Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Description from the maker (original English)
MCP server for Wan AI video generation
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Pick the AI app you use, then copy the settings.
ACEDATACLOUD_API_TOKENValues marked secret are keys to your account. Never share them or paste them into a chat.
You need
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Works in Claude on the web, desktop and mobile:
https://wan.mcp.acedata.cloud/mcpOpen Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"wan": {
"command": "uvx",
"args": [
"mcp-wan"
],
"env": {
"ACEDATACLOUD_API_TOKEN": "your-value"
}
}
}
}Run this in your terminal
claude mcp add --transport http wan https://wan.mcp.acedata.cloud/mcpclaude mcp add wan --env ACEDATACLOUD_API_TOKEN=your-value -- uvx mcp-wanFill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"wan": {
"url": "https://wan.mcp.acedata.cloud/mcp"
}
}
}Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"wan": {
"command": "uvx",
"args": [
"mcp-wan"
],
"env": {
"ACEDATACLOUD_API_TOKEN": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"wan": {
"type": "http",
"url": "https://wan.mcp.acedata.cloud/mcp"
}
}
}Paste into .vscode/mcp.json in your project
{
"servers": {
"wan": {
"type": "stdio",
"command": "uvx",
"args": [
"mcp-wan"
],
"env": {
"ACEDATACLOUD_API_TOKEN": "your-value"
}
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
ChatGPT connects only to servers on the internet:
https://wan.mcp.acedata.cloud/mcpMenu names can differ slightly by plan and over time.
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These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
The server asks you to sign in before it lists its tools.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026
The registry name was verified with the GitHub account AceDataCloud, which owns the repo
We have not read this repo from GitHub yet
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Responded in 722 ms (HTTP 401)
Declares OAuth sign-in, so your AI app can take you to log in
Not checked yet; we read the tool list when we check the endpoint
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 3 of 3 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
You need to fill in: ACEDATACLOUD_API_TOKEN
Either way works: install it on your computer or connect to the cloud version.
The GitHub repo last changed –, and the latest version (2026.11.1.1) reached the registry 7 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.
In the same category: Figma Context MCP, Claude Real Video, Figma MCP Server
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Let any LLM watch a video locally — and search everything it has ever watched.
Figma’s official server gives AI your design data so it can turn designs into code or describe them accurately. Connects to Figma’s cloud.
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
A Model Context Protocol (MCP) server for AI video generation using Wan through the AceDataCloud API.
Generate AI videos from text or images directly from Claude, VS Code, or any MCP-compatible client.
| Tool | Description |
|---|---|
wan_generate_video | Generate AI video from a text prompt using Wan. |
wan_generate_video_from_image | Generate AI video using a reference image as the starting frame. |
wan_get_task | Query the status and result of a video generation task. |
wan_get_tasks_batch | Query multiple video generation tasks at once. |
wan_list_models | List all available Wan models for video generation. |
wan_list_resolutions | List all available resolution options. |
wan_list_actions | List all available Wan API actions and corresponding tools. |
The hosted endpoint is https://wan.mcp.acedata.cloud/mcp. Choose one route for the MCP client:
| Route | When to use it | Credential setup |
|---|---|---|
| Hosted OAuth | The client supports remote MCP OAuth | Add only the URL, then sign in to AceDataCloud and approve access. No token needs to be pasted into client configuration. |
| Hosted API token | The client cannot finish OAuth, or you need an explicit integration credential | Send an AceDataCloud API token in the Authorization: Bearer … header. Keep it in a local secret store or environment variable. |
| Local stdio | The client runs a local MCP process | Install mcp-wan and pass ACEDATACLOUD_API_TOKEN to that process. It still calls the AceDataCloud API. |
The hosted service advertises OAuth metadata and Dynamic Client Registration (DCR). DCR registers the client application; it is not an API key. OAuth signs you in and the client sends the resulting Bearer token; it may reuse or create an API credential for the account. Browser sign-in still requires an AceDataCloud account. The hosted service can be metered: review current service documentation and displayed pricing before a real operation. Do not configure both an OAuth login and a fixed Authorization header for the same server.
Customize → Connectors → Add custom connector, enter https://wan.mcp.acedata.cloud/mcp, select sign-in, and choose Register automatically if Claude asks how to register its OAuth client. Complete consent. Claude Desktop's local claude_desktop_config.json is a separate setup. Claude connector guide.claude mcp add --transport http --scope user wan https://wan.mcp.acedata.cloud/mcp, then claude mcp login wan. Check /mcp. Claude Code MCP guide.https://wan.mcp.acedata.cloud/mcp. For a project, merge the entry below into /.cursor/mcp.json; for personal use, use ~/.cursor/mcp.json. Cursor MCP guide.https://wan.mcp.acedata.cloud/mcp, then finish the browser sign-in. New portable workspace configs use /.mcp.json; the VS Code-specific format below uses /.vscode/mcp.json or the user profile. Check MCP: List Servers. VS Code MCP setup.codex mcp add wan --url https://wan.mcp.acedata.cloud/mcp, then codex mcp login wan. Its user settings are in ~/.codex/config.toml. Official Codex MCP guide.Cursor project config (OAuth):
{
"mcpServers": { "wan": {"url": "https://wan.mcp.acedata.cloud/mcp"} } }
VS Code-specific workspace config (OAuth):
{
"servers": { "wan": {"type": "http", "url": "https://wan.mcp.acedata.cloud/mcp"} } }
Bearer . An API Key / API Token field expects this raw value; only a manually configured HTTP Authorization header needs the Bearer prefix. A platform-... account-management token cannot replace a generation API key.Save the key in the client's credential store or the environment variable shown below. Never put it in a prompt, shared workflow, screenshot, or Git commit. If authentication fails, check the full copied value, application/service access, expiration, usage limit, and balance before creating another key.
A fixed Bearer header bypasses OAuth. If the header is invalid, remove it before trying browser sign-in; keep the saved credential private.
For Claude Code, the shell expands the token when you add the server; treat the saved user MCP config as a secret:
export ACEDATACLOUD_API_TOKEN='YOUR_API_TOKEN'
claude mcp add --transport http --scope user wan https://wan.mcp.acedata.cloud/mcp \ --header "Authorization: Bearer $ACEDATACLOUD_API_TOKEN"
For a Claude Code project config, put a variable reference in /.mcp.json and set that variable in the environment that launches Claude Code:
{
"mcpServers": { "wan": { "type": "http", "url": "https://wan.mcp.acedata.cloud/mcp", "headers": {"Authorization": "Bearer ${ACEDATACLOUD_API_TOKEN}"} } } }
Cursor uses a different environment-variable syntax in ~/.cursor/mcp.json or an uncommitted project config:
{
"mcpServers": { "wan": { "url": "https://wan.mcp.acedata.cloud/mcp", "headers": {"Authorization": "Bearer ${env:ACEDATACLOUD_API_TOKEN}"} } } }
In VS Code, run MCP: Open User Configuration and merge this server plus its masked input; ${input:...} is for VS Code's user/workspace format and is not portable to the Agent Host .mcp.json format:
{
"inputs": [ {"id": "acedata-wan-token", "type": "promptString", "description": "AceDataCloud API token", "password": true} ], "servers": { "wan": { "type": "http", "url": "https://wan.mcp.acedata.cloud/mcp", "headers": {"Authorization": "Bearer ${input:acedata-wan-token}"} } } }
For Cline, use its MCP configuration UI or CLI file ~/.cline/data/settings/cline_mcp_settings.json; its remote transport value is streamableHttp. For JetBrains AI Assistant, add a remote URL from Settings → Tools → AI Assistant → Model Context Protocol (MCP). For Zed, use a context_servers entry with the URL only for OAuth or add a local Bearer header. These clients have different configuration schemas; follow their current UI rather than copying another client's JSON. Cline · JetBrains · Zed.
Install the package and give the local process an API token:
python -m pip install mcp-wan
export ACEDATACLOUD_API_TOKEN='YOUR_API_TOKEN' mcp-wan
For Claude Desktop local MCP, merge this entry into the file opened by its developer settings (~/Library/Application Support/Claude/claude_desktop_config.json on macOS). uvx requires uv on PATH:
{
"mcpServers": { "wan": { "command": "uvx", "args": ["mcp-wan"], "env": {"ACEDATACLOUD_API_TOKEN": "YOUR_API_TOKEN"} } } }
Keep this user-level file private. Self-hosted HTTP uses mcp-wan --transport http --port 8000; expose it only with suitable network and TLS controls. Local execution still calls the AceDataCloud API.
https://wan.mcp.acedata.cloud/health returning {"status":"ok"} checks endpoint reachability only.wan_list_models is a reference tool; it does not verify downstream API access or balance.wan_generate_video with your own valid input after reviewing current service documentation and displayed pricing. If the result contains a task ID, call wan_get_task on that same ID until terminal success or failure. Do not resubmit the operation just to check progress.For 401, check which auth route the client used and whether the token or OAuth session is valid. A 403 may mean an account permission or content moderation failure; read the returned error. Insufficient balance and downstream service failures need their own diagnosis. A listed tool or submitted task does not prove
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