Generating video from Claude and Cursor with one API key (MCP + agent skills)

Posted on Nov 5 • Originally published at Medium

Disclosure: I work on Revana. The examples use its MCP server and REST API because that's what I know end to end. The patterns (quote first, cap the cost, idempotent retries, wait without polling) apply to any paid generation API you give an agent.

Coding agents are now good at the glue work around media: writing a storyboard, generating a start frame, rendering a clip, trimming it with ffmpeg, and committing the result to a repo. What they lack out of the box is a safe way to spend money on generation. An agent that can call a video model in a retry loop can also burn $50 in a minute.

This post covers two ways to give Claude (Claude Code, Claude Desktop) and Cursor access to video models such as Seedance 2.5, Veo 3.1 and Kling, through a single key:

You can use either or both. MCP is less work. The skill gives you more control and works in any agent that can run a shell.

Everything below is also in a public repo, Aribk7/revana-skills: ready-made Agent Skills for Claude Code, Codex and Cursor, runnable examples, and two n8n workflows.

Revana runs a remote MCP server over streamable HTTP at:

https://revana.si/api/mcp Enter fullscreen mode Exit fullscreen mode Claude Code claude mcp add --transport http revana https://revana.si/api/mcp Enter fullscreen mode Exit fullscreen mode Then type /mcp inside Claude Code and choose revana to sign in. The OAuth flow creates a separate API key for this connection. You can revoke it from the dashboard without touching your other keys.

Add it as a custom connector with the same URL, then click Connect and approve it on revana.si.

Add the server to ~/.cursor/mcp.json (global) or.cursor/mcp.json (per project). With OAuth, Cursor asks you to sign in the first time a tool is used:

{ "mcpServers": { "revana": { "url": "https://revana.si/api/mcp" } } } Enter fullscreen mode Exit fullscreen mode Any client that takes headers If your client doesn't support OAuth, pass an API key from the dashboard as a header. Keep this file out of git: the key spends real credits.

{ "mcpServers": { "revana": { "type": "http", "url": "https://revana.si/api/mcp", "headers": { "Authorization": "Bearer sr_live_YOUR_KEY" } } } } Enter fullscreen mode Exit fullscreen mode VS Code and Codex CLI one-liners, for completeness:

code --add-mcp '{"name":"revana","type":"http","url":"https://revana.si/api/mcp"}' codex mcp add revana --url https://revana.si/api/mcp && codex mcp login revana Enter fullscreen mode Exit fullscreen mode What the agent gets Tool What it does Costs money list_models Every video/image model with options and price no get_quote Exact price for a request, before anything runs no get_balance What the credits can spend now, what's held by running jobs no upload_file Turn a local image/clip/sound into an https link for references (14 days) no generate_video Start the generation, capped by max_cost_usd yes get_video Wait for a job (long-poll up to 40 s per call) no get_video_link A download link for the result (valid one hour) no The design choice that matters is that quoting is a separate, free tool and the server instructions tell the model to quote first and ask before calling generate_video. In practice, this prompt:

Make a 5-second 720p video of a paper boat in the rain with Seedance 2.5. Tell me the price first.

produces a get_quote call, a message like "That's $1.05 (5 s x $0.21/s at 720p, price as of 2026-11-05). Go ahead?", and only after you answer yes, a generate_video call with max_cost_usd: 1.25 and an idempotency key the agent makes up. If the agent retries after a network error, it reuses that key, and the server returns the same job instead of starting a second paid one.

The other detail is get_video with wait_seconds. Without it, agents tend to poll in a tight loop and fill their own context with status messages. A long-poll lets one tool call wait up to 40 seconds.

MCP is convenient, but sometimes you want the agent to drive the HTTP API directly: in CI, in a sandbox without MCP, or when you want the generated files written straight into the repo. In that case, give the agent a short rules file and a key in the environment.

The key goes in the environment, set by you, never pasted into the chat:

export REVANA_API_KEY = sr_live_... # in your shell profile or a.env the agent can't print Enter fullscreen mode Exit fullscreen mode Then add a skill. For Claude Code that's.claude/skills/video/SKILL.md. For Cursor, put the same text in.cursor/rules/video.mdc.

If you'd rather not write it yourself, the revana-skills repo has finished skills for video, images, UGC ads, music and picking the cheapest model. Copy a folder from its skills/ directory into ~/.claude/skills/ (or your agent's skills directory). The minimal version looks like this:

--- name: video description: Generate a video or image with the Revana API (Seedance 2.5, Veo 3.1, Kling, Wan, Nano Banana Pro). Use when the user asks to make, render or animate a video or image. --- # Rules 1. The key is in $REVANA_API_KEY.

Never print, echo or write it to a file. 2. Quote first from the live price list (no key needed) and wait for a "yes": curl -s https://api.revana.si/v1/models | jq '.data[] | select(.id=="seedance-2.5") |.price' Cost = price.usd[resolution] (or " <res> +audio" when present and audio is on) x duration.

3. Always send max_cost_usd equal to the agreed price. 4.

Send an Idempotency-Key header. On any retry, send the same key and the same body. 5.

Poll GET /v1/generations/{id} every 5 s until status is succeeded or failed. 6. Download with GET /v1/generations/{id}/content into./media/, then tell the user the path and the final cost_usd.

7. If error.retryable is false, don't retry: change the request or ask the user. Enter fullscreen mode Exit fullscreen mode With the skill in place, the agent's generated commands look like this:

# 1. submit (202 Accepted; a replay of the same key returns 200 with the same job) GEN = $( curl -s https://api.revana.si/v1/generations \ -H "Authorization: Bearer $REVANA_API_KEY " \ -H "Content-Type: application/json" \ -H "Idempotency-Key: boat-rain-v1" \ -d '{ "model": "seedance-2.5", "input": { "prompt": "a paper boat drifting down a rain-soaked street, low angle, shallow depth of field", "resolution": "720p", "duration": 5, "aspect_ratio": "16:9", "audio": true }, "max_cost_usd": 1.05 }' ) ID = $( echo " $GEN " | jq -r.id ) # 2. poll while:; do G = $( curl -s https://api.revana.si/v1/generations/ $ID -H "Authorization: Bearer $REVANA_API_KEY " ) S = $( echo " $G " | jq -r.status ) [ " $S " = succeeded ] || [ " $S " = failed ] && break sleep 5 done echo " $G " | jq '{status, cost_usd, error}' # 3. download (the endpoint redirects to a short-lived file URL, hence -L) mkdir -p media curl -sL https://api.revana.si/v1/generations/ $ID /content \ -H "Authorization: Bearer $REVANA_API_KEY " -o media/boat-rain.mp4 Enter fullscreen mode Exit fullscreen mode Image-to-video from a local file Agents often generate a start frame first and then animate it. Reference media must be public https:// URLs, so a local file goes through /v1/uploads first. The upload is free, and the returned link is valid for 14 days:

// upload.mjs: node upload.mjs frame.png -> prints a https link to use as image_url import { readFile } from " node:fs/promises "; import { basename } from " node:path "; const file = process. argv [ 2 ]; const bytes = await readFile ( file ); const headers = { Authorization: `Bearer ${ process. env. REVANA_API_KEY } `, " Content-Type ": " application/json " }; const up = await fetch ( " https://api.revana.si/v1/uploads ", { method: " POST ", headers, body: JSON. stringify ({ content_type: " image/png ", bytes: bytes. length, filename: basename ( file ) }), }). then (( r ) => r. json ()); // PUT the bytes with exactly the headers the API returned (content type and length are signed) const put = await fetch ( up. upload_url, { method: up. upload_method, headers: up. upload_headers, body: bytes }); if (! put. ok ) throw new Error ( `upload failed: ${ put. status } ` ); console. log ( up. url ); // e.g. https://api.revana.si/v1/uploads/upl_..., good for 14 days Enter fullscreen mode Exit fullscreen mode Then the generation takes it as the first frame:

{ "model": "seedance-2.5", "input": { "prompt": "the boat starts to drift, rain intensifies", "image_url": "https://api.revana.si/v1/uploads/upl_...", "resolution": "720p", "duration": 5, "aspect_ratio": "16:9", "audio": true }, "max_cost_usd": 1.25 } Enter fullscreen mode Exit fullscreen mode What actually goes wrong with agents and paid APIs After a few weeks of running this daily, these are the problems I've seen and what fixes each one:

The revana-skills repo also has runnable examples (curl, Node, Python, Next.js route handlers, Vercel AI SDK tools, MCP configs) and importable n8n workflows that quote, create, wait and download.

The full API is described in an OpenAPI file at https://revana.si/openapi.json, and GET https://api.revana.si/v1/models lists every model and price without a key. Prices quoted in this post are as of 2026-11-05.

Try it: revana.si has one API key for 200+ video and image models, with live prices on revana.si/pricing.