Framesail AI
@framesail
关于 Framesail AI
Official remote MCP server for Framesail AI. Create long-form (faceless YouTube) videos end to end from any MCP client: script, locked character references, storyboard, voiceover, and final video editing — with characters and style held consistent across every shot.
基本信息
配置
使用下面的配置,将此服务器添加到你的 MCP 客户端。
{
"mcpServers": {
"framesail": {
"type": "streamable-http",
"url": "https://api.framesail.com/mcp",
"headers": {
"Authorization": "Bearer fsk_YOUR_API_KEY"
}
}
}
}工具
68List your channels. Every project lives in a channel, which owns the reusable styles (art/narrative/director) that drive generation.
Create a new channel — the container for projects and their reusable styles. Use when the user wants a fresh creative identity rather than adding to an existing channel.
List projects in a channel.
Create a project. The description (the video concept/topic) seeds script generation, so write a meaningful one. The response's web_url is the project's page in the web app — share it so the user can follow along.
Fetch a project row — settings, voice config, default style, export URL.
Patch project fields. Updatable: title, description, asset_mix, sfx_level, video_concept, voice_mix, voice_tts_provider, script_target_minutes, narrator_speed. (The narrator's TTS voice is NOT here — use set_narrator_voice.)
Permanently delete a project and everything in it (script versions, assets, voiceover, segments, renders). Irreversible — confirm with your user first.
Set the project's default style — the style whose art/narrative/director fields drive its generations. Use after create_style to put a new visual identity into effect, or to switch a project between channel styles.
Merge a patch into the project's burned-in caption config (keys like enabled, plus styling). Read the current value from get_project (caption_config). Applies at the next export — no rebuild needed.
THE resume/orientation tool: one call returns every pipeline step's state (script -> scan -> reference_images -> voices -> voiceover -> style_templates -> storyboard -> segment_assets -> scenes -> export), any running jobs, and a next_action telling you exactly what to do next. Call this when picking up an existing project, after any await_jobs, or whenever you're unsure where a video stands — never guess pipeline position. Every step carries a web_url — the page in the Framesail web app where your user can see that step's output. Share it whenever you present a step's results ("review the storyboard here: ...") so they can inspect and edit in the browser; the app and this API act on the same live state.
Poll this between steps: returns active + recently-finished AI jobs (scope by project_id, or style_id for style analysis), plus per-segment- asset render statuses for projects. A step is done when its jobs reach status=complete (or error, with a user-readable message). NOTE: finished jobs drop out of `jobs` after ~30s — a short list does NOT mean work was lost; judge render batches by `segment_assets` statuses (or get_pipeline_progress), never by counting jobs. Prefer await_jobs over polling this in a tight loop.
Block (server-side) until the scope has no pending/running jobs, or the timeout passes — use this instead of polling get_workflow_status yourself. Returns {done, jobs}. If done=false the work is still running: just call await_jobs again (a 3-5 minute storyboard takes a few consecutive calls). Keep timeout_seconds <= 50 so the client doesn't time out the tool call.
Inspect the prompt sections a generation job exposes for per-call override via editable_sections (jobs: script, script_scan, storyboard, segment_image, segment_video, voice_block, ...). Sections marked locked cannot be overridden.
List the models allowed for a generation job, with display names, credit estimates, and each model's settings_schema — the valid keys for that tool's `settings` param (e.g. image quality/orientation, video duration). The first entry is the default every tool uses when model is omitted.
Generate the project's script from its description/concept and the channel's narrative style. Async — returns {job_id}; poll get_workflow_status.
Read the active script's full text + the version list. Use this to show the script to your user for review/feedback before scan_script — the review-edit-resave loop (get_script -> discuss -> save_script) is the expected workflow when the user wants input.
Save script text (your own draft, or an edited version of the generated one — saving creates a new version, old versions are kept). Run scan_script afterwards so assets and voice blocks reflect the new text.
AI-rewrite a passage of the active script in the project's narrative voice (the same in-editor revise the UI offers). selected_text must appear verbatim in the script; omit it to revise the whole script. Synchronous — returns {revised_text}, which is NOT saved: splice it over selected_text (or replace the full script) and call save_script to keep it.
Switch the project's active script to another saved version (ids come from get_script's version list — every save_script creates one). Re-run scan_script / rescan_voice_blocks afterwards if the text differs, since downstream artifacts follow the active version.
Analyze the active script: extracts character/environment/object assets and splits narration into voice blocks. DESTRUCTIVE on re-run (assets are recreated, not merged — curated descriptions, reference images, and voices are lost; prefer rescan_voice_blocks after script edits). Async — returns {job_id}.
List the project's assets extracted by scan_script — characters, environments, objects. Each has a description (the spec every shot uses to render it — surfaced top-level here; the raw row nests it at ai_output.description), an optional reference image (file_path is a public URL — view_image it), and for characters a voice_id. Review these after scan_script: fix descriptions, then generate_asset_reference for each one (all of them need a reference image before voiceover). asset_type filter: "character" | "environment" | "object".
Manually add a character/environment/object the scan missed. asset_type: "character" | "environment" | "object". The description is the generation-facing spec of its look — be specific.
Rename an asset and/or rewrite its description. If the look changed, regenerate its reference image afterwards so renders match.
Delete a project asset (e.g. one the scan over-extracted).
Render an asset's reference image in the channel's art style — the visual anchor that keeps a character/environment looking identical across every shot. EVERY character, environment, and object asset needs one before generate_voiceover (the server enforces this; fire the jobs for all assets, then one await_jobs). Async — the job writes the image onto the asset row: await_jobs(project_id), then list_assets and view_image the file_path to check likeness.
Bind a TTS voice to a character asset — required before generate_voiceover for every character with dialogue (the narrator's voice is separate: set_narrator_voice). Browse ids with list_voices.
List available TTS voices (id, label, preview audio URL) for a provider: "minimax" (default engine) or "elevenlabs". Match the project's voice_tts_provider (see get_project) so picked ids work with its engine.
Set the project's narrator TTS voice — required before generate_voiceover whenever the script has narration. Browse ids with list_voices. (Character dialogue voices are separate: set_character_voice.)
List the project's voice blocks (per-speaker narration chunks) with their audio status and assigned voices.
Override one voice block's voice or playback volume (block ids from list_voice_blocks). Re-run generate_voiceover for the block afterwards if you changed its voice — existing audio is not regenerated automatically.
Re-extract voice blocks from the active script WITHOUT touching assets or their reference images — the non-destructive alternative to scan_script after a script edit. Existing audio is superseded by the new block split, so re-run generate_voiceover afterwards. Async — returns {job_id}.
Generate TTS audio for the project's voice blocks. Without voice_block_ids it fills gaps: only blocks with no audio yet run, so re-calling it is always safe (already-generated and currently-generating blocks are skipped, never re-billed). Pass voice_block_ids to explicitly REgenerate those blocks (e.g. after changing a block's voice). Speakers must have voices bound first — set_narrator_voice / set_character_voice. Optional editable_sections/settings apply to every selected block (see get_section_template("voice_block") and list_models("voice_block")). Async — returns one job per block.
Plan the full visual storyboard: segments, shot pacing, image/video prompts, overlays, continuation chains — driven by the channel's director and art styles. Requires voiceover to exist (timing comes from it). BEFORE calling: confirm the project's asset_mix with your user (image vs video vs generated_graphic percentages, update_project) — the storyboard plans against it and video-heavy mixes multiply the later render cost. Async — returns {job_id}; this is the longest LLM step.
List the storyboard's segments (narration span, type, duration, creative direction). The 1-based segment_number is the handle every segment tool takes (update/split/combine/continuation/regenerate) — you never need a UUID. Each segment also reports `continues_from_segment`. When set, this shot is a CONTINUATION of that earlier segment: its rendered frame carries over (same composition, characters, and setting) and only the delta changes — an added overlay, a shifted expression, a closer angle, a slow reframe. Null means a fresh, independent shot. The storyboard plans these chains automatically; adjust them with set_segment_continuation.
List one segment's assets (images/video/overlays) including their status, config (prompts, model), and public URLs of rendered files — pass an image's public_url to view_image to actually look at it.
Regenerate a segment's primary image or video with optional overrides — the API equivalent of the editor's expert drawer. asset_type: "image" | "video" (for a video segment, "image" targets its start frame). Use a different model, override prompt sections (see get_section_template("segment_image")), or tweak settings (e.g. image quality), then re-run just this asset. Async — returns {job_id}.
Change a segment's visual type: "image" | "video" | "overlay_scene". carry_frame=true reuses the already-rendered image as the video start frame (or vice versa) instead of recreating it.
Rewrite one segment's creative direction from feedback ("make this shot a close-up", "show the machine from above") — an LLM rewrites the shot's prompts; continuation links, SFX, and overlays are preserved. The visual assets reset to not_started: re-render them afterwards (generate_segments or regenerate_segment_asset). For a precise prompt tweak with no rewrite, use regenerate_segment_asset with editable_sections instead.
Split a segment at the given time offsets (ms, 1-3 cuts → 2-4 parts). inherit_index picks which resulting part keeps the original creative data. Later segments renumber — re-check get_segments before further edits.
Merge a segment with an adjacent one (segment numbers must be neighbors). keep: "this" | "other" — whose creative data survives. Later segments renumber — re-check get_segments before further edits.
Make a segment's image render as a continuation of an EARLIER segment's frame (same composition evolving — the storyboard's continues_from_segment, settable after the fact). continues_from is that earlier segment's number; pass 0 to clear the link. Regenerate the segment's image afterwards — the reference is applied at generation time.
Attach a sound effect from the audio library to a segment (find track ids via browse_audio_library with category="sfx"). Re-run build_scenes to get it onto the timeline.
Remove a sound effect from a segment. With one SFX attached, no name needed; with several, pass sfx_name (the asset name shown by get_segment_assets).
Render every actionable segment asset (images, video clips, overlays) across the project, in dependency order. THE most expensive call in the pipeline: ALWAYS dry_run=true first, show your user the estimate next to get_credit_balance, and wait for a fresh yes before the real run — prior blanket permission ("do the whole thing") does not cover this spend. Pass segment_numbers to render only a subset — e.g. segments 1-18 for the opening minute before committing to the full video. Safe to re-run: completed and currently-generating assets are skipped, so a second call only picks up new/failed work. Async — one job per asset; await_jobs until all complete.
Compile segments + assets + voiceover into the editor/render timeline (scenes). Run after segment assets are complete, before export.
List the project's scenes (composition layers, durations, layout).
Edit ONE scene with a natural-language note (the same director chat the editor UI uses): move/restyle/add/remove layers and overlays, retime, etc. Synchronous — returns the applied mutations + updated scene. Use list_scenes to find scene ids; for notes spanning the whole video use project_director_note instead.
Apply a project-WIDE director note ("make the intro punchier", "all captions bigger", "tighten pacing in the back half"). A routing pass picks only the scenes the note applies to and edits each one. Synchronous — a few seconds per affected scene. Returns the per-scene results; re-run export_video afterwards to see changes in the final render.
Render the final MP4 (Remotion). Fetches the current timeline and queues the render. Async — poll get_workflow_status for the video_export job, then call get_video_url.
Download URL for the most recent completed export.
List the channel's style rows (variable groups). Styles hold the art_style / narrative_style / director_style / script_prompt fields that drive every generation step, plus any custom @variables.
Fetch one style row — its inputs (reference material) and analyzed fields (art_style, narrative_style, director_style, script_prompt, ...). Show fields to the user for review; fine-tune with update_style_fields.
Hand-edit a style's analyzed fields after reviewing them — e.g. tighten the art_style wording or adjust the director_style pacing rules. `fields` is the FULL flat dict to write: {key: {"value": str, "applies_to": [...]}} (fetch with get_style, modify, send back). Editing fields does NOT trigger re-analysis, so your edits stick.
The curated preset catalog for the no-AI style creation path, grouped by axis (art_style / narrative_style / director_style). Show the user the labels + descriptions and let THEM pick one per axis — don't choose silently. Art presets include preview image URLs (view_image works on them). Create with create_style(presets={axis: id, ...}) — instant, no analysis job. Full field text lands on the style row (get_style shows it after creation).
Create a style. Two mutually exclusive paths: References (best): inputs=[{"input_type": "youtube" | "text", "value": "<url or description>"}] — YouTube videos are watched and text directions read; async analysis writes the style's art/narrative/director fields: await_jobs(style_id=...) before using the style. (Image/video FILE references require the multipart REST endpoint POST /styles.) Presets (instant, no analysis): presets={"art_style": id, "narrative_style": id, "director_style": id} — all three axes, ids from list_style_presets.
Re-run style analysis (after changing a style's inputs). Async — await_jobs(style_id=...) until the style_analysis job completes.
Render one of a style's two template images — a REAL step of style setup, not an optional extra: a style isn't finished until both its character and environment templates are rendered (the app shows them on the style card). Asset reference images render against them (characters → character template; environments and objects → environment template), and segment renders fall back on them when a shot has no asset reference — so finish BOTH before generate_asset_reference. Run once per template_type ("character" | "environment") for every new style; skip only types the style already has (get_style shows them). Async — await_jobs(style_id=...), then get_style.
Delete a style (e.g. a failed analysis experiment). Don't delete a style that projects still use as their default — rebind them first with set_project_style.
Register a BYOK provider API key (encrypted at rest, BYOK plan only). Jobs whose model belongs to this provider then run on YOUR key and charge 0 credits. Providers: openai, gemini, anthropic, fal, elevenlabs, minimax.
List registered BYOK providers (masked — only the last 4 characters).
Verify the connection: the account email and plan behind the current credential. Call once after connecting — before creating anything — to confirm you're on the right account; costs nothing.
Current credit balance + plan info. Check before expensive steps (a full segment render can cost hundreds of credits — generate_segments dry_run gives the estimate). Jobs covered by a BYOK provider key bill 0.
Browse the audio library for background music and sound effects. category: "music" | "sfx". Returns track ids for add_music_track / add_segment_sfx.
List the project's background music tracks (volume, loop, timing).
Add background music to the project from the audio library (find track ids with browse_audio_library, category="music"). Defaults loop the track under the whole video at bed level (volume 0.2 ≈ -14 dB under narration — don't raise it without being asked); re-run export_video to hear it.
Tweak a music track. fields keys: name, volume (0-1), loop, start_frame, duration_frames, position, trim_start_frame, trim_end_frame.
Remove a music track from the project.
Fetch a rendered Framesail image so you (and your user) can SEE it — pass a URL from get_segment_assets, get_style, or asset endpoints. Returns the image inline. Only Framesail media URLs are allowed.
概览
What is Framesail AI?
Framesail AI is the official remote MCP server for Framesail. It enables you to create long-form YouTube videos end to end from any MCP client: script, locked character references, storyboard, voiceover, and final MP4, with characters and style held consistent across every shot.
How to use Framesail AI?
Connect via OAuth or an fsk_ API key. For claude.ai / Claude Desktop, add a custom connector pointing to https://api.framesail.com/mcp and approve the browser login. For Claude Code, run claude mcp add --transport http framesail https://api.framesail.com/mcp --header "Authorization: Bearer fsk_...". Other MCP clients similarly set the URL and Authorization header. Create API keys on your Framesail account page.
Key features of Framesail AI
- Full video production pipeline as MCP tools: script, references, storyboard, voiceover, render.
- Streamable HTTP transport with OAuth 2.1 or
fsk_API key authentication. - Supports anonymous
initializeandtools/listfor health checks without an account. - Character and style consistency maintained across every shot.
- Available on Pro and BYOK pricing plans.
Use cases of Framesail AI
- Automate long-form YouTube video creation from an AI coding assistant or chat client.
- Generate a complete video (script to MP4) with a single MCP tool sequence.
- Integrate video production into automated workflows that already use MCP.
FAQ from Framesail AI
What transport does Framesail AI use?
Streamable HTTP.
How do I authenticate?
Either via OAuth 2.1 (Dynamic Client Registration + PKCE) or by using an fsk_ API key passed in the Authorization header.
What plans are required to access the server?
API and MCP access is available on Framesail’s Pro and BYOK plans. See the pricing page for details.
Can I use Framesail AI without an account?
Anonymous initialize and tools/list are supported for directories and health checks. Tool calls require authentication with an account.
Where can I get help or support?
Email [email protected] or join the Discord community.
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