Creatorforge
БесплатноНе проверенMCP server for AI content generation, enabling agents to learn a voice, generate content ideas, write scripts, and produce multi-platform content deterministica
Описание
MCP server for AI content generation, enabling agents to learn a voice, generate content ideas, write scripts, and produce multi-platform content deterministically.
README
The AI content team you own — not one you rent for $15K/month.
Business owner? Creator? Ask yourself:
- Are you paying (or about to pay) five figures a month for a "done-for-you AI content team"?
- Does that team's "proprietary system" run on someone else's servers, with your voice, audience, and data living there?
- When the retainer ends, do you keep anything — or does the system walk out the door with them?
- Do you actually want to film 2–4 hours a week and have everything else handled — without renting the engine that does it?
If you nodded, here's the deal: creatorforge is that content team, as open software you own and run yourself. No retainer. No 50-spots-only. No "proprietary" black box. It's free, COCL (Cognis Open Collaboration License), and runs on your hardware and your model.
Watch the walkthrough
A full narrated tour — setup, the tool in action, and every demo scenario:
Watch the creatorforge walkthrough
What you get
The same deliverables an agency installs — generated from one command:
- Voice profile — it learns your style from your past posts (no model training, nothing uploaded — just measurable style features).
- Niche research brief — content pillars, audience pains, keyword targets.
- Content ideas — a steady pipeline of format × angle ideas so you never face a blank page.
- Hooks — proven scroll-stopping formulas, written in your voice.
- Scripts — full, structured scripts sized to each platform.
- Captions — on-screen overlay text + timed SRT subtitles.
- Thumbnail concepts — headline / visual / emotion / layout, rendered as actual SVG mockups.
- Multi-platform packaging — one idea, tailored for YouTube, Shorts, TikTok, Reels, X, and LinkedIn (each platform's limits respected).
- Posting calendar — your ideas scheduled at your cadence.
You film. creatorforge does the rest.
How it's different (the honest version)
| The agency offer | creatorforge | |
|---|---|---|
| Price | ~$15K/month retainer | free, open source |
| Where it runs | their cloud | your hardware |
| Your voice/data | lives on their system | never leaves your machine |
| When it ends | you keep nothing | you own it forever |
| The "system" | proprietary black box | readable code you can audit |
| Results promised | "1 billion views" | a great engine — the views are on you |
No inflated view-count promises here. creatorforge gives you a genuinely strong content system; what it can't do is guarantee virality, and anyone who guarantees that is selling something. It runs fully offline on a deterministic engine, and gets sharper the moment you point it at a local model (Ollama) or a cloud one — your call.
Quick start
pip install -e .
# 1. Learn your voice from a folder of your past posts/scripts
creatorforge profile ./my_posts/ --out voice.json
# 2. Run the whole team on a topic, across your platforms
creatorforge pipeline --topic "why you should own your AI stack" \
--niche "AI for business" --platforms youtube,tiktok,x,linkedin \
--voice voice.json --start 2026-07-06 --out plan.json
# Or one piece at a time
creatorforge hooks --topic "cold email that converts" --voice voice.json
creatorforge script --topic "cold email that converts" --platform youtube_shorts --voice voice.json
creatorforge thumbnail --topic "cold email that converts" --svg thumb # writes thumb-1.svg …
# Use your own local model to sharpen the prose (nothing leaves your machine)
creatorforge script --topic "..." --provider ollama --model llama3
Run python demo.py to watch it learn a voice and generate a full multi-platform plan end to end.
Platforms
| Platform | Aspect | Sweet spot | Tailored output |
|---|---|---|---|
| YouTube | 16:9 | ~10 min | title + description + script |
| YouTube Shorts | 9:16 | ≤60 s | short script + captions |
| TikTok | 9:16 | ~27 s | caption + hashtags + script |
| Reels | 9:16 | ~60 s | caption + hashtags + script |
| X | 16:9 | — | ≤280-char post |
| 1:1 | ~90 s | long-form post |
Local models — every modality, on your hardware
creatorforge drives the best open-source, local, free model your machine can run, in every modality — and degrades cleanly when you don't have the big one. Ask it what it can do:
creatorforge capabilities
| Modality | What it does | Open model (GPU) | Runs with no GPU |
|---|---|---|---|
| Text | hooks, scripts, ideas in your voice | any Ollama model (auto-picks your best) | ✅ via Ollama / template engine |
| Transcription | footage → text → repurposed posts | faster-whisper large-v3 |
✅ base/small on CPU |
| Voice | voiceover + voice cloning | XTTS-v2 (clone) | ✅ Piper (CPU) |
| Image | photorealistic thumbnails | FLUX.1-schnell / SDXL-Turbo / SD 1.5 | ✅ real raster PNG (PIL) → SVG |
| Video | finished short, captions timed | LTX-Video / CogVideoX (text-to-video) | ✅ assembled MP4 (ffmpeg) / animated GIF |
| Audio | voiceover + music, leveled | MusicGen beds | ✅ ffmpeg mix / stdlib WAV |
The recommended model in each row is chosen to fit your VRAM (recommend() ladders from a 24 GB GPU down to CPU). Photorealistic images, cloned voices, MP4s, and generated b-roll need the model/tool installed — but there's always a real, local fallback so nothing hard-fails: a composited raster thumbnail, an animated GIF, a synthesized WAV. Nothing is ever sent to a cloud API.
# transcribe footage with local Whisper
creatorforge transcribe talk.mp4
# generate a thumbnail (diffusion if you have it, else a real raster PNG)
creatorforge image --topic "owning your AI stack" --voice voice.json --out thumb
# produce a finished short from a script (MP4 with ffmpeg, else animated video)
creatorforge video --topic "owning your AI stack" --platform youtube_shorts --out short
# voiceover (Piper, or clone your voice with XTTS) and an audio track
creatorforge voiceover --from-script script.json --out vo.wav --speaker my_voice.wav
creatorforge audio --voiceover vo.wav --music bed.mp3 --out track
# the whole production in one command: plan + thumbnail + video + audio + outbox
creatorforge produce --topic "owning your AI stack" --niche "AI for business" \
--provider ollama --out ./production/
Long-form & cinematic production (5–15 min)
Short clips are one mode. creatorforge also plans and assembles long-form video — documentaries, video essays, dev logs, promos — structured the way the industry actually does it. It fuses four things:
- a format (
creatorforge formats) — the proven beat order for documentary / video-essay / devlog / promo - a cinematic style (
creatorforge styles) — pacing, shot vocabulary, color, and music mood drawn from the grammar of prestige docs, kinetic vlogs, trailer-cut blockbusters, slow-burn arthouse, true-crime, and more - the algorithm playbook — what each platform actually rewards (watch time / AVD, completion rate, the first-30s hook, re-hooks every ~40s, chapters) turned into concrete production directives
- your voice (+ an optional local model to polish the narration)
…into a full plan: acts → scenes → timed shots → narration → chapters → a music & SFX cue sheet → titles and thumbnails, sized to your target runtime.
creatorforge formats # documentary, video_essay, devlog, promotional
creatorforge styles # epic_doc, true_crime, kinetic_vlog, blockbuster, arthouse_slowburn, …
creatorforge longform --topic "owning your AI stack" --format documentary --style epic_doc --minutes 12 --out plan.json
creatorforge studio --topic "owning your AI stack" --format documentary --minutes 10 --provider ollama --out ./film/
Generative music and sound effects come from local open models (MusicGen / AudioGen) when your GPU can run them, with a synthesized bed as a fallback so a cut always has a track.
On "Netflix-level": creatorforge plans and directs at that structural level — story structure, shot lists, pacing, sound design, retention engineering — and assembles the cut with whatever render models you have. Cinema-grade footage and audio come from the heavy open models (FLUX / LTX-Video / MusicGen / XTTS) on a capable GPU, which the engine drives; on a laptop you still get a complete, correctly-structured cut with real generated assets. The structure is studio-grade everywhere; the render fidelity scales with your hardware.
Punch above your weight class: real photos, designed
You don't beat a giant cloud image model on a laptop by out-rendering it — you out-source and out-design it. creatorforge pulls real, no-watermark photography and composites it into pro visuals, which reads as more professional than weak CPU diffusion ever will.
- Your own library, offline. Index image folders you already have and search them by keyword — multiple related shots per scene, your images, zero watermarks, zero licensing questions. Optionally caption them with local
llavafor smarter matching. - Free, no-key, no-watermark CC stock. Openverse / Wikimedia Commons, each result carrying its license + attribution so you stay compliant. Watermarked sources (Getty/Shutterstock previews) are never queried.
- Designed, not dumped. A sourced hero photo gets cover-cropped, color-graded, given a legibility scrim, and set with a bold headline — a real editor's thumbnail.
# build an offline, searchable index of your image folders (your own = no watermark)
creatorforge assets index ~/Pictures ~/b-roll --out assets.json
# pull multiple related, key shots for a scene
creatorforge assets search "datacenter server racks" --index assets.json -k 6
creatorforge assets search "founder at laptop" --index assets.json --online # + free CC stock
# build a thumbnail composited over a real sourced photo
creatorforge image --topic "owning your AI stack" --assets assets.json --out thumb
# studio/produce auto-source a hero from your library:
creatorforge studio --topic "..." --format documentary --assets assets.json --out ./film/
Licensing, honestly: your own library is yours. Openverse/Wikimedia results are Creative Commons / public-domain and may require attribution — creatorforge surfaces the license and attribution string with every result so you can credit correctly. It never pulls watermarked or paid-preview imagery.
Direction & engagement craft (multi-cam, cool shots, retention)
Long-form plans don't just have scenes — they have coverage and engagement built in:
- Multi-camera shot generation. Every beat gets a shot list across A/B/C/detail/drone/POV cameras with motivated camera moves — dolly-in, push-in, crane, gimbal track, drone reveal, dolly-zoom (vertigo), orbit, speed-ramp — and the showy "cool shots" land where they matter (cold opens, turns, climaxes). The plan tells you exactly which cameras a production needs.
- Engagement craft, encoded. Each beat carries a retention move drawn from two lineages: great-filmmaker grammar (in-media-res, but/therefore causality, show-don't-tell, escalating stakes, tension-release, match cuts, the Kuleshov effect) and modern retention tactics (front-load the payoff, escalate every segment, reset the hook on a cadence, concrete stakes/numbers, no dead air, tease what's coming, emotional payoff). Structure isn't just correct — it's sticky.
It's all in the longform/studio plan: scenes[].shots (cams + moves), scenes[].retention_move, multicam, and engagement_plan.
Make content for your repos — and grow like the AI companies that made it
Point creatorforge at a repository and it writes the content for it; point it at an owner and it does the whole catalog.
# one repo -> multi-platform content (reads the README, derives what it is)
creatorforge repo ./codegraph-mcp --format promotional --out plan.json
creatorforge repo cognis-digital/agentledger --longform --format documentary # via gh
# every repo of an owner, batched
creatorforge repos --owner cognis-digital --format promotional --out ./repo_content/
# a 30-day launch strategy that mirrors how the big AI companies actually grew
creatorforge growth ./codegraph-mcp
The growth playbook encodes the plays that repeatedly worked for the AI companies that broke out — a runnable demo over a pitch deck, building in public, a benchmark moment, developer-first distribution, founder-led content, free/open core, naming the category — and turns them into a concrete day-by-day launch calendar for your project. The edge was never the secret; it's executing these consistently, which is exactly what the engine makes cheap.
Wire it into your stack (MCP)
creatorforge ships an MCP server, so Claude, an internal orchestrator, or any MCP-capable agent can drive it directly:
creatorforge serve # JSON-RPC over stdio
Tools: profile_voice, generate_ideas, write_hooks, write_script, thumbnail_concepts, package_for_platform, run_pipeline. Hand the packaged posts to your scheduler/poster of choice and the loop is closed.
The pipeline
flowchart LR
posts[Your past posts] --> voice[VoiceProfile]
topic[Topic + niche] --> pipe{{run_pipeline}}
voice --> pipe
prov[Provider<br/>Template / Ollama] -.optional polish.-> pipe
pipe --> ideas[ideas]
pipe --> hooks[hooks]
pipe --> script[script] --> caps[captions + SRT]
pipe --> thumbs[thumbnails + SVG]
pipe --> pkg[per-platform packages]
ideas --> cal[calendar]
pkg --> out[(Multi-platform deliverable)]
caps --> out
thumbs --> out
cal --> out
topic --> lf[[longform.build_longform]] --> studio[(Cinematic plan:<br/>scenes · shots · cues)]
voice --> lf
classDef hot stroke:#8b5cf6,stroke-width:3px;
class pipe,lf hot;
See docs/ARCHITECTURE.md for the full walkthrough.
Demos
Five runnable scenarios in demos/, each for a different audience. Every one runs fully offline — no network, GPU, or model download — on the deterministic engine, so they double as smoke tests. Details in docs/DEMOS.md.
# cp1252 consoles (Windows): PYTHONUTF8=1 makes the emoji output render
PYTHONUTF8=1 python demos/run_all.py # all five, end to end
PYTHONUTF8=1 python demos/02_agency_full_pipeline.py # or just one
| # | Scenario | Audience | What it shows |
|---|---|---|---|
| 1 | 01_creator_voice_to_post.py |
Solo creators | Learn a voice from past posts, then write hooks, a script, overlays, and SRT in that voice. |
| 2 | 02_agency_full_pipeline.py |
Business owners | The whole agency bundle from one run_pipeline call — brief, ideas, hooks, script, captions, packages, calendar. |
| 3 | 03_devrel_repo_launch.py |
DevRel & marketing | Point it at a repo (reads the README), get multi-platform content + a 30-day launch calendar. |
| 4 | 04_multiplatform_repurpose.py |
Multi-platform publishers | One idea packaged for all six channels with every limit honored, plus the algorithm playbook. |
| 5 | 05_longform_studio.py |
Long-form showrunners | A 12-minute documentary plan: scenes, multi-cam shot lists, retention moves, chapters, titles. |
Testing
pip install -e ".[dev]"
pytest -q # 49 tests
License
COCL (Cognis Open Collaboration License). © Cognis Digital. The whole engine is open — read it, fork it, run it on your own models. You own your content team.
Status: v0.1 — runnable and tested. Short-form + long-form (5–15 min) production; text, transcription, voice, image, video, music/SFX backends wired with hardware-aware selection and CPU fallbacks; format/style/algorithm intelligence baked in. Roadmap: ComfyUI image/video backend, true text-to-video assembly, A/B title scoring, scheduled auto-publish.
Установка Creatorforge
У этого сервера нет опубликованного пакета — он собирается из исходников. Открой репозиторий и следуй инструкции в README.
▸ github.com/cognis-digital/creatorforgeFAQ
Creatorforge MCP бесплатный?
Да, Creatorforge MCP бесплатный — установка в пару кликов через Unyly без оплаты.
Нужен ли API-ключ для Creatorforge?
Нет, Creatorforge работает без API-ключей и переменных окружения.
Creatorforge — hosted или self-hosted?
Self-hosted: сервер запускается локально на твоей машине командой из раздела установки.
Как установить Creatorforge в Claude Desktop, Claude Code или Cursor?
Открой Creatorforge на unyly.org, выбери вкладку своего клиента (Claude Desktop, Claude Code, Cursor) и нажми Install — конфиг сгенерируется автоматически, без правки JSON.
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