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Valmera vs Reap: two video MCP servers built for opposite jobs

Reap and Valmera are the two products most often named in the same sentence as "video editing MCP server", and they are close to opposites in what they do with the footage. Reap takes one long recording and multiplies it — clips, animated captions in 100+ languages, dubbing in 80+. Valmera takes one recording and finishes it — cuts, captions, music, grade, zooms, object removal, one export from the original file. Everything below was checked against both vendors' own pages on 5 August 2026.

THE VERDICT, FIRST

If what you need is many deliverables out of one recording — short clips for several platforms, captions in a language your audience actually reads, a dubbed version for another market, all scheduled out to social accounts — Reap is the better product and it is not close. Valmera has no dubbing, no translation, no batch output, no publishing and no team seats. If what you need is one video that is genuinely finished — dead air cut, captions timed to the new edit, music ducked under speech, a grade, punch-ins that land on the right words, a watermark repainted out — Valmera is the better product, and Reap does not attempt most of that. The MCP tool counts, 10 against 110, are not a scoreboard; they are the shape of those two bets written down.

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What each product actually is

Reap — a repurposing and localisation system

Reap describes itself as an AI video editor that turns long videos, webinars and interviews into clips, animated captions, dubbed versions and translated subtitles, and it is more accurate to read it as a production pipeline than as an editor. You give it a long recording; it finds the moments worth pulling, reframes them for vertical with speaker detection, captions them, optionally dubs them, and can publish them to TikTok, Instagram Reels, YouTube Shorts, LinkedIn, Facebook and X from a built-in content calendar. Its clipping is prompt-first — you direct it by intent, topic, hook or audience — rather than only algorithmic virality scoring, which matters if your reason for clipping is not virality at all.

The part that is genuinely uncommon is the language surface. Captions in 100+ languages, dubbing in 80+ with voice cloning, and explicit support for romanized scripts — Hinglish, romanized Urdu, Arabizi, romanized Bengali, Tagalog-English — which is how an enormous number of people actually write on social platforms and which most caption tools simply cannot produce. Reap reaches you four ways: the web app, a REST API, a CLI, and a hosted MCP server, plus connectors for n8n, Zapier and Make.

Valmera — an agent that performs the whole edit

Valmera is an agentic video editor. You upload real footage (up to 14 GB or 3 hours — MP4, MOV, MKV, WebM) and describe the edit in plain English. The system indexes the file into a word-level transcript with speaker labels, silence detection, shot detection and labeled frame tiles the agent reads directly, then the agent edits a versioned edit decision list, renders a preview, looks at the frames it just produced, and corrects itself. Nothing is destructive; any cut can be restored; the final export is cut from the original upload at source quality. The same tool registry the agent uses is published as a remote MCP server, so Claude can drive the whole thing from inside a conversation.

Its scope is one project at a time and one deliverable per request. That is the trade it makes: depth on a single video instead of throughput across many.

Where Reap is genuinely better

This page is published by one of the two vendors, so the honest thing is to start here rather than bury it. Five areas where Reap wins outright:

Dubbing and translation. Dubbing across 80+ languages with voice cloning, and captions and subtitle translation across 100+. Valmera does neither, at all. If you publish the same video into more than one language, this single row decides the comparison and nothing further down changes it.

Romanized scripts. Hinglish, romanized Urdu, Arabizi. This is a real engineering choice, not a marketing line — producing captions in the script an audience writes in, rather than the one a language table says they should use, is the difference between captions that get read and captions that get scrolled past.

Volume. One request can produce many clips, each reframed and captioned, and Reap can publish and schedule them out. Valmera produces one deliverable per request — there is no batch multi-clip output and no publishing integration of any kind. For a team whose job is filling a content calendar, that is a structural advantage.

Teams and brand consistency. Role-based workspace permissions, multiple seats, shared assets, and brand templates that lock fonts, colours, intros, outros and caption styles across everything the team ships. Valmera has no team seats, no collaboration and no stored brand kits — a repeated look has to be re-described each time.

A conventional API. Reap has a documented REST API with a published OpenAPI spec, plus a CLI, alongside its MCP server — and its own pages put API access on every paid tier from $9.99/month rather than behind an enterprise call. Valmera ships an MCP server and deliberately does not ship a REST API — auth is a user account over OAuth, there are no organisation seats and no per-project API keys to rotate. If you are wiring video into a backend service rather than into an agent, Reap fits that shape and Valmera does not.

And the entry price: Reap's paid tier starts at $9.99/month billed annually, well under Valmera's $30 Creator plan.

Feature comparison

Every row was checked against the vendors' own product, pricing, API and MCP pages on 5 August 2026. Where a vendor does not publish something, the cell says not published rather than guessing — absence from a marketing page is not proof a feature is missing.

ValmeraReap
Unit of outputOne finished videoMany clips / language variants
Starts fromYour uploaded file (14 GB / 3 h)A long video or a URL
Remote MCP server
Tools exposed over MCP108 (97 editing + 11 session)10
MCP authOAuth 2.1 + DCR, or bearer tokenAPI key
REST API + CLINo (MCP only, by design)
Long video → short clips
Batch: many deliverables per request
Publish / schedule to social accounts
AI dubbing (80+ languages)
Subtitle translation (100+ languages)
Romanized-script captions
Caption languagesSpoken language; English best-tested100+
Caption styling11 presets · 12 fonts · 9 entrances50+ presets
Subtitle file (SRT/VTT) exportTranslation published; file format not specified
Auto-reframe to vertical / square16:9, 9:16, 1:1, 4:5Yes, social formats
Silence and filler-word removalNot published
Colour grading and finishing effectsNot published
Music library, ducking, masteringNot published
AI sound effects, images, short clipsNot published
AI b-roll insertion
Erase a watermark or object from the pixelsNot published
Agent can look at the frames it renderedNo such tool published
Replies verified against the recorded editNot claimed
Team seats and role permissions
Brand templates / stored brand kits
Free tier without a card
Watermark on the free tierSmall mark, top-leftYes, and 720p only
Export qualityFrom the original file, source quality1080p (Creator) · 4K (Studio)

Pricing

Both tables checked 5 August 2026 against each vendor's own pricing page. Prices change; re-check before you buy.

Reap

PlanPriceWhat it includes
Free$01 h/month of AI clipping and 1 h of captioning, 720p watermarked exports, 1 seat, no API access
Creator$9.99/mo · $119.88/yrUp to 10 h/month, 1080p watermark-free, up to 2 h/month dubbing and translation, 3 brand templates, 1 seat, API access
Studio$29/mo · $348/yrUp to 20 h/month, 4K watermark-free, up to 5 h/month dubbing and translation, up to 3 seats, 6 brand templates, API access
EnterpriseCustomCustom hours, unlimited seats and brand templates, 4K, API access and custom integrations

One thing worth knowing before you pick a tier: the monthly prices are shown as reductions from $24 and $50, so the headline $9.99 is a promotional rate rather than a list rate — treat it as such and check what it renews at. API access, on the other hand, is not gated the way it is at most tools in this category: Reap's own pages put the REST API, the CLI and the MCP server on every paid tier from $9.99, not behind Enterprise.

Valmera

PlanPriceWhat it includes
Free$050 one-time credits, no card, never refills; exports carry a small Valmera mark
Creator$30/mo · $300/yr2,000 credits per billing cycle, no watermark, 3-day trial
Pro$50/mo · $500/yr4,000 credits per billing cycle, no watermark, 3-day trial
Frontier$100/mo · $1,000/yr10,000 credits, a stronger model for reasoning and vision, 3-day trial

The two meters measure different things and are not convertible. Reap charges by hours of video processed, which is predictable and rewards volume: a 20-hour month is a 20-hour month whether the work was trivial or not. Valmera charges by the AI work an edit actually takes — a simple request costs a few credits, a long conversation about a long video costs more — which rewards knowing what you want and punishes fishing. During a Valmera trial the account can spend 10% of the plan's credits; converting releases the rest. See plans for the current numbers.

The honest comparison is not $9.99 against $30. It is: what is the cost of the outcome you need? One finished, graded, music-mixed video a week is not something Reap produces at any price. Forty captioned clips in six languages is not something Valmera produces at any price.

The workflow difference, in one picture

The tool counts follow from the pipeline shapes. Reap runs a fan-out: one input, one analysis pass, many outputs, each finished by the pipeline and judged by you afterwards. Valmera runs a closed loop: one input, one edit decision list, a preview render, the agent looking at the frames it produced, and a revision — repeated until the single deliverable is right.

Fan-out pipeline versus closed edit loopTwo lanes. The top lane, Reap, shows one long source video feeding a single analysis step, which fans out into four parallel deliverables — a clip, a captioned clip, a dubbed clip and a translated-subtitle clip — each leaving the pipeline directly as an export. There is no arrow returning to the analysis step. The bottom lane, Valmera, shows one uploaded file feeding an index step, then an edit decision list, then a preview render, then a step where the agent looks at the frames it produced; an arrow returns from that step to the edit decision list, forming a loop. Only after the loop settles does a single export leave, cut from the original file.REAP — FAN-OUT: ONE PASS, MANY DELIVERABLESLong videourl or uploadOne analysis passfaces · tone · pacingClip · 9:16reframedClip + captions100+ languagesClip, dubbed80+ languagesTranslated substiming keptExport ×4+ scheduleNo arrow comes back. Quality is judged by a person, after the pipeline has finished.VALMERA — CLOSED LOOP: ONE DELIVERABLE, REVISED UNTIL IT LANDSUpload14 GB / 3 hIndexwords · shots · tilesEdit decision listversioned, non-destructivePreview renderfast proxyAgent looks at itreal rendered frameswrong aim, wrong moment, wrong size → revise the listnothing left to fixOne exportcut from the ORIGINAL fileEvery reply is checked against the edits recorded in the list, sothe agent cannot report work it did not do.

Read the two lanes as answers to one question: who checks the result? In a fan-out, the pipeline cannot check itself, because there is no single result to check — there are forty, and a human skims them. That is a perfectly sound design when the deliverables are short and interchangeable, and it is why Reap can be fast and cheap per output. In a closed loop, the agent is the first reviewer: it renders, it looks at the frames, and it fixes what it sees. That only pays for itself when the deliverable is one thing you care about, and it is why Valmera costs more per output and takes longer.

The tool counts fall straight out of this. Ten tools are enough to describe a fan-out — submit, poll, retrieve, plus one verb per output type. A closed loop needs a vocabulary rich enough for the corrections a reviewer makes: not "caption it" but "move that caption above the lower third for the six seconds the chart is on screen". That is where 97 editing tools come from, and it is the reason the number is not bragging — it is arithmetic.

The MCP surface, side by side

Reap claims to be the first video editing MCP server with integrated AI clipping. We have no evidence against that and no interest in disputing it — MCP is recent, Reap was early, and being early is worth something.

Its server is hosted at mcp.reap.video, documented as API-key based with an OAuth protected-resource discovery document published at the endpoint, installable in one command, and it lists ten tools: create_clips, add_captions, dub_video, translate_subtitles, transcribe, reframe, get_status, get_results, list_templates and export_video. Reap names Claude Desktop, Claude Code, Cursor, VS Code, Windsurf, Gemini CLI and ChatGPT as supported clients, and publishes an OpenAPI spec and an llms.txt so a model can read the docs. That is a well-built server. Six of those ten are editing verbs; the other four are the submit-poll-retrieve-and-deliver plumbing every async pipeline needs.

Valmera's server is hosted too, and uses OAuth 2.1 with dynamic client registration and PKCE, so the client registers itself and you sign in — there is no key to store, paste into a chat window, or rotate — with a bearer token available for clients that have no OAuth support. It exposes 108 tools: 97 editing tools and 11 session tools for projects, uploads, indexing, rendering, export and download. Two design details matter more than the count. The registry is the same one Valmera's own agent uses — the tools are not re-declared for MCP, so there is no second list that can drift out of step with the product. And slow operations return a job id and a wait_for_job tool rather than a fabricated completion, because a model that is told a render finished when it has not will confidently describe frames that do not exist.

If you want the full field rather than these two, we keep a side-by-side of every video editing MCP server — Valmera, Reap, OpenClip, Video Jungle and the DaVinci Resolve bridge — and a definitional guide to what MCP video editing is. Setup for either server is a few minutes; ours is documented per client on the MCP setup page.

What this feels like on a real job

A 90-minute webinar you need to spread. Reap. You point it at the recording, it finds the moments, reframes them vertical, captions them, dubs the three best into Spanish and Hindi, and schedules them. You review a folder of finished clips. Doing this in Valmera would mean one conversation per clip and no dubbing at the end of it — the wrong tool, used stubbornly.

A 12-minute launch video that has to be right. Valmera. The dead air comes out and the cuts snap to word boundaries; captions are timed against the new edit rather than the raw recording; music ducks under speech; a grade goes on; punch-ins land on the words that carry the argument; the client logo in the corner of the screen recording gets repainted out of the pixels; the export is cut from the original file at source quality. Reap does not attempt most of that list, and would not claim to.

Both, in sequence. This is not a rhetorical concession — it is the most sensible pipeline for a lot of teams. Finish the long video in Valmera, then hand the finished file to Reap to clip, caption and localise. Both are remote MCP servers, so a single agent session can hold both connectors and move between them without you touching a file manager.

See what a closed loop produces

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Where Valmera is genuinely better

Finishing. Cutting is the first ten minutes of an edit. The rest is captions timed to the new cut, music that gets out of the way of speech, a grade, zooms that land on the right words, a sound effect on the moment that needs one, and a watermark that has to go. Valmera has caption presets, fonts and animations, a 23-track CC0 music library with sidechain ducking, voiceover and one-request mastering to −14 LUFS, six colour-grade presets with custom exposure, contrast, saturation, temperature and tint, eight finishing effects, seven transition styles, and pixel-level erasure of a watermark or a small static object. Reap publishes none of that.

The agent sees its own output. After a render, Valmera's agent looks at the actual frames it produced and reacts to them. That is what makes "blur the username in the corner" or "end on the wide shot" land rather than approximate, because the aim point is a measurement off a real frame instead of a guess from a transcript.

Replies you can trust. Every agent reply is verified server-side against the edits actually recorded. The agent cannot claim a cut, a caption or a music change it did not make; if nothing changed, it says so. When an AI is doing the work unattended, an agent that reports honestly is worth more than one with a longer feature list.

Non-destructive by construction. Edits are entries in a versioned edit decision list, the upload is never modified, any cut can be restored, and the final export is cut from the original file — previews use a faster proxy, the deliverable does not.

Editing without a template. Because the tool surface is a vocabulary rather than a menu of pipelines, requests that no product has a button for still work: change the aspect ratio partway through and back, put text behind the subject, enhance a mouse cursor in a screen recording, splice in a generated still with Ken Burns motion, snap existing cuts onto the music's beat grid.

Where Valmera fits, and where it does not

Valmera is for one person with one video that matters, who would rather describe the outcome than operate a timeline. It is at its best on talking-head footage, screen recordings, podcasts and launch videos, in one language, ending in one file.

It is the wrong tool if you need dubbing, subtitle translation, SRT or VTT files, team seats, brand kits, direct publishing or scheduling, batch multi-clip output, a REST API, or a native mobile app — none of which exist. It is also not a text-to-video generator: it edits footage you already have. English is the best-tested transcription path. Captions are burned in. And a closed loop costs turns, which cost credits — if your measure of success is clips per dollar, Reap wins that measurement honestly.

Frequently Asked Questions

Neither, in general — they finish different jobs. Reap turns one long recording into many short deliverables and localises them: clips, animated captions in 100+ languages, dubbing in 80+. Valmera turns one recording into one finished video: cuts, captions, music ducking, grading, zooms, object removal, then an export cut from the original file. Ask what leaves the tool at the end. If it is a folder of clips in six languages, that is Reap. If it is one video you would put your name on, that is Valmera.
Reap claims to be the first video editing MCP server with integrated AI clipping, and we have no evidence against it — MCP itself is recent and Reap was early. It is worth saying plainly because being first is not the same as being broadest: Reap publishes 10 MCP tools, Valmera publishes 108 (97 editing plus 11 session tools). Those are different bets, not a ranking.
Reap's MCP page lists 10: create_clips, add_captions, dub_video, translate_subtitles, transcribe, reframe, get_status, get_results, list_templates and export_video. Valmera exposes 108 — 97 editing tools plus 11 session tools for projects, uploads, indexing, rendering, export and download. Tool count is a proxy for how much of an edit the agent can own, not a quality score: a 10-tool server that dubs into 80 languages beats a 108-tool server that cannot dub at all, if dubbing is your problem.
No. Valmera has no dubbing, no voice cloning and no subtitle translation. Captions are burned in, in the language that was spoken, and English is the best-tested transcription path. If your work is publishing the same video across languages, Reap does that and Valmera does not — this is the single clearest reason to pick Reap.
Nothing in Reap's published feature set or MCP tool list covers colour grading, music mixing with ducking, generated sound effects, or repainting a watermark or object out of the pixels. Those are finishing operations, and Reap is not positioned as a finishing tool — it is positioned as a repurposing and localisation system. Valmera has all four, driven from the same chat or the same MCP registry.
Reap, by design. One request can fan out into many clips, each auto-reframed, captioned and optionally dubbed, and Reap can publish and schedule them to connected social accounts. Valmera produces one deliverable per request and has no batch multi-clip output, no publishing and no scheduling. If your bottleneck is volume, that difference is decisive.
Reap's MCP server is hosted at mcp.reap.video and documented as API-key based, with an OAuth protected-resource discovery document published at the endpoint; you sign up in the Reap app for credentials. Valmera's is hosted and uses OAuth 2.1 with dynamic client registration and PKCE, so the client registers itself and you sign in — no key to store or rotate — with a bearer token available for clients that have no OAuth support.
Checked 5 August 2026. Reap: Free $0 (1 hour a month of clipping and 1 hour of captioning, 720p watermarked exports), Creator $9.99/month billed annually ($119.88/year), Studio $29/month ($348/year), Enterprise custom. Valmera: Free $0 with 50 one-time credits and no card, Creator $30/month for 2,000 credits, Pro $50/month for 4,000, Frontier $100/month for 10,000, each paid plan opening with a 3-day trial. Reap meters hours of video; Valmera meters the AI work an edit takes. The two units are not convertible, so compare on the job rather than the sticker.
Yes, and for some workflows that is the honest answer. Reap is stronger at taking a finished long video and spreading it — clips, languages, platforms. Valmera is stronger at making the long video worth spreading. Running Valmera first and Reap second is a coherent pipeline, and both are remote MCP servers, so one agent can hold both connectors at once.
Valmera does: after a render, the agent looks at the frames it actually produced, and every reply is verified server-side against the edits recorded in the edit decision list, so it cannot claim a cut or a caption it did not make. Reap publishes no tool that returns a frame to the model, and makes no reply-verification claim — its MCP pattern is submit, poll, retrieve, which is a reasonable design for a pipeline whose output is judged by a human afterwards.

Choosing between them

Pick Reap if the video already exists and the problem is distribution: more clips, more platforms, more languages, on a schedule, with a team and a brand template holding it together. Its dubbing and its romanized-script captions are things Valmera cannot do at all, and its entry price is a third of ours.

Pick Valmera if the problem is the video itself: making one recording into something finished, with an agent that renders, looks at what it rendered, fixes it, and tells you the truth about what it changed. Fifty free credits, no card, is enough to test that claim on your own footage — which is the only test that settles it.

And if the honest answer is both, run them in that order. Valmera makes the video worth spreading; Reap spreads it.

Start editing with Valmera

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