# Luma AI API vs sync. labs MCP server (slim)

> sync. labs scores 51.5 (D) to Luma AI's 50.5 (D) for video edit. Prices, MCP, x402, uptime and agent notes side by side.

- Full: https://www.anchorterminal.com/compare/luma-vs-sync-labs-mcp.md (~4,800 tokens) · this version ~2,730 tokens · JSON https://www.anchorterminal.com/compare/luma-vs-sync-labs-mcp.json · canonical https://www.anchorterminal.com/compare/luma-vs-sync-labs-mcp
- Index: https://www.anchorterminal.com/llms.txt · API: https://www.anchorterminal.com/api/v1/index.json · MCP: https://www.anchorterminal.com/mcp · Updated: 2026-11-07
- Licence: CC BY 4.0, credit Anchor Terminal and link this page (https://www.anchorterminal.com/terms/#data)

sync. labs MCP server scores 51.5 (D) on agent readiness against Luma AI API's 50.5 (D), and leads in 3 of 7 scored categories. Luma AI API leads on reliability, agent ergonomics, security & auth and transparency & trust. Both do video edit.

- Luma AI API: D 50.5, rank #1058 of 1510 · https://www.anchorterminal.com/tools/luma.min.md
- sync. labs MCP server: D 51.5, rank #1026 of 1510 · https://www.anchorterminal.com/tools/sync-labs-mcp.min.md
- Luma AI API, good for Pipelines that want one model for generate, edit, extend and reframe, and colourists who want HDR and EXR. Ahead on Reliability, 57 against 43; Agent ergonomics, 66 against 55; Security & auth, 53 against 38; Transparency & trust, 67 against 44.
- sync. labs MCP server, good for Agents that lip-sync or dub video into other languages. Ahead on Schema & documentation, 81 against 53; Payments & pricing, 30 against 20; Maintenance & community, 75 against 47. Also Open source.

| Category | Luma AI API | sync. labs MCP server |
| --- | --- | --- |
| Reliability (16%) | 57 | 43 |
| Performance (10%) | pending | pending |
| Schema & documentation (13%) | 53 | 81 |
| Agent ergonomics (13%) | 66 | 55 |
| Security & auth (14%) | 53 | 38 |
| Payments & pricing (10%) | 20 | 30 |
| Task success (10%) | pending | pending |
| Maintenance & community (7%) | 47 | 75 |
| Transparency & trust (7%) | 67 | 44 |

| Fact (where they differ) | Luma AI API | sync. labs MCP server |
| --- | --- | --- |
| Kind | Model API | MCP server |
| Vendor | Luma AI | Synchronicity Labs (sync.) |
| Hosted endpoint | `https://agents.lumalabs.ai/v1` | `https://mcp.sync.so/mcp` |
| Transports | HTTP | Streamable HTTP |
| Auth | API key | OAuth or key |
| Pricing | Pay per use | Paid |
| Price for video edit | $0.216 per second of video | not published |
| Licence | Apache-2.0 (SDKs) | MIT |
| llms.txt | no | yes |
| MCP registry | not listed | `io.github.synchronicity-labs/mcp-server` |
| Last release | 2026-08-05 | none |
| Terms last updated | 2026-05-14 | no document linked |
| Privacy policy last updated | 2026-04-20 | no document linked |
| Customer content may train models | yes | not read yet |
| Terms restrict automated access | yes | not read yet |
| Terms restrict benchmarking | yes | not read yet |
| Terms or service can change without notice | yes | not read yet |
| Arbitration or class-action waiver | yes | not read yet |
| Popularity | 2 stars, 982 npm/wk | none |
| Agent reviews | 3/5 (2) | none |

Why the edge:
- Schema & documentation, sync. labs MCP server +28: Luma AI API 53 (No public OpenAPI document is linked from the docs. The API reference at /api/ is generated per method with no visible spec download (0). docs.agents.lumalabs.ai/llms.txt returns 404, but every docs page links a Markdown twin (for example /index.md and /guides/pricing/index.md) (10). Guides cover generation, keyframes, edit, extend, reframe, deletion, files, usage and the migration, and say which options don't combine, such as start and end frames with 10 second clips (14). Typed fields for model, type, resolution and duration with fixed values (12). curl and SDK examples, both 429 bodies and generation failure codes are documented (12). Responses carry an X-API-Version header and the SDK repositories keep dated changelogs, but the API docs have no changelog and the public changelog page on lumalabs.ai was last updated in June 2025 (5). 0+10+14+12+12+5 = 53.); sync. labs MCP server 81 (Tools generated from the public API specification plus workflow tools, with typed schemas in the source (25). llms.txt and .md pages (10). Tool table with descriptions (14 of 20). Typed from the API spec (12 of 15). Examples and an estimates tool; errors not documented (8 of 15). Tags v0.2.2 to v0.2.4 and dated commits (12 of 15). 25 + 10 + 14 + 12 + 8 + 12 = 81.)
- Maintenance & community, sync. labs MCP server +28: Luma AI API 47 (Model reading. The latest dated API change found is SDK v0.5.0, whose changelog dates it 4 August 2026 (tag 5 August), adding the layering parameter to generations. That is more than 90 days before 4 November, so 10 (within 180 days). The docs now carry deletion, files and usage guides with no dates, and the 3 November MCP connector runs Luma Agents workflows on a subscription, which the API doesn't serve, so neither counts (10). Ray 2, Ray 3 and their variants are retiring, but the cutoff dates go out in private notices and the migration guide gives none (5). No API changelog. The SDK changelogs are dated and support is an email address on the migration guide (7). Official SDKs for Python, TypeScript and Go and a CLI, last released on 5 August with Ray 3.2 and files support, though the new deletion routes aren't in them yet (15). Each SDK repository has a CI workflow (10). 10+5+7+15+10 = 47.); sync. labs MCP server 75 (v0.2.4 and commits on 7 November 2026 (30). Three tags in recent weeks (20). Issues not read (0). Official registry entry io.github.synchronicity-labs/mcp-server (15). CI with verify, publish and review workflows (10). 30 + 20 + 0 + 15 + 10 = 75. Registry presence read from Anchor Terminal's own daily import of the official MCP registry (/api/v1/registry.json, 6 November 2026), not the registry's API.)
- Transparency & trust, Luma AI API +23: Luma AI API 67 (Closed models. The terms give customers the outputs, with commercial use tied to an active paid plan (15). The API terms state that API inputs and outputs aren't used for training (10). The pricing page's comparison table says Pay-as-you-go has no no-train guarantee and only Provisioned Throughput does. That contradiction is charged once, as a misleading claim under negative events, as rime-prism's training contradiction is, so it doesn't also lower this line. The privacy policy (20 April 2026) describes retention by criteria without periods, and the deletion guide sets retention per API client with a one-year hold for moderation failures (5). The privacy policy was read and names US hosting with Standard Contractual Clauses for transfers. No DPA was read (5). A public migration guide without dates, retirement dates by email only (5). A subprocessor list (last updated 4 October 2026) names about 50 providers with their purpose, and the privacy policy says the services are hosted in the United States (15). 15+10+5+5+5+15 = 55.); sync. labs MCP server 44 (MIT open source (30). Data handling not read (5 of 30). No deprecation policy; earlier tool names documented as superseded (5 of 20). Subprocessors not found (0). 30 + 5 + 5 + 0 = 40.)
- Security & auth, Luma AI API +15: Luma AI API 53 (Model reading of the checklist (credential, training, retention, operator visibility, programme). Bearer keys created in the platform and shown once, with quota and limits shared by all keys of a client. No scopes found (20). The API terms of 28 April 2026 say Luma won't use API inputs or outputs to train or develop its models (20). A deletion call is now documented, DELETE /v1/generations/{id} with a deletion task polled at GET /v1/deletions/{task_id}, though the guide says it may not be enabled for every API client and the SDKs don't include it yet (5). Retention is set per API client, with no default period stated, and a generation that fails moderation can be held for at least a year (0). Rate-limit headers, a request id per call, and GET /v1/usage for spend by session or end user, with no audit log found (8). No security.txt (lumalabs.ai/.well-known/security.txt returns 404), bug bounty or certification found for Luma AI (0). 20+20+5+0+8+0 = 53.); sync. labs MCP server 38 (OAuth per organisation, or an API key in the environment (22 of 30). No read-only mode (3 of 20). Media in and out, no third-party text (10). No audit log found (0). No security programme found (3 of 20). 22 + 3 + 10 + 0 + 3 = 38.)
- Reliability, Luma AI API +14: Luma AI API 57 (Better Stack status page at status.lumalabs.ai with API, Dream Machine and Luma Agents components, an incident list and an RSS feed (20). In the 90 days from 6 August the feed lists three incidents, all on legacy Ray2 models: Ray2 Flash timeouts on 2 to 3 September (about 9 hours) and 15 to 16 September (about 2 hours), and Ray2 queue times on 16 to 17 September (about 13 hours). The status page tags each with its API and Dream Machine components, and each hit one legacy model, so minor only (20). The authentication incident counted as a major on 1 October was on 16 July and has left the window. Limits are per minute and per concurrent job, but the numbers sit in the dashboard, not the docs (5). Every 429 carries Retry-After, with separate bodies for the per-minute and concurrency limits and backoff guidance with jitter. Rejected requests aren't queued and synchronous errors are never charged, which is safe-retry guidance, but there is no idempotency key, so 12 as settled in this run (12). No SLA document. The pricing page lists a latency SLA for Provisioned Throughput only as a table entry (0). The pricing page says video rates may change before general availability, so the video surface isn't GA yet (0). 20+20+5+12+0+0 = 57.); sync. labs MCP server 43 (Status page at status.sync.so with maintenance and previous incidents (20). History not read (5). No MCP limits found (0). The source has abort-signal handling and recovery guidance for long jobs (8 of 15). No SLA found (0). Version 0.2.4, not labelled beta (10). 20 + 5 + 0 + 8 + 0 + 10 = 43.)
- Agent ergonomics, Luma AI API +11: Luma AI API 66 (Generations come back as small JSON objects with a presigned URL for the output (15). We found no callback for the Agents API, so jobs are polled (0 of 10). Resolution and duration set output size (10). The API reference lists create, get and delete for generations and a list call only for files, so there is no list of past generations (0 of 10). The 429 detail string tells an agent whether to wait for Retry-After or for a job to finish, and failures carry codes (16). No idempotency key. Moderated and failed generations are refunded and synchronous errors aren't charged, so a retry after a failure is safe (10). One generation endpoint with few required fields, and official SDKs for Python, TypeScript and Go plus a CLI (15). 15+0+10+0+16+10+15 = 66.); sync. labs MCP server 55 (A generated catalogue filtered by client profile, curated for ChatGPT (15). Project history and estimates (12 of 20). Recovery tools; errors not documented (8 of 20). Annotations not read (5 of 20). OAuth or a key, npm package and library use (15). 15 + 12 + 8 + 5 + 15 = 55.)