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)
Transcode/conform/splice video, convert docs, transcribe audio for AI agents. Free $1 trial.
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
BOTVERSE_API_KEY, BOTVERSE_CONNECTOR_URLValues marked secret are keys to your account. Never share them or paste them into a chat.
You need
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Pick your app above. We remember it, so next time the button says “Install in …”.
Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"botverse": {
"command": "npx",
"args": [
"-y",
"botverse-mcp"
],
"env": {
"BOTVERSE_API_KEY": "your-value",
"BOTVERSE_CONNECTOR_URL": "your-value"
}
}
}
}Run this in your terminal
claude mcp add botverse --env BOTVERSE_API_KEY=your-value --env BOTVERSE_CONNECTOR_URL=your-value -- npx -y botverse-mcpFill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"botverse": {
"command": "npx",
"args": [
"-y",
"botverse-mcp"
],
"env": {
"BOTVERSE_API_KEY": "your-value",
"BOTVERSE_CONNECTOR_URL": "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": {
"botverse": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"botverse-mcp"
],
"env": {
"BOTVERSE_API_KEY": "your-value",
"BOTVERSE_CONNECTOR_URL": "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.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
Your choice stays on this device in a cookie; no account needed.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
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 6, 2026
The registry name was verified with the GitHub account MkTurner74, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 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: BOTVERSE_API_KEY, BOTVERSE_CONNECTOR_URL
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (1.5.1) reached the registry 2 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
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.
MCP server and command-line tool for Botverse — video transcoding and document conversion for AI agents and the humans who configure them.
Two ways to use it: an MCP server for your AI agents, and a `botverse` CLI for the shell — evaluation, CI/CD, cron, scripts, and local coding agents. No AWS. No FFmpeg. No infrastructure.
{
"mcpServers": { "botverse": { "command": "npx", "args": ["-y", "botverse-mcp"], "env": { "BOTVERSE_API_KEY": "bv_live_..." } } } }
Or with a connector URL (recommended for claude.ai):
{
"mcpServers": { "botverse": { "command": "npx", "args": ["-y", "botverse-mcp"], "env": { "BOTVERSE_CONNECTOR_URL": "https://botverse.cloud/mcp?token=bv_sess_..." } } } }
botverse)The same package ships a botverse CLI for the shell — it reads files from disk and streams them straight to the API (no content goes through an LLM), so it's the fast path for evaluation, automation, and local coding agents.
export BOTVERSE_API_KEY=bv_live_… # or BOTVERSE_CONNECTOR_URL=…?token=bv_sess_…
npx botverse convert report.md --to pdf npx botverse convert *.md --to docx,pdf -o ./out npx botverse transcode clip.mov --to mp4 -o ./out npx botverse transcribe call.mp4 --to docx --attendees "Sarah Chen,Mike Torres" npx botverse conform video.mp4 audio.wav --to mp4 --method speed_conform --target-framerate 25 npx botverse balance
Each job uploads → polls → downloads the finished file to -o (default: current dir). Globs and multiple --to formats run as a batch.
Sandbox note: the CLI needs outbound network to
botverse.cloudand Botverse's file storage host, so it does
not run inside sandboxed agent environments (claude.ai / Claude Desktop), whose
egress is allowlisted. There, use the MCP tools (e.g.
convert_content) instead.
| Tool | Description |
|---|---|
get_upload_url | Get a presigned URL to upload a file for use with the _media/_file/_video (object-key-based) tools |
transcode_from_url | Transcode video from a public URL |
transcode_video | Transcode an uploaded video file |
conform_from_url | Mux a separate video + audio source (public URLs) into one output |
conform_media | Mux an uploaded video + audio source into one output |
conform_splice_from_url | Concatenate video/image segments (public URLs) — slates, bumpers, end cards, inserts, joined clips |
conform_splice_media | Concatenate uploaded video/image segments — same use cases |
convert_content | Convert document content inline (up to 4 MB; sandbox-safe) |
convert_from_url | Convert a document from a public URL |
convert_file | Convert an uploaded document |
submit_workflow | Submit a multi-step BWDL workflow chaining several of the above tools together, with dependency ordering and parallel branches |
get_workflow_status | Poll a workflow (and its per-step status) until it reaches a terminal state |
cancel_workflow | Cancel an in-progress workflow; already-completed steps are billed, the rest are not |
get_job_status | Poll a job until complete |
get_download_url | Get the signed download URL |
get_wallet_balance | Check wallet balance |
submit_workflow chains multiple Botverse tools (transcode, convert, transcribe, conform, splice) into one server-side job — e.g. transcribe → clip extraction → delivery — instead of your agent making each call and polling each one individually.
workflow_id and a steps array. Each step has an id, a tool (any MCP tool name), an inputs object, and an optional depends_on array of prior step ids.depends_on run in parallel."$.steps. .output_key", and a workflow-level parameter with "$.params. " — no other template syntax is supported.submit_workflow, poll with get_workflow_status every 5–10 seconds until the status is COMPLETED, FAILED, PARTIALLY_FAILED, or CANCELLED, and stop early with cancel_workflow if needed (you're only billed for steps that already completed).Example — a two-step conversion chain (URL → DOCX → PDF):
{
"workflow_id": "md-to-pdf-via-docx", "steps": [ { "id": "to_docx", "tool": "convert_from_url", "inputs": { "source_url": "https://example.com/report.md", "output_format": "docx" } }, { "id": "to_pdf", "tool": "convert_file", "depends_on": ["to_docx"], "inputs": { "object_key": "$.steps.to_docx.output_key", "output_format": "pdf" } } ] }
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