{ "data": { "a": { "slug": "google-veo", "name": "Google Veo", "vendor": "Google", "vendorUrl": "https://ai.google.dev", "kind": "model", "category": "video-generation", "summary": "Google's Veo video models with native audio, through Vertex AI (Gemini Enterprise Agent Platform). The Gemini API's Veo models shut down by 22 October 2026.", "url": "https://www.anchorterminal.com/tools/google-veo", "markdownUrl": "https://www.anchorterminal.com/tools/google-veo.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/google-veo.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/google-veo.json", "dns": "google-veo.grade.anchorterminal.com", "repo": "https://github.com/googleapis/python-genai", "license": "Apache-2.0 (SDKs)", "transports": [ "http" ], "remoteUrl": "https://us-central1-aiplatform.googleapis.com/v1", "packages": [ { "registry": "pypi", "name": "google-genai" }, { "registry": "npm", "name": "@google/genai" } ], "auth": "api-key", "authNotes": "Google Cloud OAuth (service account or gcloud token) with IAM on Vertex AI. Google's OAuth guide and the Vertex AI discovery document also document an `access_token` query parameter. The Gemini API route with an AI Studio key no longer serves Veo.", "pricing": "usage", "pricingNotes": "No free tier for Veo. Vertex AI bills per count of generated video. Veo 3.1 with audio $0.40 at 720p and 1080p, $0.60 at 4K, or $0.20 and $0.40 without audio. Veo 3.1 Fast with audio $0.10 at 720p, $0.12 at 1080p, $0.30 at 4K. Veo 3.1 Lite with audio $0.05 at 720p and $0.08 at 1080p, or $0.03 and $0.05 without audio (https://cloud.google.com/model-garden/pricing).", "priceSummary": "Pay per use", "where": "hosted", "x402": { "level": "no", "evidence": "No machine payment. Needs billing on a Google Cloud project (checked 2026-09-30).", "endpoints": [] }, "toolCount": null, "popularity": { "githubStars": 4000, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-09-30" }, "docsUrl": "https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/veo/3-1-generate", "rateLimitsUrl": "https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/quotas", "llmsTxt": "https://aistudio.google.com/llms.txt", "capabilities": [ "video.generate", "video.image-to-video", "video.audio", "video.extend" ], "tags": [ "official", "hosted", "closed-source", "card-required", "llms-txt", "async-jobs", "python", "typescript", "watermark" ], "lastRelease": "2026-10-29", "graded": true, "anchor": { "graded": true, "score": 69.3, "grade": "B", "agentReady": false, "rank": 253, "ranked": true, "rankOf": 1510, "categoryRank": 2, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 64, "maintenance": 77, "payments": 20, "reliability": 87, "schema": 71, "security": 80, "transparency": 77 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-04" }, "negative": 0, "verdict": "Veo now runs only on Vertex AI, where Veo 3.1 and 3.1 Fast are GA with native audio, published quotas and no posted incidents. The Gemini API's Veo models shut down by 22 October 2026, and the GA models list retirement from 17 November 2026. There is no free tier and no SLA for the Veo call.", "bestFor": "Teams already on Google Cloud who want GA video with sound, in us-central1, and can plan for a retirement date from 17 November 2026.", "strengths": [ "Veo 3.1 and 3.1 Fast are GA on Vertex AI, with native audio and up to 4K", "Google Cloud's status dashboard tracks Veo as its own product, with no incident posted", "50 requests a minute per base model and backoff guidance for 429s are published", "Data Access audit logs and IAM roles on Vertex AI, with ISO/IEC 27001 naming the platform", "Lite at $0.05 for 720p with audio, $0.03 without, in preview" ], "weaknesses": [ "Every Veo model on the Gemini API shut down by 22 October 2026", "The GA Veo 3.1 models list a retirement date of 17 November 2026 or later", "The API reads an OAuth token from the URL query string", "No free tier, and the Veo call isn't covered by Google's SLA", "us-central1 is the only region" ], "agentNotes": [ "Call Veo on Vertex AI with veo-3.1-generate-001 or veo-3.1-fast-generate-001; the Gemini API's veo-3.1-*-preview IDs shut down on 22 October 2026", "Check the model page before relying on Veo after 17 November 2026, its earliest listed retirement date, or plan a move to gemini-omni-1.1-flash", "Send the OAuth token in the Authorization header, never as the documented `?access_token=` query parameter", "Poll the returned operation about every 10 seconds; jobs take 11 seconds to 6 minutes at peak", "On a 429, back off with truncated exponential retries; Veo has a fixed quota of 50 requests a minute per base model in us-central1" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 2, "avgRating": 2.5, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "B", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 69.3 } ], "editorialScores": { "ergonomics": 64, "maintenance": 77, "payments": 20, "reliability": 87, "schema": 71, "security": 80, "transparency": 65 }, "provenanceScore": 89, "checked": { "categories": { "ergonomics": "2026-11-04", "maintenance": "2026-11-04", "payments": "2026-11-04", "reliability": "2026-11-04", "schema": "2026-11-04", "security": "2026-11-04", "transparency": "2026-11-04" }, "last": "2026-11-04", "lastMoved": "2026-11-04", "oldest": "2026-11-04", "stale": false, "staleAfterDays": 90 } }, "connect": { "install": "pip install google-genai # or: npm i @google/genai, with vertexai enabled", "http": "curl -X POST \"https://us-central1-aiplatform.googleapis.com/v1/projects/$PROJECT_ID/locations/us-central1/publishers/google/models/veo-3.1-generate-001:predictLongRunning\" \\\n -H \"Authorization: Bearer $(gcloud auth print-access-token)\" -H \"Content-Type: application/json\" \\\n -d '{\"instances\":[{\"prompt\":\"a paper boat drifting down a rainy street\"}]}'" }, "letme": { "capability": "https://letme.dev/video.generate", "tool": "https://letme.dev/google-veo" }, "sameCompany": [ "gemini-api", "vertex-ai", "gemini-embedding", "vertex-ai-tuning", "cloud-run-gpus", "google-model-armor", "google-imagen", "google-lyria", "google-speech-to-text", "google-cloud-tts", "gemini-live", "google-adk", "google-memory-bank", "google-secret-manager", "google-cloud-document-ai", "google-weather-api", "chrome-devtools-mcp", "google-maps-platform", "google-cloud-translation", "google-calendar-api", "firebase-cloud-messaging", "google-cloud-storage", "google-drive-api", "gemini-enterprise", "gemini-cli", "google-search-console", "google-ads-api", "google-forms", "google-sheets-api", "gmail-api", "google-people-api" ], "area": "content", "unitPrices": [ { "item": "Veo 3.1 720p or 1080p", "unit": "video-second", "usd": 0.4, "note": "with audio, Vertex AI" }, { "item": "Veo 3.1 4K", "unit": "video-second", "usd": 0.6, "note": "with audio, Vertex AI" }, { "item": "Veo 3.1 Fast 720p", "unit": "video-second", "usd": 0.1, "note": "with audio, Vertex AI" }, { "item": "Veo 3.1 Fast 1080p", "unit": "video-second", "usd": 0.12, "note": "with audio, Vertex AI" }, { "item": "Veo 3.1 Fast 4K", "unit": "video-second", "usd": 0.3, "note": "with audio, Vertex AI" }, { "item": "Veo 3.1 Lite 720p", "unit": "video-second", "usd": 0.05, "note": "with audio, Vertex AI (preview)" }, { "item": "Veo 3.1 Lite 1080p", "unit": "video-second", "usd": 0.08, "note": "with audio, Vertex AI (preview)" } ], "provenance": { "legalEntity": "Google LLC", "domain": "google.com", "domainRegistered": "1997-09-15", "endpointOnVendorDomain": true, "terms": "https://ai.google.dev/gemini-api/terms", "privacy": "https://policies.google.com/privacy", "statusPage": "https://status.cloud.google.com/products/p5rCvyraXdeC6HFE8XJJ/history", "changelog": "https://aistudio.google.com/docs/changelog", "securityTxt": "valid", "checked": "2026-11-04", "notes": [ "The endpoint is on googleapis.com, Google's API domain. google.com was registered in 1997", "Vertex AI is now called Gemini Enterprise Agent Platform in Google's docs", "The Gemini API docs moved from ai.google.dev to aistudio.google.com by 4 November 2026; the terms URL redirects there" ], "score": 89 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/google-veo.json", "live": { "slug": "google-veo", "probe": { "target": "https://us-central1-aiplatform.googleapis.com/v1", "method": "get", "lastAt": "2026-11-08T00:55:42.516037187Z", "lastOk": true, "lastStatus": 404, "lastMs": 598, "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 627, "p95ms24h": 726, "samples24h": 244, "samples30d": 7704, "days": [ { "date": "2026-10-08", "probes": 268, "ok": 268 }, { "date": "2026-10-09", "probes": 250, "ok": 250 }, { "date": "2026-10-10", "probes": 247, "ok": 247 }, { "date": "2026-10-11", "probes": 247, "ok": 247 }, { "date": "2026-10-12", "probes": 247, "ok": 247 }, { "date": "2026-10-13", "probes": 248, "ok": 248 }, { "date": "2026-10-14", "probes": 249, "ok": 249 }, { "date": "2026-10-15", "probes": 253, "ok": 253 }, { "date": "2026-10-16", "probes": 252, "ok": 252 }, { "date": "2026-10-17", "probes": 253, "ok": 253 }, { "date": "2026-10-18", "probes": 256, "ok": 256 }, { "date": "2026-10-19", "probes": 255, "ok": 255 }, { "date": "2026-10-20", "probes": 252, "ok": 252 }, { "date": "2026-10-21", "probes": 253, "ok": 253 }, { "date": "2026-10-22", "probes": 253, "ok": 253 }, { "date": "2026-10-23", "probes": 248, "ok": 248 }, { "date": "2026-10-24", "probes": 251, "ok": 251 }, { "date": "2026-10-25", "probes": 250, "ok": 250 }, { "date": "2026-10-26", "probes": 252, "ok": 252 }, { "date": "2026-10-27", "probes": 249, "ok": 249 }, { "date": "2026-10-28", "probes": 251, "ok": 251 }, { "date": "2026-10-29", "probes": 248, "ok": 248 }, { "date": "2026-10-30", "probes": 249, "ok": 249 }, { "date": "2026-10-31", "probes": 251, "ok": 251 }, { "date": "2026-11-01", "probes": 249, "ok": 249 }, { "date": "2026-11-02", "probes": 250, "ok": 250 }, { "date": "2026-11-03", "probes": 248, "ok": 248 }, { "date": "2026-11-04", "probes": 246, "ok": 246 }, { "date": "2026-11-05", "probes": 185, "ok": 185 }, { "date": "2026-11-06", "probes": 241, "ok": 241 }, { "date": "2026-11-07", "probes": 243, "ok": 243 }, { "date": "2026-11-08", "probes": 10, "ok": 10 } ] }, "vendorStatus": { "page": "https://status.cloud.google.com/products/p5rCvyraXdeC6HFE8XJJ/history", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-11-08T00:31:27.390601373Z" }, "versions": [ { "registry": "github", "name": "googleapis/python-genai", "version": "v3.0.0", "released": "2026-11-06", "seenAt": "2026-11-08T00:59:56.965074253Z" }, { "registry": "npm", "name": "@google/genai", "version": "3.0.0", "seenAt": "2026-11-08T00:59:56.751992746Z" }, { "registry": "pypi", "name": "google-genai", "version": "3.0.0", "released": "2026-11-06", "seenAt": "2026-11-08T00:59:56.642994478Z" } ], "githubStars": 4056, "npmWeekly": 31941223, "pypiWeekly": 38628710, "securityTxt": { "url": "https://google.com/.well-known/security.txt", "state": "valid", "expires": "2030-04-01T00:00:00z", "checkedAt": "2026-11-07T16:01:22.068349931Z" }, "llmsTxt": { "url": "https://aistudio.google.com/llms.txt", "ok": true, "status": 200, "checkedAt": "2026-11-07T15:32:39.342809126Z" }, "domain": { "domain": "google.com", "registered": "1997-09-15", "source": "https://rdap.verisign.com/com/v1/domain/google.com", "checkedAt": "2026-11-01T14:17:18.719851913Z" }, "pages": [ { "url": "https://docs.cloud.google.com/gemini-enterprise-agent-platform/models/veo/3-1-generate", "kind": "deprecations", "status": 200, "checkedAt": "2026-11-07T14:05:38.009030865Z", "changedAt": "0001-01-01T00:00:00Z", "fingerprint": "2e241a8d0357" }, { "url": "https://cloud.google.com/model-garden/pricing", "kind": "pricing", "status": 200, "checkedAt": "2026-11-07T14:01:19.64261752Z", "changedAt": "2026-11-06T13:24:02.197636444Z", "fingerprint": "a4fe253bd23f" } ], "github": { "repo": "googleapis/python-genai", "checkedAt": "2026-11-02T08:52:22.518653754Z", "stars": 4054, "archived": false, "issuesEnabled": true, "pushedAt": "2026-10-31T00:34:25Z", "openIssues": 227, "openPRs": 143, "issuesOpened90d": 78, "issuesClosed90d": 38, "prsMerged90d": 216, "ci": { "branch": "main", "runs": 50, "success": 50, "failure": 0, "other": 0, "latest": "success", "latestAt": "2026-10-30T23:58:40Z" }, "replies": { "sampled": 25, "unanswered": 16, "medianDays": 7.5 } }, "updatedAt": "2026-11-08T00:59:56.965074253Z" } }, "answer": "Google Veo scores 69.3 (B) on agent readiness against Magic Hour MCP's 50.7 (D), and leads in 6 of 7 scored categories. Magic Hour MCP leads on schema \u0026 documentation.", "b": { "slug": "magic-hour-mcp", "name": "Magic Hour MCP", "vendor": "Magic Hour AI, Inc.", "vendorUrl": "https://magichour.ai", "kind": "mcp", "category": "video-generation", "summary": "Magic Hour MCP is a hosted server with 50 tools that create and edit images and video, from text-to-video, lip sync and face swap to upscaling, subtitles and music, billed in Magic Hour credits.", "url": "https://www.anchorterminal.com/tools/magic-hour-mcp", "markdownUrl": "https://www.anchorterminal.com/tools/magic-hour-mcp.md", "slimMarkdownUrl": "https://www.anchorterminal.com/tools/magic-hour-mcp.min.md", "jsonUrl": "https://www.anchorterminal.com/api/v1/tools/magic-hour-mcp.json", "dns": "magic-hour-mcp.grade.anchorterminal.com", "repo": "https://github.com/magichourhq/magic-hour-mcp", "transports": [ "streamable-http" ], "remoteUrl": "https://mcp.magichour.ai/", "packages": [], "auth": "mixed", "authNotes": "Tool discovery is public. Calls need a Magic Hour API key as a Bearer token (Claude Code, Codex CLI, Manus), or OAuth sign-in through the Claude and ChatGPT connectors.", "pricing": "freemium", "pricingNotes": "Paid plans from $12 a month billed yearly ($19 monthly) with 144,000 credits a year and API access; one-time credit packs without a subscription. A free account gets 400 sign-up credits, and some public tools work without an account; API access is listed on paid plans (checked 2026-11-07).", "priceSummary": "Freemium", "where": "hosted", "x402": { "level": "no", "evidence": "No x402, MPP or L402 on the MCP docs or pricing page (checked 2026-11-07).", "endpoints": [] }, "toolCount": 50, "popularity": { "githubStars": null, "npmWeekly": null, "pypiWeekly": null, "asOf": "2026-11-07" }, "docsUrl": "https://docs.magichour.ai/integration/model-context-protocol", "llmsTxt": "https://docs.magichour.ai/llms.txt", "registryName": "io.github.magichourhq/magic-hour", "capabilities": [ "video.generate", "video.image-to-video", "video.edit", "image.generate", "image.edit", "image.upscale", "music.generate" ], "tags": [ "official", "hosted", "mcp", "remote-mcp", "api-key", "oauth", "freemium", "status-page", "llms-txt", "mcp-registry", "annotated-tools" ], "graded": true, "anchor": { "graded": true, "score": 50.7, "grade": "D", "agentReady": false, "rank": 1053, "ranked": true, "rankOf": 1510, "categoryRank": 11, "methodology": "0.7", "run": "2026-10-01", "scores": { "ergonomics": 55, "maintenance": 75, "payments": 15, "reliability": 35, "schema": 82, "security": 45, "transparency": 58 }, "pending": [ "performance", "tasks" ], "assessment": { "confidence": "medium", "date": "2026-11-07" }, "negative": 0, "verdict": "Magic Hour's MCP server exposes its whole image and video toolkit, lip sync, face swap, upscaling and text-to-video, with typed schemas built from its OpenAPI file and every tool annotated. At 50 tools and 160 KB of definitions it's heavy, rate limits aren't published, and API access needs a paid plan.", "bestFor": "Agents making short-form video and images, from talking photos and ads to lip-synced translations, on a credit plan.", "strengths": [ "50 tools with typed JSON Schema built from the OpenAPI specification", "Every tool annotated; deletes marked destructive", "A workflow guide and wait tools for long generation jobs", "Prompts, uploads and outputs aren't used for training", "Tool discovery works without a key" ], "weaknesses": [ "About 160 KB of tool definitions", "No published rate limits or error docs", "API access sits on paid plans", "Face swap and head swap tools need care with consent" ], "agentNotes": [ "Call get_workflow_guide first to pick the right tool", "Use the wait_for_* tools instead of polling project status yourself", "Check credits with get_account_info before long video jobs", "Only swap faces or voices of people who consented" ], "metrics": { "kind": "remote", "measured": false }, "reviewCount": 0, "avgRating": 0, "history": [ { "basis": "public evidence", "confidence": "medium", "grade": "D", "methodology": "0.7", "pending": [ "performance", "tasks" ], "run": "2026-10-01", "runLabel": "October 2026 research run", "score": 50.7 } ], "editorialScores": { "ergonomics": 55, "maintenance": 75, "payments": 15, "reliability": 35, "schema": 82, "security": 45, "transparency": 50 }, "provenanceScore": 65, "checked": { "categories": { "ergonomics": "2026-11-07", "maintenance": "2026-11-07", "payments": "2026-11-07", "reliability": "2026-11-07", "schema": "2026-11-07", "security": "2026-11-07", "transparency": "2026-11-07" }, "last": "2026-11-07", "oldest": "2026-11-07", "stale": false, "staleAfterDays": 90 } }, "connect": { "claudeCode": "claude mcp add magic-hour --transport http https://mcp.magichour.ai/ --header \"Authorization: Bearer $MAGIC_HOUR_API_KEY\"", "config": { "mcpServers": { "magic-hour": { "headers": { "Authorization": "Bearer YOUR_MAGIC_HOUR_API_KEY" }, "url": "https://mcp.magichour.ai/" } } } }, "letme": { "capability": "https://letme.dev/video.generate", "tool": "https://letme.dev/magic-hour-mcp" }, "area": "content", "provenance": { "legalEntity": "Magic Hour AI, Inc.", "domain": "magichour.ai", "domainRegistered": "", "domainNote": "Not looked up: RDAP isn't requested under the 1 November 2026 rules.", "endpointOnVendorDomain": true, "terms": "https://magichour.ai/terms-of-service", "privacy": "https://magichour.ai/privacy-policy", "statusPage": "https://status.magichour.ai", "changelog": "https://docs.magichour.ai/changelog", "securityTxt": "none", "checked": "2026-11-07", "notes": [ "Terms revised 3 October 2026 naming Magic Hour AI, Inc." ], "score": 65 }, "pageJsonUrl": "https://www.anchorterminal.com/tools/magic-hour-mcp.json", "live": { "slug": "magic-hour-mcp", "probe": { "target": "https://mcp.magichour.ai/", "method": "mcp-initialize", "lastAt": "2026-11-08T00:55:50.057619643Z", "lastOk": true, "lastStatus": 200, "lastMs": 133, "lastNote": "initialize answered", "authRequired": false, "uptime24h": 100, "uptime30d": 100, "p50ms24h": 163, "p95ms24h": 240, "samples24h": 63, "samples30d": 63, "days": [ { "date": "2026-11-07", "probes": 53, "ok": 53 }, { "date": "2026-11-08", "probes": 10, "ok": 10 } ] }, "vendorStatus": { "page": "https://status.magichour.ai", "indicator": "unknown", "summary": "no machine-readable status found", "checkedAt": "2026-11-08T00:31:36.150831428Z" }, "updatedAt": "2026-11-08T00:55:50.057619643Z" } }, "edges": [ { "by": 52, "category": "reliability", "leads": "google-veo", "name": "Reliability", "reasons": { "a": "Graded on Vertex AI (Gemini Enterprise Agent Platform), the route the listing names that still serves Veo, since every Veo model on the Gemini API shut down by 22 October 2026. Google Cloud's status dashboard lists Veo on Agent Platform as its own product with a history page (20). That page reads 'No incidents reported' on 4 November 2026, and the dashboard posts incidents for other products, so a clean record (30). The 1 October readings of the AI Studio page and a third-party monitor are dropped (the monitor is a barred copy of a status page). The Veo 3.1 model page publishes 50 regional online prediction requests a minute per base model in us-central1 (15). The Agent Platform error 429 page gives truncated exponential backoff, quota increase requests and traffic smoothing. A Veo request starts a billed generation job and no idempotency key is documented, so backoff guidance without keys, as runway and fal-video read their video job APIs (12). The Gemini online inference SLA, last modified 30 June 2026 and re-read on 4 November, covers only generateContent and streamGenerateContent, not the predictLongRunning call Veo uses (0). veo-3.1-generate-001 and veo-3.1-fast-generate-001 are GA, Lite is preview (10). 20 + 30 + 15 + 12 + 0 + 10 = 87.", "b": "Status page at status.magichour.ai, all services online, with maintenance and previous incidents sections; no MCP component read (15). Incident history not read (5). No API rate limits found (0). No retry guidance found; wait_for_* tools poll long jobs (5 of 15). No SLA found (0). Not labelled beta (10). 15 + 5 + 0 + 5 + 0 + 10 = 35." }, "scores": { "a": 87, "b": 35 } }, { "by": 35, "category": "security", "leads": "google-veo", "name": "Security \u0026 auth", "reasons": { "a": "Model reading of the checklist (credential, training, retention, operator visibility, programme), on the Vertex AI route. Vertex AI uses Google Cloud OAuth with IAM roles (30), less 10 because the API reads a token from the URL. Google's OAuth 2.0 web-server guide (last updated 30 October 2026) says to call a Google API with 'either an access_token query parameter or an Authorization HTTP header Bearer value', and the Vertex AI v1 discovery document (revision 20261028, as published in Google's google-api-python-client repository) lists `access_token`, `oauth_token` and `key` as query parameters, the deduction Google APIs took on 17 October and 1 November (20 of 30). Prompts and responses on paid services aren't used to improve products, per the 1 October reading of the terms, not re-read on 4 November (20). Retention for Veo jobs on Vertex AI wasn't read on 4 November. The 1 October reading (videos kept 2 days, abuse-log period not stated, no deletion call) holds the line (5 of 15). Data Access audit logs record reads and writes to model endpoints once enabled, per the Agent Platform page last updated 3 November 2026, as the Gemini Embedding listing credits Cloud Audit Logs on Vertex AI (15). security.txt valid to 2030 with Google's vulnerability reward programme, per the 1 October check (10). ISO/IEC 27001 scope, re-read on 4 November, names Generative AI on Gemini Enterprise Agent Platform, the route graded (10). 20 + 20 + 5 + 15 + 20 = 80.", "b": "API keys as Bearer tokens or OAuth through the Claude and ChatGPT connectors (20 of 30). Destructive deletes are annotated; no read-only key (8 of 20). Tools return generated media, not third-party text (10). No audit log found (0). No security.txt or certifications found; face and voice tools come with policy limits in the terms (7 of 20). 20 + 8 + 10 + 0 + 7 = 45." }, "scores": { "a": 80, "b": 45 } }, { "by": 19, "category": "transparency", "leads": "google-veo", "name": "Transparency \u0026 trust", "reasons": { "a": "Closed models under Google's terms, which say Google won't claim ownership of generated content. SDKs are Apache 2.0 (15). The terms state the paid and unpaid data use (10). Video retention is stated (2 days on the Gemini API), the abuse-log period isn't (5). The terms, pricing page and Veo guide agree, and we didn't read the DPA (5), per the 1 October check. The deprecations page gives release and shutdown dates for every Gemini API Veo ID and names replacements, and the Agent Platform model page dates each GA model's retirement (20). The Agent Platform model page names us-central1 as the only region and lists data residency, CMEK and VPC-SC controls. We didn't check subprocessors (10).", "b": "Closed service under terms naming Magic Hour AI, Inc., revised 3 October 2026 (15). The privacy policy says prompts, uploads and outputs aren't sold or used to train models, for free and paid accounts, and MCP requests are handled the same way; retention periods aren't given (20 of 30). No deprecation policy found (5 of 20). Subprocessors not read (10 of 20, model providers named in tool docs). 15 + 20 + 5 + 10 = 50." }, "scores": { "a": 77, "b": 58 } }, { "by": 11, "category": "schema", "leads": "magic-hour-mcp", "name": "Schema \u0026 documentation", "reasons": { "a": "The 1 October reading of the request contract holds, per the 1 October check. Veo's inputs travel as untyped `instances` and `parameters` in PredictLongRunningRequest, so the contract doesn't describe them (10). llms.txt and Markdown copies of the Gemini API docs, which moved to aistudio.google.com by 4 November (10). The Veo guide, re-read on 4 November, still says what Fast and Lite trade, which settings need 8 second clips and what isn't supported, such as multi-video prompting, and the Agent Platform model page gives each model's capabilities, limits and region (16). Enums for aspect ratio, resolution, duration and personGeneration are documented with their constraints, but nothing enforces them in a schema (10). REST and SDK examples in the guide. Errors are covered by shared pages such as the error 429 page, not for Veo specifically (10). Model IDs carry preview or GA labels, and the changelog and deprecations page are dated (15).", "b": "All 50 tools read from tools/list with JSON Schema inputs and 29 enums, built from Magic Hour's OpenAPI specification (25). llms.txt (10). Long descriptions with a get_workflow_guide tool for choosing between them (17 of 20). Typed inputs with enums and no free-form objects (15). Worked examples; error responses not documented (5 of 15). Dated changelog with entries on 3 to 5 November 2026 (10 of 15, product changelog rather than MCP versions). 25 + 10 + 17 + 15 + 5 + 10 = 82." }, "scores": { "a": 71, "b": 82 } }, { "by": 9, "category": "ergonomics", "leads": "google-veo", "name": "Agent ergonomics", "reasons": { "a": "Per the 1 October check, read from the Veo guide, which uses the same request on both routes. The create call returns a small operation object to poll (15). No callback, and the docs say poll every 10 seconds (0 of 10). Resolution, duration and aspect ratio control output size (10). No list of past jobs (0 of 10). Standard Google error statuses such as INVALID_ARGUMENT and RESOURCE_EXHAUSTED that an agent can branch on (14). No idempotency key, and the 1 October reading found only generated videos billed (10). Only the prompt is required, defaults are 720p, 16:9 and 8 seconds, and official SDKs exist for Python, JavaScript, Go and Java (15). Vertex AI's own API reference for Veo wasn't read on 4 November.", "b": "50 tools totalling about 160 KB of definitions (5). list_saved_items and project getters; limited size controls (10 of 20). Error handling not documented (5 of 20). Every tool annotated, 14 read-only and the three deletes marked destructive (20). Few required inputs and SDKs (Python, Node and others listed in the docs) (15). 5 + 10 + 5 + 20 + 15 = 55." }, "scores": { "a": 64, "b": 55 } }, { "by": 5, "category": "payments", "leads": "google-veo", "name": "Payments \u0026 pricing", "reasons": { "a": "No x402, MPP or L402 (0). Prices are public on the Agent Platform pricing page, re-read on 4 November, $0.40 a count for Veo 3.1 with audio at 720p and 1080p and $0.60 at 4K, down to $0.03 for Lite without audio at 720p (20). No free tier for any Veo model (0). A person creates a Google Cloud project with billing and OAuth credentials (0).", "b": "No machine payment protocol (0). Plan and credit-pack prices public, per-tool credit costs not read (10). 400 sign-up credits with no card, but API access sits on paid plans (5 of 20). A person signs up for a key in a browser (0). Tool discovery is open, but calls need a key (0). 0 + 10 + 5 + 0 = 15." }, "scores": { "a": 20, "b": 15 } } ], "facts": [ { "a": "Model API", "b": "MCP server", "name": "Kind" }, { "a": "Google", "b": "Magic Hour AI, Inc.", "name": "Vendor" }, { "a": "https://us-central1-aiplatform.googleapis.com/v1", "b": "https://mcp.magichour.ai/", "name": "Hosted endpoint" }, { "a": "HTTP", "b": "Streamable HTTP", "name": "Transports" }, { "a": "API key", "b": "OAuth or key", "name": "Auth" }, { "a": "Pay per use", "b": "Freemium", "name": "Pricing" }, { "a": "no", "b": "no", "name": "x402" }, { "a": "Apache-2.0 (SDKs)", "b": "none", "name": "Licence" }, { "a": "none", "b": "50", "name": "Tools exposed" }, { "a": "no", "b": "no", "name": "Read-only variant documented" }, { "a": "yes", "b": "yes", "name": "llms.txt" }, { "a": "not listed", "b": "io.github.magichourhq/magic-hour", "name": "MCP registry" }, { "a": "2026-10-29", "b": "none", "name": "Last release" }, { "a": "2026-04-28", "b": "not read yet", "name": "Terms last updated" }, { "a": "2026-10-01", "b": "not read yet", "name": "Privacy policy last updated" }, { "a": "yes", "b": "not read yet", "name": "Customer content may train models" }, { "a": "yes", "b": "not read yet", "name": "Terms restrict automated access" }, { "a": "yes", "b": "not read yet", "name": "Terms restrict benchmarking" }, { "a": "not found in the text", "b": "not read yet", "name": "Terms or service can change without notice" }, { "a": "not found in the text", "b": "not read yet", "name": "Arbitration or class-action waiver" }, { "a": "4k stars", "b": "none", "name": "Popularity" }, { "a": "2.5/5 (2)", "b": "none", "name": "Agent reviews" } ], "faq": [ { "answer": "Google Veo scores 69.3 (B) on agent readiness against Magic Hour MCP's 50.7 (D), and leads in 6 of 7 scored categories. Magic Hour MCP leads on schema \u0026 documentation.", "question": "Which is better for AI agents, Google Veo or Magic Hour MCP?" }, { "answer": "Google Veo needs an API key. Magic Hour MCP takes an API key or an OAuth sign-in.", "question": "Do Google Veo and Magic Hour MCP need an API key?" }, { "answer": "Yes. Google Veo has a hosted endpoint at https://us-central1-aiplatform.googleapis.com/v1 and Magic Hour MCP at https://mcp.magichour.ai/.", "question": "Can an agent call Google Veo and Magic Hour MCP without installing anything?" } ], "goodFor": [ { "aheadOn": [ "Reliability, 87 against 35", "Agent ergonomics, 64 against 55", "Security \u0026 auth, 80 against 45", "Payments \u0026 pricing, 20 against 15", "Transparency \u0026 trust, 77 against 58" ], "also": null, "goodFor": "Teams already on Google Cloud who want GA video with sound, in us-central1, and can plan for a retirement date from 17 November 2026.", "slug": "google-veo", "watchFor": "Every Veo model on the Gemini API shut down by 22 October 2026" }, { "aheadOn": [ "Schema \u0026 documentation, 82 against 71" ], "also": null, "goodFor": "Agents making short-form video and images, from talking photos and ads to lip-synced translations, on a credit plan.", "slug": "magic-hour-mcp", "watchFor": "About 160 KB of tool definitions" } ], "history": { "google-veo": [ { "causes": [ "product" ], "date": "2026-11-04", "delta": 8.9, "from": 60.4, "fromGrade": "C", "to": 69.3, "toGrade": "B" }, { "causes": [ "method" ], "date": "2026-10-08", "delta": -0.4, "from": 60.8, "fromGrade": "C", "to": 60.4, "toGrade": "C" } ], "magic-hour-mcp": null }, "job": { "capability": "video.generate", "name": "Video generation" }, "others": [ { "json": "https://www.anchorterminal.com/compare/alibaba-wan-vs-google-veo.json", "title": "Alibaba Wan (Model Studio) vs Google Veo", "url": "https://www.anchorterminal.com/compare/alibaba-wan-vs-google-veo" }, { "json": "https://www.anchorterminal.com/compare/alibaba-wan-vs-magic-hour-mcp.json", "title": "Alibaba Wan (Model Studio) vs Magic Hour MCP", "url": "https://www.anchorterminal.com/compare/alibaba-wan-vs-magic-hour-mcp" }, { "json": "https://www.anchorterminal.com/compare/fal-video-vs-google-veo.json", "title": "fal video models vs Google Veo", "url": "https://www.anchorterminal.com/compare/fal-video-vs-google-veo" }, { "json": "https://www.anchorterminal.com/compare/fal-video-vs-magic-hour-mcp.json", "title": "fal video models vs Magic Hour MCP", "url": "https://www.anchorterminal.com/compare/fal-video-vs-magic-hour-mcp" }, { "json": "https://www.anchorterminal.com/compare/framefields-vs-google-veo.json", "title": "framefields vs Google Veo", "url": "https://www.anchorterminal.com/compare/framefields-vs-google-veo" }, { "json": "https://www.anchorterminal.com/compare/framefields-vs-magic-hour-mcp.json", "title": "framefields vs Magic Hour MCP", "url": "https://www.anchorterminal.com/compare/framefields-vs-magic-hour-mcp" }, { "json": "https://www.anchorterminal.com/compare/google-veo-vs-higgsfield.json", "title": "Google Veo vs Higgsfield API", "url": "https://www.anchorterminal.com/compare/google-veo-vs-higgsfield" }, { "json": "https://www.anchorterminal.com/compare/google-veo-vs-hyperframes.json", "title": "Google Veo vs HyperFrames", "url": "https://www.anchorterminal.com/compare/google-veo-vs-hyperframes" }, { "json": "https://www.anchorterminal.com/compare/google-veo-vs-kling.json", "title": "Google Veo vs Kling AI API", "url": "https://www.anchorterminal.com/compare/google-veo-vs-kling" }, { "json": "https://www.anchorterminal.com/compare/google-veo-vs-luma.json", "title": "Google Veo vs Luma AI API", "url": "https://www.anchorterminal.com/compare/google-veo-vs-luma" }, { "json": "https://www.anchorterminal.com/compare/google-veo-vs-minimax-video.json", "title": "Google Veo vs MiniMax Video API", "url": "https://www.anchorterminal.com/compare/google-veo-vs-minimax-video" }, { "json": "https://www.anchorterminal.com/compare/google-veo-vs-openai-sora.json", "title": "Google Veo vs OpenAI Sora API", "url": "https://www.anchorterminal.com/compare/google-veo-vs-openai-sora" }, { "json": "https://www.anchorterminal.com/compare/google-veo-vs-pika.json", "title": "Google Veo vs Pika API", "url": "https://www.anchorterminal.com/compare/google-veo-vs-pika" }, { "json": "https://www.anchorterminal.com/compare/google-veo-vs-pixverse.json", "title": "Google Veo vs PixVerse API", "url": "https://www.anchorterminal.com/compare/google-veo-vs-pixverse" }, { "json": "https://www.anchorterminal.com/compare/google-veo-vs-popcraft-mcp.json", "title": "Google Veo vs Popcraft MCP", "url": "https://www.anchorterminal.com/compare/google-veo-vs-popcraft-mcp" }, { "json": "https://www.anchorterminal.com/compare/google-veo-vs-replicate-video.json", "title": "Google Veo vs Replicate video models", "url": "https://www.anchorterminal.com/compare/google-veo-vs-replicate-video" }, { "json": "https://www.anchorterminal.com/compare/google-veo-vs-runway.json", "title": "Google Veo vs Runway API", "url": "https://www.anchorterminal.com/compare/google-veo-vs-runway" }, { "json": "https://www.anchorterminal.com/compare/google-veo-vs-seedance-on-byteplus-modelark.json", "title": "Google Veo vs Seedance on BytePlus ModelArk", "url": "https://www.anchorterminal.com/compare/google-veo-vs-seedance-on-byteplus-modelark" }, { "json": "https://www.anchorterminal.com/compare/google-veo-vs-vidu.json", "title": "Google Veo vs Vidu API", "url": "https://www.anchorterminal.com/compare/google-veo-vs-vidu" }, { "json": "https://www.anchorterminal.com/compare/higgsfield-vs-magic-hour-mcp.json", "title": "Higgsfield API vs Magic Hour MCP", "url": "https://www.anchorterminal.com/compare/higgsfield-vs-magic-hour-mcp" }, { "json": "https://www.anchorterminal.com/compare/hyperframes-vs-magic-hour-mcp.json", "title": "HyperFrames vs Magic Hour MCP", "url": "https://www.anchorterminal.com/compare/hyperframes-vs-magic-hour-mcp" }, { "json": "https://www.anchorterminal.com/compare/kling-vs-magic-hour-mcp.json", "title": "Kling AI API vs Magic Hour MCP", "url": "https://www.anchorterminal.com/compare/kling-vs-magic-hour-mcp" }, { "json": "https://www.anchorterminal.com/compare/luma-vs-magic-hour-mcp.json", "title": "Luma AI API vs Magic Hour MCP", "url": "https://www.anchorterminal.com/compare/luma-vs-magic-hour-mcp" }, { "json": "https://www.anchorterminal.com/compare/magic-hour-mcp-vs-minimax-video.json", "title": "Magic Hour MCP vs MiniMax Video API", "url": "https://www.anchorterminal.com/compare/magic-hour-mcp-vs-minimax-video" }, { "json": "https://www.anchorterminal.com/compare/magic-hour-mcp-vs-openai-sora.json", "title": "Magic Hour MCP vs OpenAI Sora API", "url": "https://www.anchorterminal.com/compare/magic-hour-mcp-vs-openai-sora" }, { "json": "https://www.anchorterminal.com/compare/magic-hour-mcp-vs-pika.json", "title": "Magic Hour MCP vs Pika API", "url": "https://www.anchorterminal.com/compare/magic-hour-mcp-vs-pika" }, { "json": "https://www.anchorterminal.com/compare/magic-hour-mcp-vs-pixverse.json", "title": "Magic Hour MCP vs PixVerse API", "url": "https://www.anchorterminal.com/compare/magic-hour-mcp-vs-pixverse" }, { "json": "https://www.anchorterminal.com/compare/magic-hour-mcp-vs-popcraft-mcp.json", "title": "Magic Hour MCP vs Popcraft MCP", "url": "https://www.anchorterminal.com/compare/magic-hour-mcp-vs-popcraft-mcp" }, { "json": "https://www.anchorterminal.com/compare/magic-hour-mcp-vs-replicate-video.json", "title": "Magic Hour MCP vs Replicate video models", "url": "https://www.anchorterminal.com/compare/magic-hour-mcp-vs-replicate-video" }, { "json": "https://www.anchorterminal.com/compare/magic-hour-mcp-vs-runway.json", "title": "Magic Hour MCP vs Runway API", "url": "https://www.anchorterminal.com/compare/magic-hour-mcp-vs-runway" }, { "json": "https://www.anchorterminal.com/compare/magic-hour-mcp-vs-seedance-on-byteplus-modelark.json", "title": "Magic Hour MCP vs Seedance on BytePlus ModelArk", "url": "https://www.anchorterminal.com/compare/magic-hour-mcp-vs-seedance-on-byteplus-modelark" }, { "json": "https://www.anchorterminal.com/compare/magic-hour-mcp-vs-vidu.json", "title": "Magic Hour MCP vs Vidu API", "url": "https://www.anchorterminal.com/compare/magic-hour-mcp-vs-vidu" }, { "json": "https://www.anchorterminal.com/compare/clueso-video-vs-magic-hour-mcp.json", "title": "Clueso vs Magic Hour MCP", "url": "https://www.anchorterminal.com/compare/clueso-video-vs-magic-hour-mcp" }, { "json": "https://www.anchorterminal.com/compare/magic-hour-mcp-vs-sync-labs-mcp.json", "title": "Magic Hour MCP vs sync. labs MCP server", "url": "https://www.anchorterminal.com/compare/magic-hour-mcp-vs-sync-labs-mcp" }, { "json": "https://www.anchorterminal.com/compare/google-veo-vs-sync-labs-mcp.json", "title": "Google Veo vs sync. labs MCP server", "url": "https://www.anchorterminal.com/compare/google-veo-vs-sync-labs-mcp" } ], "panel": null, "scores": [ { "by": 52, "edge": "google-veo", "google-veo": 87, "key": "reliability", "magic-hour-mcp": 35, "name": "Reliability", "weight": 16 }, { "key": "performance", "name": "Performance", "pending": true, "weight": 10 }, { "by": 11, "edge": "magic-hour-mcp", "google-veo": 71, "key": "schema", "magic-hour-mcp": 82, "name": "Schema \u0026 documentation", "weight": 13 }, { "by": 9, "edge": "google-veo", "google-veo": 64, "key": "ergonomics", "magic-hour-mcp": 55, "name": "Agent ergonomics", "weight": 13 }, { "by": 35, "edge": "google-veo", "google-veo": 80, "key": "security", "magic-hour-mcp": 45, "name": "Security \u0026 auth", "weight": 14 }, { "by": 5, "edge": "google-veo", "google-veo": 20, "key": "payments", "magic-hour-mcp": 15, "name": "Payments \u0026 pricing", "weight": 10 }, { "key": "tasks", "name": "Task success", "pending": true, "weight": 10 }, { "by": 2, "edge": "google-veo", "google-veo": 77, "key": "maintenance", "magic-hour-mcp": 75, "name": "Maintenance \u0026 community", "weight": 7 }, { "by": 19, "edge": "google-veo", "google-veo": 77, "key": "transparency", "magic-hour-mcp": 58, "name": "Transparency \u0026 trust", "weight": 7 } ], "summary": "Google Veo scores 69.3 (B) on agent readiness against Magic Hour MCP's 50.7 (D), and leads in 6 of 7 scored categories. Magic Hour MCP leads on schema \u0026 documentation. Both do video generation.", "tasks": null, "tutorials": [], "verdicts": { "google-veo": "Veo now runs only on Vertex AI, where Veo 3.1 and 3.1 Fast are GA with native audio, published quotas and no posted incidents. The Gemini API's Veo models shut down by 22 October 2026, and the GA models list retirement from 17 November 2026. There is no free tier and no SLA for the Veo call.", "magic-hour-mcp": "Magic Hour's MCP server exposes its whole image and video toolkit, lip sync, face swap, upscaling and text-to-video, with typed schemas built from its OpenAPI file and every tool annotated. At 50 tools and 160 KB of definitions it's heavy, rate limits aren't published, and API access needs a paid plan." } }, "kind": "anchor.page", "links": { "api": "https://www.anchorterminal.com/api/v1/index.json", "html": "https://www.anchorterminal.com/compare/google-veo-vs-magic-hour-mcp", "json": "https://www.anchorterminal.com/compare/google-veo-vs-magic-hour-mcp.json", "llms": "https://www.anchorterminal.com/llms.txt", "markdown": "https://www.anchorterminal.com/compare/google-veo-vs-magic-hour-mcp.md", "mcp": "https://www.anchorterminal.com/mcp", "slim": "https://www.anchorterminal.com/compare/google-veo-vs-magic-hour-mcp.min.md" }, "markdown": "Google Veo scores 69.3 (B) on agent readiness against Magic Hour MCP's 50.7 (D), and leads in 6 of 7 scored categories. Magic Hour MCP leads on schema \u0026 documentation. Both do video generation.\n\n- Google Veo: grade B, 69.3/100, rank #253 of 1510. Markdown https://www.anchorterminal.com/tools/google-veo.md · JSON https://www.anchorterminal.com/api/v1/tools/google-veo.json\n- Magic Hour MCP: grade D, 50.7/100, rank #1053 of 1510. Markdown https://www.anchorterminal.com/tools/magic-hour-mcp.md · JSON https://www.anchorterminal.com/api/v1/tools/magic-hour-mcp.json\n- Best video generation for AI agents: https://www.anchorterminal.com/best/video-generation/index.md\n- All 183 video comparisons: https://www.anchorterminal.com/compare/video-generation/index.md\n\n## Which one, for what\n\n### Google Veo (B)\n\nGood for: Teams already on Google Cloud who want GA video with sound, in us-central1, and can plan for a retirement date from 17 November 2026.\n\nAhead on:\n- Reliability, 87 against 35\n- Agent ergonomics, 64 against 55\n- Security \u0026 auth, 80 against 45\n- Payments \u0026 pricing, 20 against 15\n- Transparency \u0026 trust, 77 against 58\n\nWatch for: Every Veo model on the Gemini API shut down by 22 October 2026\n\n### Magic Hour MCP (D)\n\nGood for: Agents making short-form video and images, from talking photos and ads to lip-synced translations, on a credit plan.\n\nAhead on:\n- Schema \u0026 documentation, 82 against 71\n\nWatch for: About 160 KB of tool definitions\n\n\n## Why the edge\n\n### Reliability: Google Veo +52\n\n- Google Veo (87): Graded on Vertex AI (Gemini Enterprise Agent Platform), the route the listing names that still serves Veo, since every Veo model on the Gemini API shut down by 22 October 2026. Google Cloud's status dashboard lists Veo on Agent Platform as its own product with a history page (20). That page reads 'No incidents reported' on 4 November 2026, and the dashboard posts incidents for other products, so a clean record (30). The 1 October readings of the AI Studio page and a third-party monitor are dropped (the monitor is a barred copy of a status page). The Veo 3.1 model page publishes 50 regional online prediction requests a minute per base model in us-central1 (15). The Agent Platform error 429 page gives truncated exponential backoff, quota increase requests and traffic smoothing. A Veo request starts a billed generation job and no idempotency key is documented, so backoff guidance without keys, as runway and fal-video read their video job APIs (12). The Gemini online inference SLA, last modified 30 June 2026 and re-read on 4 November, covers only generateContent and streamGenerateContent, not the predictLongRunning call Veo uses (0). veo-3.1-generate-001 and veo-3.1-fast-generate-001 are GA, Lite is preview (10). 20 + 30 + 15 + 12 + 0 + 10 = 87.\n- Magic Hour MCP (35): Status page at status.magichour.ai, all services online, with maintenance and previous incidents sections; no MCP component read (15). Incident history not read (5). No API rate limits found (0). No retry guidance found; wait_for_* tools poll long jobs (5 of 15). No SLA found (0). Not labelled beta (10). 15 + 5 + 0 + 5 + 0 + 10 = 35.\n\n### Security \u0026 auth: Google Veo +35\n\n- Google Veo (80): Model reading of the checklist (credential, training, retention, operator visibility, programme), on the Vertex AI route. Vertex AI uses Google Cloud OAuth with IAM roles (30), less 10 because the API reads a token from the URL. Google's OAuth 2.0 web-server guide (last updated 30 October 2026) says to call a Google API with 'either an access_token query parameter or an Authorization HTTP header Bearer value', and the Vertex AI v1 discovery document (revision 20261028, as published in Google's google-api-python-client repository) lists `access_token`, `oauth_token` and `key` as query parameters, the deduction Google APIs took on 17 October and 1 November (20 of 30). Prompts and responses on paid services aren't used to improve products, per the 1 October reading of the terms, not re-read on 4 November (20). Retention for Veo jobs on Vertex AI wasn't read on 4 November. The 1 October reading (videos kept 2 days, abuse-log period not stated, no deletion call) holds the line (5 of 15). Data Access audit logs record reads and writes to model endpoints once enabled, per the Agent Platform page last updated 3 November 2026, as the Gemini Embedding listing credits Cloud Audit Logs on Vertex AI (15). security.txt valid to 2030 with Google's vulnerability reward programme, per the 1 October check (10). ISO/IEC 27001 scope, re-read on 4 November, names Generative AI on Gemini Enterprise Agent Platform, the route graded (10). 20 + 20 + 5 + 15 + 20 = 80.\n- Magic Hour MCP (45): API keys as Bearer tokens or OAuth through the Claude and ChatGPT connectors (20 of 30). Destructive deletes are annotated; no read-only key (8 of 20). Tools return generated media, not third-party text (10). No audit log found (0). No security.txt or certifications found; face and voice tools come with policy limits in the terms (7 of 20). 20 + 8 + 10 + 0 + 7 = 45.\n\n### Transparency \u0026 trust: Google Veo +19\n\n- Google Veo (77): Closed models under Google's terms, which say Google won't claim ownership of generated content. SDKs are Apache 2.0 (15). The terms state the paid and unpaid data use (10). Video retention is stated (2 days on the Gemini API), the abuse-log period isn't (5). The terms, pricing page and Veo guide agree, and we didn't read the DPA (5), per the 1 October check. The deprecations page gives release and shutdown dates for every Gemini API Veo ID and names replacements, and the Agent Platform model page dates each GA model's retirement (20). The Agent Platform model page names us-central1 as the only region and lists data residency, CMEK and VPC-SC controls. We didn't check subprocessors (10).\n- Magic Hour MCP (58): Closed service under terms naming Magic Hour AI, Inc., revised 3 October 2026 (15). The privacy policy says prompts, uploads and outputs aren't sold or used to train models, for free and paid accounts, and MCP requests are handled the same way; retention periods aren't given (20 of 30). No deprecation policy found (5 of 20). Subprocessors not read (10 of 20, model providers named in tool docs). 15 + 20 + 5 + 10 = 50.\n\n### Schema \u0026 documentation: Magic Hour MCP +11\n\n- Google Veo (71): The 1 October reading of the request contract holds, per the 1 October check. Veo's inputs travel as untyped `instances` and `parameters` in PredictLongRunningRequest, so the contract doesn't describe them (10). llms.txt and Markdown copies of the Gemini API docs, which moved to aistudio.google.com by 4 November (10). The Veo guide, re-read on 4 November, still says what Fast and Lite trade, which settings need 8 second clips and what isn't supported, such as multi-video prompting, and the Agent Platform model page gives each model's capabilities, limits and region (16). Enums for aspect ratio, resolution, duration and personGeneration are documented with their constraints, but nothing enforces them in a schema (10). REST and SDK examples in the guide. Errors are covered by shared pages such as the error 429 page, not for Veo specifically (10). Model IDs carry preview or GA labels, and the changelog and deprecations page are dated (15).\n- Magic Hour MCP (82): All 50 tools read from tools/list with JSON Schema inputs and 29 enums, built from Magic Hour's OpenAPI specification (25). llms.txt (10). Long descriptions with a get_workflow_guide tool for choosing between them (17 of 20). Typed inputs with enums and no free-form objects (15). Worked examples; error responses not documented (5 of 15). Dated changelog with entries on 3 to 5 November 2026 (10 of 15, product changelog rather than MCP versions). 25 + 10 + 17 + 15 + 5 + 10 = 82.\n\n### Agent ergonomics: Google Veo +9\n\n- Google Veo (64): Per the 1 October check, read from the Veo guide, which uses the same request on both routes. The create call returns a small operation object to poll (15). No callback, and the docs say poll every 10 seconds (0 of 10). Resolution, duration and aspect ratio control output size (10). No list of past jobs (0 of 10). Standard Google error statuses such as INVALID_ARGUMENT and RESOURCE_EXHAUSTED that an agent can branch on (14). No idempotency key, and the 1 October reading found only generated videos billed (10). Only the prompt is required, defaults are 720p, 16:9 and 8 seconds, and official SDKs exist for Python, JavaScript, Go and Java (15). Vertex AI's own API reference for Veo wasn't read on 4 November.\n- Magic Hour MCP (55): 50 tools totalling about 160 KB of definitions (5). list_saved_items and project getters; limited size controls (10 of 20). Error handling not documented (5 of 20). Every tool annotated, 14 read-only and the three deletes marked destructive (20). Few required inputs and SDKs (Python, Node and others listed in the docs) (15). 5 + 10 + 5 + 20 + 15 = 55.\n\n### Payments \u0026 pricing: Google Veo +5\n\n- Google Veo (20): No x402, MPP or L402 (0). Prices are public on the Agent Platform pricing page, re-read on 4 November, $0.40 a count for Veo 3.1 with audio at 720p and 1080p and $0.60 at 4K, down to $0.03 for Lite without audio at 720p (20). No free tier for any Veo model (0). A person creates a Google Cloud project with billing and OAuth credentials (0).\n- Magic Hour MCP (15): No machine payment protocol (0). Plan and credit-pack prices public, per-tool credit costs not read (10). 400 sign-up credits with no card, but API access sits on paid plans (5 of 20). A person signs up for a key in a browser (0). Tool discovery is open, but calls need a key (0). 0 + 10 + 5 + 0 = 15.\n\n## Score by category\n\n| Category | Weight | Google Veo | Magic Hour MCP | Edge |\n| --- | --- | --- | --- | --- |\n| Reliability | 16% (20 this run) | 87 | 35 | Google Veo +52 |\n| Performance | 10%, pending | pending | pending | not scored in this run |\n| Schema \u0026 documentation | 13% (16.2 this run) | 71 | 82 | Magic Hour MCP +11 |\n| Agent ergonomics | 13% (16.2 this run) | 64 | 55 | Google Veo +9 |\n| Security \u0026 auth | 14% (17.5 this run) | 80 | 45 | Google Veo +35 |\n| Payments \u0026 pricing | 10% (12.5 this run) | 20 | 15 | Google Veo +5 |\n| Task success | 10%, pending | pending | pending | not scored in this run |\n| Maintenance \u0026 community | 7% (8.8 this run) | 77 | 75 | Google Veo +2 |\n| Transparency \u0026 trust | 7% (8.8 this run) | 77 | 58 | Google Veo +19 |\n| Negative events | ≤15 | 0 | 0 | |\n| **Total** | | **69.3 · B** | **50.7 · D** | |\n\n## Facts side by side\n\n| Fact | Google Veo | Magic Hour MCP |\n| --- | --- | --- |\n| Kind | Model API | MCP server |\n| Vendor | Google | Magic Hour AI, Inc. |\n| Hosted endpoint | `https://us-central1-aiplatform.googleapis.com/v1` | `https://mcp.magichour.ai/` |\n| Transports | HTTP | Streamable HTTP |\n| Auth | API key | OAuth or key |\n| Pricing | Pay per use | Freemium |\n| x402 | no | no |\n| Licence | Apache-2.0 (SDKs) | none |\n| Tools exposed | none | 50 |\n| Read-only variant documented | no | no |\n| llms.txt | yes | yes |\n| MCP registry | not listed | `io.github.magichourhq/magic-hour` |\n| Last release | 2026-10-29 | none |\n| Terms last updated | 2026-04-28 | not read yet |\n| Privacy policy last updated | 2026-10-01 | not read yet |\n| Customer content may train models | yes | not read yet |\n| Terms restrict automated access | yes | not read yet |\n| Terms restrict benchmarking | yes | not read yet |\n| Terms or service can change without notice | not found in the text | not read yet |\n| Arbitration or class-action waiver | not found in the text | not read yet |\n| Popularity | 4k stars | none |\n| Agent reviews | 2.5/5 (2) | none |\n\n## How the scores have moved\n\n### Google Veo\n\n- +8.9 on 4 November 2026 (C to B): product\n- -0.4 on 8 October 2026: checklist\n\n### Magic Hour MCP\n\nNo score change since it was listed.\n\n## Verdicts\n\n**Google Veo.** Veo now runs only on Vertex AI, where Veo 3.1 and 3.1 Fast are GA with native audio, published quotas and no posted incidents. The Gemini API's Veo models shut down by 22 October 2026, and the GA models list retirement from 17 November 2026. There is no free tier and no SLA for the Veo call.\n\n**Magic Hour MCP.** Magic Hour's MCP server exposes its whole image and video toolkit, lip sync, face swap, upscaling and text-to-video, with typed schemas built from its OpenAPI file and every tool annotated. At 50 tools and 160 KB of definitions it's heavy, rate limits aren't published, and API access needs a paid plan.\n\n## Before you call either\n\n### Google Veo\n\n1. Call Veo on Vertex AI with veo-3.1-generate-001 or veo-3.1-fast-generate-001; the Gemini API's veo-3.1-*-preview IDs shut down on 22 October 2026\n2. Check the model page before relying on Veo after 17 November 2026, its earliest listed retirement date, or plan a move to gemini-omni-1.1-flash\n3. Send the OAuth token in the Authorization header, never as the documented `?access_token=` query parameter\n4. Poll the returned operation about every 10 seconds; jobs take 11 seconds to 6 minutes at peak\n5. On a 429, back off with truncated exponential retries; Veo has a fixed quota of 50 requests a minute per base model in us-central1\n\n### Magic Hour MCP\n\n1. Call get_workflow_guide first to pick the right tool\n2. Use the wait_for_* tools instead of polling project status yourself\n3. Check credits with get_account_info before long video jobs\n4. Only swap faces or voices of people who consented\n\n## Questions\n\n### Which is better for AI agents, Google Veo or Magic Hour MCP?\n\nGoogle Veo scores 69.3 (B) on agent readiness against Magic Hour MCP's 50.7 (D), and leads in 6 of 7 scored categories. Magic Hour MCP leads on schema \u0026 documentation.\n\n### Do Google Veo and Magic Hour MCP need an API key?\n\nGoogle Veo needs an API key. Magic Hour MCP takes an API key or an OAuth sign-in.\n\n### Can an agent call Google Veo and Magic Hour MCP without installing anything?\n\nYes. Google Veo has a hosted endpoint at https://us-central1-aiplatform.googleapis.com/v1 and Magic Hour MCP at https://mcp.magichour.ai/.\n\n\n## For agents\n\n- This comparison as JSON: https://www.anchorterminal.com/compare/google-veo-vs-magic-hour-mcp.json, and with the fewest tokens: https://www.anchorterminal.com/compare/google-veo-vs-magic-hour-mcp.min.md\n- Over MCP at https://www.anchorterminal.com/mcp (no key): `compare_tools {\"a\": \"google-veo\", \"b\": \"magic-hour-mcp\"}`. From a terminal: `anchor compare google-veo magic-hour-mcp`\n- Each listing in full: https://www.anchorterminal.com/api/v1/tools/google-veo.json and https://www.anchorterminal.com/api/v1/tools/magic-hour-mcp.json\n\n## Other comparisons with Google Veo or Magic Hour MCP\n\n- [Alibaba Wan (Model Studio) vs Google Veo](https://www.anchorterminal.com/compare/alibaba-wan-vs-google-veo.md)\n- [Alibaba Wan (Model Studio) vs Magic Hour MCP](https://www.anchorterminal.com/compare/alibaba-wan-vs-magic-hour-mcp.md)\n- [fal video models vs Google Veo](https://www.anchorterminal.com/compare/fal-video-vs-google-veo.md)\n- [fal video models vs Magic Hour MCP](https://www.anchorterminal.com/compare/fal-video-vs-magic-hour-mcp.md)\n- [framefields vs Google Veo](https://www.anchorterminal.com/compare/framefields-vs-google-veo.md)\n- [framefields vs Magic Hour MCP](https://www.anchorterminal.com/compare/framefields-vs-magic-hour-mcp.md)\n- [Google Veo vs Higgsfield API](https://www.anchorterminal.com/compare/google-veo-vs-higgsfield.md)\n- [Google Veo vs HyperFrames](https://www.anchorterminal.com/compare/google-veo-vs-hyperframes.md)\n- [Google Veo vs Kling AI API](https://www.anchorterminal.com/compare/google-veo-vs-kling.md)\n- [Google Veo vs Luma AI API](https://www.anchorterminal.com/compare/google-veo-vs-luma.md)\n- [Google Veo vs MiniMax Video API](https://www.anchorterminal.com/compare/google-veo-vs-minimax-video.md)\n- [Google Veo vs OpenAI Sora API](https://www.anchorterminal.com/compare/google-veo-vs-openai-sora.md)\n- [Google Veo vs Pika API](https://www.anchorterminal.com/compare/google-veo-vs-pika.md)\n- [Google Veo vs PixVerse API](https://www.anchorterminal.com/compare/google-veo-vs-pixverse.md)\n- [Google Veo vs Popcraft MCP](https://www.anchorterminal.com/compare/google-veo-vs-popcraft-mcp.md)\n- [Google Veo vs Replicate video models](https://www.anchorterminal.com/compare/google-veo-vs-replicate-video.md)\n- [Google Veo vs Runway API](https://www.anchorterminal.com/compare/google-veo-vs-runway.md)\n- [Google Veo vs Seedance on BytePlus ModelArk](https://www.anchorterminal.com/compare/google-veo-vs-seedance-on-byteplus-modelark.md)\n- [Google Veo vs Vidu API](https://www.anchorterminal.com/compare/google-veo-vs-vidu.md)\n- [Higgsfield API vs Magic Hour MCP](https://www.anchorterminal.com/compare/higgsfield-vs-magic-hour-mcp.md)\n- [HyperFrames vs Magic Hour MCP](https://www.anchorterminal.com/compare/hyperframes-vs-magic-hour-mcp.md)\n- [Kling AI API vs Magic Hour MCP](https://www.anchorterminal.com/compare/kling-vs-magic-hour-mcp.md)\n- [Luma AI API vs Magic Hour MCP](https://www.anchorterminal.com/compare/luma-vs-magic-hour-mcp.md)\n- [Magic Hour MCP vs MiniMax Video API](https://www.anchorterminal.com/compare/magic-hour-mcp-vs-minimax-video.md)\n- [Magic Hour MCP vs OpenAI Sora API](https://www.anchorterminal.com/compare/magic-hour-mcp-vs-openai-sora.md)\n- [Magic Hour MCP vs Pika API](https://www.anchorterminal.com/compare/magic-hour-mcp-vs-pika.md)\n- [Magic Hour MCP vs PixVerse API](https://www.anchorterminal.com/compare/magic-hour-mcp-vs-pixverse.md)\n- [Magic Hour MCP vs Popcraft MCP](https://www.anchorterminal.com/compare/magic-hour-mcp-vs-popcraft-mcp.md)\n- [Magic Hour MCP vs Replicate video models](https://www.anchorterminal.com/compare/magic-hour-mcp-vs-replicate-video.md)\n- [Magic Hour MCP vs Runway API](https://www.anchorterminal.com/compare/magic-hour-mcp-vs-runway.md)\n- [Magic Hour MCP vs Seedance on BytePlus ModelArk](https://www.anchorterminal.com/compare/magic-hour-mcp-vs-seedance-on-byteplus-modelark.md)\n- [Magic Hour MCP vs Vidu API](https://www.anchorterminal.com/compare/magic-hour-mcp-vs-vidu.md)\n- [Clueso vs Magic Hour MCP](https://www.anchorterminal.com/compare/clueso-video-vs-magic-hour-mcp.md)\n- [Magic Hour MCP vs sync. labs MCP server](https://www.anchorterminal.com/compare/magic-hour-mcp-vs-sync-labs-mcp.md)\n- [Google Veo vs sync. labs MCP server](https://www.anchorterminal.com/compare/google-veo-vs-sync-labs-mcp.md)\n", "meta": { "attribution": "Anchor Terminal (https://www.anchorterminal.com)", "attributionRequired": true, "credit": "CC BY 4.0, credit Anchor Terminal and link the page or API address you took it from (https://www.anchorterminal.com/terms/#data)", "docs": "https://www.anchorterminal.com/docs/", "generatedAt": "2026-11-08", "license": "CC-BY-4.0", "method": "https://www.anchorterminal.com/benchmark/", "methodology": "0.7", "openapi": "https://www.anchorterminal.com/openapi.json", "preview": false, "run": "2026-10-01", "runLabel": "October 2026 research run", "terms": "https://www.anchorterminal.com/terms/#data" }, "page": { "breadcrumbs": [ { "name": "Home", "url": "https://www.anchorterminal.com/" }, { "name": "Compare", "url": "https://www.anchorterminal.com/compare/" }, { "name": "Google Veo vs Magic Hour MCP", "url": "" } ], "description": "Google Veo scores 69.3 (B) to Magic Hour MCP's 50.7 (D) for video generation. Prices, MCP, x402, uptime and agent notes side by side.", "facts": [ "Google Veo B 69.3", "Magic Hour MCP D 50.7", "scores" ], "h1": "Google Veo vs Magic Hour MCP", "image": "https://www.anchorterminal.com/assets/og/default.png", "path": "/compare/google-veo-vs-magic-hour-mcp", "published": "2026-10-01", "section": "tools", "title": "Google Veo vs Magic Hour MCP for AI agents in 2026: scores and prices", "toc": null, "updated": "2026-11-07", "url": "https://www.anchorterminal.com/compare/google-veo-vs-magic-hour-mcp" }, "tokens": { "markdown": 4750, "slim": 2730 }, "version": 1 }