMs."],
    "model": "openai/text-embedding-3-small",
    "dimensions": 1024
  }
}

Returns embedding arrays for RAG, semantic search, or clustering. 37+ models supported — pass a single string or an array of up to 2048 texts.

Structured decision (System One)

{
  "tool": "decide",
  "arguments": {
    "questions": {
      "is_bug": {
        "type": "noul",
        "instructions": "Is this a bug report or a feature request?",
        "criteria": {
          "true": "Describes broken or incorrect behavior",
          "false": "Requests new functionality"
        }
      }
    },
    "state": {
      "ticket": "The login button does not respond when clicked on Safari."
    }
  }
}

Returns calibrated probabilities instead of generated text. Three question types: noul (yes/no), choice (pick one category), score (ordinal rubric). Models: typesafe/jev-1.13 (default), upstage/solar-decide, microsoft/decision-1.

More examples: docs/plans/tool-description-improvement.md

Security

Input path sandbox — local paths on analyze_* and reference images must stay inside OPENROUTER_INPUT_DIR (falls back to OPENROUTER_OUTPUT_DIR, then cwd)
Output path sandbox — save_path must stay inside OPENROUTER_OUTPUT_DIR
Async job reads — get_chat_completion_status resolves disk paths only under OPENROUTER_OUTPUT_DIR/openrouter-jobs/ (4.7.0+)
SSRF protection — private/reserved IPs blocked on URL fetches
Untrusted content — analyze outputs tagged _meta.content_is_untrusted: true
Prototype-pollution defense — all API output boundaries (model records, embeddings, decisions, rerank results, log context) recursively strip __proto__, constructor, and prototype keys before forwarding to MCP clients
Secret redaction — the stderr JSON logger redacts API keys and sensitive values; stdout is reserved for MCP protocol traffic

Override sandboxes only with OPENROUTER_ALLOW_UNSAFE_PATHS=1 (discouraged).

Report vulnerabilities: SECURITY.md (private disclosure — do not file public issues for exploits).

Configuration

Variable	Required	Default	Description
`OPENROUTER_API_KEY`	Yes	—	OpenRouter API key
`OPENROUTER_DEFAULT_MODEL`	No	`google/gemma-4-26b-a4b-it:free`	Default when tools omit `model`
`OPENROUTER_OUTPUT_DIR`	No	`cwd`	Sandbox root for `save_path`
`OPENROUTER_INPUT_DIR`	No	`OUTPUT_DIR` or `cwd`	Sandbox root for local input files
`OPENROUTER_INLINE_MAX_BYTES`	No	`1048576` (image/audio)	Global inline media ceiling
`OPENROUTER_IMAGE_INLINE_MAX_BYTES`	No	falls back to global	Per-kind inline ceiling
`OPENROUTER_AUDIO_INLINE_MAX_BYTES`	No	falls back to global	Per-kind inline ceiling
`OPENROUTER_VIDEO_INLINE_MAX_BYTES`	No	`10485760`	Video inline ceiling
`OPENROUTER_LOG_LEVEL`	No	`info`	`error` / `warn` / `info` / `debug`

See .env.example for the full list (provider routing, fetch limits, caching, video polling, async jobs, integration-test overrides).

Development

git clone https://github.com/stabgan/openrouter-mcp-multimodal.git
cd openrouter-mcp-multimodal
npm install
cp .env.example .env   # add OPENROUTER_API_KEY
npm run build

Testing

Command	What it runs
`npm test`	3905 unit + mock tests (no API key, <20s)
`npm run test:regression`	7 security + schema regression guards
`npm run test:integration`	17 live OpenRouter scenarios (requires `.env` key)
`npm run test:e2e`	Full MCP stdio smoke (`scripts/live-e2e.mjs`)
`npm run ci`	lint + format + version sync + build + all tests

Free models for CI / zero-credit accounts: integration tests default to google/gemma-4-26b-a4b-it:free (override with OPENROUTER_INTEGRATION_MODEL). GitHub Actions requires the OPENROUTER_API_KEY repository secret.

Mock tests live under src/__tests__/mock/ and cover handlers, path sandboxes, SSRF blocks, model-cache pagination, tool descriptions, and structured outputs — 396 additional cases beyond the core suite.

npm run lint
npm run format:check
npm run version:check   # package.json vs src/version.ts, server.json, pyproject.toml

Releasing

Published artifacts (npm, PyPI/uvx, Docker, GHCR) all ship from the same semver on a git tag (vX.Y.Z). Pushing to main runs tests but does not publish to npm or PyPI.

Normal flow: merge conventional commits to main → Release Please opens a Release PR → merge it → tag is created → CI publishes everywhere.

Manual flow: bump all version files → npm run version:check → npm run ci + smoke tests → commit → git tag vX.Y.Z → git push origin vX.Y.Z.

Full checklist, file list, CI secrets, and agent instructions:

docs/RELEASING.md — maintainer release guide
AGENTS.md — quick reference for AI agents

Troubleshooting

Symptom	Likely cause	Fix
Server exits immediately / `OPENROUTER_API_KEY is required`	Missing or empty API key	Set `OPENROUTER_API_KEY` in client `env` or shell — get one at openrouter.ai/keys
`_meta.code: INVALID_CREDENTIALS` or HTTP 401	Bad or revoked key	Regenerate at openrouter.ai/keys; restart the MCP client
`_meta.code: MODEL_NOT_FOUND`	Typo or retired model ID	Run `search_models` or `validate_model`; check openrouter.ai/models
HTTP 402 / insufficient credits	Paid model or generation on zero balance	Add credits at openrouter.ai/credits or use a `:free` model
`_meta.code: UPSTREAM_HTTP` with 429	Rate limit	Wait for `_meta.retry_after_seconds` if present; reduce concurrency
`_meta.code: UNSAFE_PATH`	Local path outside sandbox	Put files under `OPENROUTER_INPUT_DIR` or set `OPENROUTER_OUTPUT_DIR` wider; see Security
`npx` not found (Windows GUI apps)	GUI `PATH` differs from terminal	Use the Windows npx `cmd /c` wrapper
No inline image/audio after upgrade	v4.7.0 with `save_path` set	Expected — result is text + `_meta.save_path` only; omit `save_path` or read the saved file
MCP client shows stale tool list	Client cache	Restart MCP / reload window after upgrading the package pin

Structured errors include _meta.suggestions with agent-oriented next steps when available.

FAQ

Do I need paid OpenRouter credits?

No, to get started. Free models work for chat and vision. Audio/video generation usually requires credits; analysis may return 402 on some models — the server surfaces that as a structured error.

Which MCP clients are supported?

Any MCP-compatible client over stdio: Cursor, Claude Desktop, VS Code Copilot, Windsurf, Cline, Kiro, and custom agents.

How is this different from calling OpenRouter directly?

This server adds MCP tool schemas, security sandboxes, error taxonomy, model caching, async video polling with progress notifications, and agent-oriented tool descriptions — so LLMs invoke the right capability without custom HTTP glue.

Where is the security advisory for path traversal?

Fixed in 4.5.2+ — see GHSA-3q7p-736f-x44v, SECURITY.md, and docs/solutions/security-issues/.

Compatibility

Works with any MCP client. Protocol: MCP 2025-11-25 (backwards-compatible with 2025-06-18 and earlier). Node ≥ 22 (Docker image uses Node 24).

License

Apache 2.0 — see LICENSE.

Contributing

Issues and PRs welcome. For large changes, open an issue first.

Before submitting: run npm run ci. Use Conventional Commits (fix:, feat:, etc.) so Release Please can cut the next release. See docs/RELEASING.md if you need to ship a version.

Available Tools

11 tools

analyze_audioB

Read-only

Analyze or transcribe an audio file using a multimodal model

Inputs: audio_path (required), model, question.

analyze_imageB

Read-only

Analyze an image using a vision model

Inputs: image_path (required), model, question.

analyze_videoA

Read-only

Analyze or transcribe a video file using a multimodal model. Accepts mp4, mpeg, mov, or webm from a local file path, HTTP(S) URL, or base64 data URL. Default model: google/gemini-2.5-flash.

Inputs: video_path (required), model, question.

chat_completionB

Send messages to an OpenRouter model and get a response

Inputs: messages (required), model, max_tokens, temperature.

generate_audioA

Generate audio from a text prompt. Conversational models (e.g. openai/gpt-audio) respond in spoken audio. Music models (e.g. google/lyria-3-clip-preview) need a structured prompt. Output format is auto-detected and file extension is corrected automatically.

Inputs: prompt (required), model, voice, format, +1 more.

generate_imageA

Generate an image from a text prompt. Optionally conditioned on one or more reference images (file paths, http(s) URLs, or data URLs) for character / style consistency. Sends modalities: ["image","text"] by default; override via the modalities field if needed.

Inputs: prompt (required), model, save_path, image_size, +4 more.

generate_videoA

Generate a video from a text prompt using an OpenRouter video-generation model (default: google/veo-3.1). Submits an async job, polls until completion or max_wait_ms, then downloads the result. Optionally conditioned on first/last-frame images or reference images. Large outputs are auto-saved when save_path is provided and path-sandboxed.

Inputs: prompt (required), seed, model, duration, +9 more.

get_model_infoC

Read-onlyIdempotent

Get details about a specific model

Inputs: model (required).

get_video_statusA

Read-onlyIdempotent

Resume a previously submitted video generation job by id. Returns the latest status; if completed, downloads the video (and saves it when save_path is provided).

Inputs: video_id (required), save_path.

search_modelsC

Read-onlyIdempotent

Search available OpenRouter models

Inputs: limit, query, provider, capabilities.

validate_modelA

Read-onlyIdempotent

Check if a model ID exists

Inputs: model (required).

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

Loading tool schema changelog…

Deploy Server

One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

B3.4/5.0

Scored 2026-05-04 11:15 across 11 tools

Disambiguation5/5

Each tool targets a distinct function: analyzing audio/image/video, generating content, chat completions, and model queries. No two tools have overlapping purposes, and even the video generation status tool is clearly a helper for async workflows.

Naming Consistency4/5

Most tools follow a verb_noun pattern (analyze_, generate_, get_, search_, validate_). The exception is 'chat_completion', which combines two nouns rather than a verb_noun, causing a minor inconsistency in the naming style.

Tool Count5/5

With 11 tools, the set covers all major modalities (audio, image, video, text) and supporting functions (model info, search, validation). The count is well-balanced—not excessive or too sparse for the server's multimodal purpose.

Completeness4/5

Core analysis, generation, and query tools are present. Some minor gaps exist (e.g., no explicit tool for listing all models, though search_models and get_model_info cover it). Overall, the surface is comprehensive for typical multimodal workflows.

Maintenance

ActivityMaintained

ResponsivenessMixed handling

Resources

Related MCP Connectors

LLM Gateway
io.github.theopenco
Chat with any LLM, generate images, browse models and check your usage and costs.
AI & Machine Learning Developer Tools
11,715
https://api.llmgateway.io/mcp
APICK AIA
app.apick
LLM chat, text tools, image generation, editing, batch image jobs, and asynchronous video generation
AI & Machine Learning Image & Video Processing
1511
https://apick.app/mcp/ai
RelaySwitchA
io.relayswitch
Every major chat, image and video model on one prepaid key. OpenAI, Anthropic and Gemini formats.
AI & Machine Learning Developer Tools
151
https://api.relayswitch.io/mcp
UnoRouterA
com.unorouter
Search UnoRouter models, free ones included, check prices and chat through one OpenAI-compatible key
AI & Machine Learning Search
32
https://mcp.unorouter.com/mcp

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What is this?

Quick start

Install

One-click

Manual config

Why this server?

Tools

Binary tool results (v4.7.0+)

Examples

Chat (free model)

Chat with structured output (JSON Schema)

Analyze an image

Search models (vision + free)

Generate video (async)

Embed text (vector embeddings)

Structured decision (System One)

Security

Configuration

Development

Testing

Releasing

Troubleshooting

FAQ

Do I need paid OpenRouter credits?

Which MCP clients are supported?

How is this different from calling OpenRouter directly?

Where is the security advisory for path traversal?

Compatibility

License

Contributing

Available Tools

Tool Schema Changelog

TDQS

Maintenance

Resources

Related MCP Connectors

Related MCP Servers

OpenRouter MCP Server

OpenRouter MCP Multimodal

OpenRouter MCP Server

Vision MCP Server

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