AI Video Atlas

com.aivideoatlasPublished by aivideoatlas.comOfficial publisherv1.0.0Updated Nov 1, 2026

Plan AI video shots: model picks, sourced prompts, prompting guides and real $/s costs.

VerifiedStreamable HTTPWeb executableMedia & DesignAI & ML

Overview

AI-generated overview

Read-only MCP server that helps an assistant plan AI video shots: sourced prompts, model picks, prompting guides and vendor-stated per-second prices.

What you can do
  • Plan a multi-shot video from a plain description, splitting it into beats with a sourced shot, model, prompt and estimated cost per beat
  • Search a library of sourced AI video shots and pull the full prompt behind a match, with creator credit and source
  • Recommend a video model for a shot with evidence, and look up vendor-stated per-second prices with source and check date
  • Get how-to workflows by job and per-model prompting guidance
  • Diagnose a shot that came out wrong and get specific prompt fixes
  • See the newest shots and guides added in the last N days
When to use it
Useful when someone is writing or debugging prompts for AI video generation, choosing between video models, budgeting a clip, or looking for real prompts other creators published. It is a planning and reference aid, not a generator.
Requirements
A remote streamable HTTP endpoint; no authentication, accounts, keys or environment variables are declared. Works with any MCP client that supports remote servers; some clients require developer mode or a paid plan to add custom connectors. The public instance is rate limited to roughly 60 requests per minute per client.
Before you install
Read-only and keyless, with no generation on the server. Queries are logged anonymously (tool name, truncated query text, argument names, result count, latency, client name) and daily aggregate counts are published, so personal information should not be put in queries. Results carry creator and vendor credits that should be kept when shown.

Installation

In SourceWeft

  1. Open AI Video Atlas in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/com.aivideoatlas%2Fatlas/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config.

{
  "mcpServers": {
    "ai-video-atlas": {
      "type": "http",
      "url": "https://mcp.aivideoatlas.com/mcp"
    }
  }
}

README

AI Video Atlas MCP server

Give your AI agent a video director. This is the open-source MCP server (and REST API) behind AI Video Atlas. It lets Claude, ChatGPT, Cursor, Gemini, Grok Bot or any MCP client plan AI video shots, pick models, find sourced prompts, and price a clip using vendor-stated $/second, all from Atlas data.

  • Live endpoint: https://mcp.aivideoatlas.com/mcp (streamable HTTP, no auth, free)
  • REST API: https://mcp.aivideoatlas.com/v1/<tool>. The OpenAPI spec is at https://mcp.aivideoatlas.com/openapi.json.
  • Agent guide: https://aivideoatlas.com/agents/

It's read-only and deterministic: no AI generation happens on the server, and every answer is built from Atlas's sourced data, with links back to the original creators and vendor pages.

Connect

Claude (web and desktop): open claude.ai → Settings → Connectors, click Add custom connector, name it AI Video Atlas and paste https://mcp.aivideoatlas.com/mcp. No sign-in is needed. On Team and Enterprise plans, an owner may need to add the connector first. Claude Code:

claude mcp add --transport http ai-video-atlas https://mcp.aivideoatlas.com/mcp

ChatGPT: custom MCP connectors need developer mode, a beta for paid plans (Pro, Business, Enterprise, Edu). It isn't available on Free. Open Settings → Apps & Connectors → Advanced settings and turn on Developer mode. Then click Create, name it AI Video Atlas, paste the URL and set authentication to No authentication. Building a custom GPT instead? Go to Configure → Actions → Import from URL and use https://mcp.aivideoatlas.com/openapi.json.

Cursor: use the one-click "Add to Cursor" button on https://aivideoatlas.com/agents/, or add this to ~/.cursor/mcp.json:

json
{"mcpServers":{"ai-video-atlas":{"url":"https://mcp.aivideoatlas.com/mcp"}}}

Gemini: Gemini CLI (free):

gemini mcp add --transport http ai-video-atlas https://mcp.aivideoatlas.com/mcp

In the Gemini app, custom connected apps are limited to Gemini Spark on personal Google accounts in the US (18+). If you have it, add a custom app with the URL above. Gems can't connect to outside tools.

Grok Bot: paste this into your Grok Bot chat:

Add this MCP server: name aivideoatlas, URL https://mcp.aivideoatlas.com/mcp (no key needed).

Grok Bot confirms before adding it, and the tools are available from your next message.

Any MCP client / API: use the URL above (streamable HTTP, no auth). For plain HTTP:

curl "https://mcp.aivideoatlas.com/v1/find_shot?query=drone+shot&limit=3"

VS Code, Windsurf and other MCP clients take the same URL.

Tools

ToolWhat it does
plan_shotsPlan a multi-shot video from a plain description: splits it into beats and picks a sourced shot, model, prompt and estimated cost for each. Deterministic, built only from Atlas data.
find_shotSearch the library of sourced AI video shots (real prompts creators posted, with the model, estimated cost and a link to the original).
best_promptGet the full sourced prompt that best matches a shot, optionally for a target model, with creator credit and source.
recommend_modelRecommend a model for a shot with evidence: how many sourced shots used each model, the cheapest vendor-stated $/s, and an estimated total.
get_pricesVendor-stated $/second prices with source URL and check date. Filter by family or host. Discontinued rows are excluded unless asked for.
get_workflowHow-to workflows, tools and model guides grouped by job (lip-sync, upscaling, character consistency and more).
get_guidePer-model prompting guidance (structure, camera, modes, consistency, audio, what to avoid, limits), sourced from vendor docs plus proven Atlas examples.
whats_newThe newest shots and guides added in the last N days.

The server also exposes MCP resources (for example, atlas://guides/<model>) and server instructions that tell agents when to use each tool.

Rate limits

The public instance is free and keyless. It allows about 60 requests a minute per client (per IPv4 address, or per IPv6 /48), enforced by a Durable Object. A backup edge rule also applies. Over the limit, you get HTTP 429 with retry-after.

Privacy

  • No accounts, keys or cookies.
  • IP addresses are never stored or logged. They're used only in memory to apply the rate limit.
  • Workers invocation logs are off. The only log line is an anonymous atlas_query event: tool name, query text (lowercased and truncated), argument names, result count, latency and client name, if the client sends one. These are used to see which tools and topics are useful.
  • Daily aggregate counts (sessions, tool calls by tool, MCP vs REST, client names) are kept in a Durable Object and published at https://mcp.aivideoatlas.com/stats/daily. Counts only: no IPs, no query text.
  • Don't put personal information in queries.
  • Full policy: https://aivideoatlas.com/privacy/

Run your own copy

npm installnpm run build            # downloads the public data export from https://aivideoatlas.com/agent-data.json and inlines itnpx wrangler dev         # localnpx wrangler deploy      # needs your own Cloudflare account

npm run build writes dist/worker.mjs. To build from a local export instead, run node scripts/build.mjs --data=path/to/agent-data.json, or place it at data/agent-data.json (gitignored).

In wrangler.toml, set account_id (or use CLOUDFLARE_ACCOUNT_ID) and, optionally, your own custom-domain route. The Durable Object binding LIMITER → RateLimiter (SQLite-backed, available on the free plan) is already declared. No secrets are required.

Data and licensing

The code is MIT-licensed (see LICENSE). The data is not in this repo: it's AI Video Atlas's public export, with credit to the original creators and vendor sources linked on every item. Please keep those credits when you show results.

Registry

server.json is the entry for the official MCP Registry (com.aivideoatlas/atlas).

Contact: [email protected]

Source: README.md at commit c2f8b2d

Tools

10

plan_shots

plan shots

Goal: a usable take on the first generation, so fewer paid generations per shot. First review and rewrite the beat list (see brief_review): Atlas parses briefs with rules, so fix non-shots, missing subjects, placeholder lines and generic coverage before writing prompts. If the user names a model or mode, pass it in model/mode (it is kept for every shot unless the docs rule it out). Returns a GUIDANCE PACKAGE, not final prompts: you (the agent) write each full video prompt yourself from it. Per shot: model + mode decision with reasons, the per-model/per-mode prompt structure and tips, 2-3 credited proven example prompts, capabilities/limits/prices with sources, techniques and director rules (practitioner hints at low weight), required assets with image-gen guidance, an 11-section quality checklist, and a starter draft (starting point only, never paste it as-is). If the user names a model or mode, pass it in model/mode (or keep it verbatim in description): Atlas keeps it for every shot unless the vendor docs rule it out, and explains why in user_named. Write each final prompt as flowing, sectioned prose sentences (subject/action, camera/lens/movement, location/light/color, style, audio), never field labels like speaker_id: or Subject:, and without stock filler phrases. Also returns intake (questions to ask the user + stated assumptions) and package_markdown (readable). Plan a multi-shot AI video from a plain description (deterministic, built only from Atlas data; no AI generation). Output is staged: decide (model/mode/clip length/aspect/cost with reasons and capability checks), direct (shot list with per-model prompts), assets (every reference/frame with status needs-generation|user-supplied|approved), image_prompts, and steps, which include a STOP: get the user to approve assets before generating any video. Global directives (same X in every shot, vertical, no text, style) apply to all shots; questions and request wording are never planned as shots; an explicit shot

Parametersmodemodelstyleretriesbudget_usdforce_plandescriptionrequiredclip_secondsmax_per_shot

refine_shot

refine shot

Get to a usable take in as few further generations as possible when a shot came out wrong. Pass the prompt you used, the model, the mode and what went wrong in plain words ("feet sliding", "face drifted", "line cut off", "too glossy", "label morphing"), plus optional frame notes. Returns a diagnosis, specific prompt changes (from Atlas craft fixes and a per-model failure-mode library, credited), a revised prompt, and an escalation ladder: same-model fixes first (prompt, seed/variation, references, duration), then a mode change, then a model switch only as a last resort with the consistency cost stated. Adapt the revised prompt to the user's voice; no generation is run.

Parametersmodeissuerequiredmodelpromptrequiredsecondsframe_urlframe_notes

fix_prompt

fix prompt

Alias of refine_shot. Fix a generated shot that came out wrong. Pass the prompt you used, the model, the mode and what went wrong in plain words ("feet sliding", "face drifted", "line cut off", "too glossy", "label morphing"), plus optional frame notes. Returns a diagnosis, specific prompt changes (from Atlas craft fixes and a per-model failure-mode library, credited), a revised prompt, and an escalation ladder: same-model fixes first (prompt, seed/variation, references, duration), then a mode change, then a model switch only as a last resort with the consistency cost stated. Adapt the revised prompt to the user's voice; no generation is run.

Parametersmodeissuerequiredmodelpromptrequiredsecondsframe_urlframe_notes

find_shot

find shot

Search AI Video Atlas's library of 106 sourced AI video shots (real prompts that creators posted, with the model used, an estimated cost and a link to the original). Use this FIRST when the user describes a shot, scene, style or job ("product ad with a rotating can", "anime fight", "lip sync dialogue", "drone over mountains"). Filters: shot_type (ads, music, shorts, characters, product, cinematic, lipsync, anime), model (e.g. kling, veo, seedance), max_cost_usd (estimated cost of the clip; when the prompt states no length we use a 5-second clip). Returns prompt excerpts; call best_prompt with a slug for the full prompt. Do not use for prices alone (use get_prices) or for tools/workflows (use get_workflow).

Parameterslimitmodelqueryrequiredshot_typemax_cost_usd

best_prompt

best prompt

Get the full, sourced prompt that best matches a shot (free text or a slug from find_shot), optionally for a target model. Returns the exact prompt text as the creator posted it, the creator credit and source, the model it was made with, and factual adaptation notes when the target model differs (other Atlas shots on the target model and its current supported price). Atlas never claims how a prompt will perform on a model it was not made with; treat adaptation notes as guidance.

Parametersshotrequiredmodel

recommend_model

recommend model

Recommend which AI video model to use for a shot, with the evidence: how many sourced Atlas shots of that kind were made with each model, the cheapest supported vendor-stated $/s, and an estimated total for the clip length and number of clips. Pass budget_usd (total) and/or max_per_shot to drop models whose estimate exceeds it; over-budget models are listed with their cost. Each row includes the generation modes the vendor docs confirm (t2v, i2v, reference-to-video, start/end, v2v, lip sync; unknown where docs do not say). Legacy, deprecated and discontinued models are never recommended. Filters by the required mode FIRST (detected from the shot text or the mode argument; endpoints whose docs say unknown are excluded), then ranks the cheapest qualifying endpoint first and notes when a pricier one has more proof. Includes each endpoint's max clip length and splits long clips.

Parametersmodeshotrequiredclipsbudget_usdclip_secondsmax_per_shot

get_prices

get prices

Vendor-stated AI video prices per second from AI Video Atlas's tracker, each with its source URL and the date we checked it. Filter by model family or host. Legacy, deprecated and discontinued rows are excluded unless include_legacy=true (then they are flagged by status). Use for "how much does X cost", "cheapest model", or before quoting any cost.

Parametershostsortmodelinclude_legacy

get_workflow

get workflow

How-to workflows, tools and model guides for AI video, grouped by job: consistent-character (Keep a character consistent), lip-sync (Lip sync & talking heads), product-ad (Product ads & UGC), camera (Direct the camera), long (Longer & multi-shot videos), i2v (Animate a still image), edit (Edit or restyle footage), upscale (Upscale & smooth), local (Run it on your own GPU), models (Models & hosts). Pass job for a curated list, query for free text (e.g. "comfyui lipsync", "upscale to 4k"), or slug for one item in full. Returns sources, creators, license and price as stated.

Parametersjobsluglimitquery

get_guide

get guide

Prompting guidance from AI Video Atlas, sourced from vendor prompting docs (Google, BytePlus, Runway, Luma, MiniMax, Alibaba, LTX, xAI, fal) plus proven Atlas examples. Pass model (kling, veo, seedance, runway, luma, hailuo, wan, ltx, grok-imagine…) for prompt structure, camera language, what the model responds to, things to avoid and known limits; or topic (shot-vocabulary, tagging, consistent-characters, i2v-vs-r2v, setup-playbooks). Every item carries its source URL; items marked atlas-editorial are our summary, not a vendor claim. Call with no arguments to list what exists. Use before writing a prompt for a specific model.

Parameterskindmodeltopic

whats_new

whats new

What is new in AI Video Atlas: the newest sourced shots and guides added in the last N days (default 7), newest first, with X like counts where we have them ("new" otherwise). Use for "what's new in AI video", weekly roundups, or trend questions. For the full weekly digest (new models, price changes, new shots, legacy prices) read https://aivideoatlas.com/digest/latest.json.

Parametersdayskindlimit

Version history

1
  1. v1.0.0LatestOct 11, 2026

Score

100% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 daysRequired25 pts
  • Auth declaredRequired10 pts
  • Tools listedRequired15 pts
  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts