Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
Descripción del creador (original en inglés)
Local MCP server: recordings or public video URLs into transcript, frames, OCR, wall-clock evidence.
Estos tres nunca se combinan en una sola puntuación: las opiniones, las mediciones y la popularidad son cosas distintas.
Todavía no escribimos un resumen sencillo para este. Abajo están los datos que leímos del registro.
Elige la app de IA que usas y copia la configuración.
TALKTHROUGH_WHISPER_MODEL, TALKTHROUGH_OCR, TALKTHROUGH_OCR_LANG, TALKTHROUGH_HOME, TALKTHROUGH_MAX_DOWNLOAD_BYTESNecesitas
¿Qué app usas?
Elige tu app arriba. La recordamos, así que la próxima vez el botón dirá “Instalar en …”.
Abre Claude Desktop → Settings → Developer → Edit Config y pega esto en claude_desktop_config.json
{
"mcpServers": {
"talkthrough": {
"command": "uvx",
"args": [
"talkthrough-mcp"
],
"env": {
"TALKTHROUGH_WHISPER_MODEL": "your-value",
"TALKTHROUGH_OCR": "your-value",
"TALKTHROUGH_OCR_LANG": "your-value",
"TALKTHROUGH_HOME": "your-value",
"TALKTHROUGH_MAX_DOWNLOAD_BYTES": "your-value"
}
}
}
}Ejecuta esto en tu terminal
claude mcp add talkthrough --env TALKTHROUGH_WHISPER_MODEL=your-value --env TALKTHROUGH_OCR=your-value --env TALKTHROUGH_OCR_LANG=your-value --env TALKTHROUGH_HOME=your-value --env TALKTHROUGH_MAX_DOWNLOAD_BYTES=your-value -- uvx talkthrough-mcpCompleta los valores vacíos antes de ejecutarlo.
Pégalo en .cursor/mcp.json de tu proyecto, o en ~/.cursor/mcp.json
{
"mcpServers": {
"talkthrough": {
"command": "uvx",
"args": [
"talkthrough-mcp"
],
"env": {
"TALKTHROUGH_WHISPER_MODEL": "your-value",
"TALKTHROUGH_OCR": "your-value",
"TALKTHROUGH_OCR_LANG": "your-value",
"TALKTHROUGH_HOME": "your-value",
"TALKTHROUGH_MAX_DOWNLOAD_BYTES": "your-value"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Pégalo en .vscode/mcp.json de tu proyecto
{
"servers": {
"talkthrough": {
"type": "stdio",
"command": "uvx",
"args": [
"talkthrough-mcp"
],
"env": {
"TALKTHROUGH_WHISPER_MODEL": "your-value",
"TALKTHROUGH_OCR": "your-value",
"TALKTHROUGH_OCR_LANG": "your-value",
"TALKTHROUGH_HOME": "your-value",
"TALKTHROUGH_MAX_DOWNLOAD_BYTES": "your-value"
}
}
}
}Tu navegador te pide permiso para abrir la app; luego la app muestra la configuración y te pide confirmar. Los valores de las claves quedan vacíos para que los completes tú.
Este se ejecuta en tu computadora, y ChatGPT solo puede conectarse a servidores en internet. Elige otra app.
Tu elección se guarda en una cookie en este dispositivo; no necesitas cuenta.
TALKTHROUGH_WHISPER_MODEL envTALKTHROUGH_OCR envTALKTHROUGH_OCR_LANG envTALKTHROUGH_HOME envTALKTHROUGH_MAX_DOWNLOAD_BYTES envEsta configuración se genera a partir de la ficha del creador en el registro. Si el README dice otra cosa, sigue el README.
Se ejecuta en tu computadora; la lista de herramientas aparece en tu app de IA después de instalarlo.
Revisamos información que cualquiera puede ver; no hemos leído el código. Las revisiones que no aplican no se cuentan. · Revisado el 8 nov 2026
El nombre en el registro se verificó con la cuenta de GitHub korovin-aa97, dueña del repo
Todavía no hemos leído este repo en GitHub
Todavía no hemos leído este repo en GitHub
Este se ejecuta en tu computadora; no hay endpoint en internet
Se ejecuta en tu computadora y usa ajustes locales en su lugar
Se ejecuta en tu computadora; solo podemos leer listas de herramientas de endpoints en internet
Comparado con todos los servidores activos de esta categoría en el registro. Las estrellas solo cuentan cuando quien lo publica es dueño del repo.
Superó 1 de 1 revisiones básicas aplicables. No hemos leído el código. Antes de agregar una clave o un token, revisa qué acceso pide el servidor y usa una clave que tenga solo los permisos que necesitas.
El registro no indica ninguna clave obligatoria, aunque algunos servidores te piden iniciar sesión la primera vez que los usas.
Se ejecuta en tu computadora. Tu app de IA lo inicia cuando hace falta, y los datos no pasan por los servidores del creador (a menos que el propio servidor llame a un servicio en línea).
El repo de GitHub cambió por última vez –, y la última versión (0.4.4) llegó al registro hace 15 días.
Las apps compatibles con MCP, como Claude Desktop, Claude Code, Cursor y VS Code. También necesitas Python (uv) en tu computadora.
En la misma categoría: Figma Context MCP, Claude Real Video, Figma MCP Server
Servidores de la misma categoría hechos por otros creadores, ordenados por estrellas.
Cómo leer una tarjeta:★ Estrellas de GitHubiTres pilares: reseñas · revisiones · usoiActualizado = fecha en que se publicó la última versión en el registroi
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.
The Figma MCP server brings Figma design context directly into your AI workflow.
Copiado tal cual del repo del creador. PopNx MCP no lo ha revisado ni lo respalda. Se quitaron HTML, imágenes y scripts. Los enlaces llevan fuera de este sitio.
Quickstart · Tools · Benchmarks · FAQ · Troubleshooting · Changelog · Contributing
Give Claude Code or Codex a narrated .mov/.mp4 — or a public video link — and talkthrough turns it into searchable transcript, exact frames, OCR and wall-clock timestamps, locally — so your agent writes an evidence-backed issue draft or investigates the fix.
Also works for meetings, workshops, product demos, and production incidents.
*Illustration — an animation of the /talkthrough:bug storyline, not a screen capture: the recording is indexed locally (transcript · keyframes · OCR · wall-clock), the evidence checkpoint is assembled, and the draft is ready to file with your own tracker tooling (gh, Jira, a GitHub MCP server — talkthrough itself never leaves your machine and never posts anything).*
Real runs, no animation:
bug-report.md comes out..mp4 and the unedited agent output. Every number is reproducible — processing that file gives job_id 8703a66bbe77a7d0 (the job id *is* the sha256 prefix, so shasum -a 256 predicts it), 17 keyframes / 4 unique, and 0 transcript segments because there is no audio track.One command, no system dependencies: ffmpeg falls back to a bundled build, OCR is pip-only, and whisper models download themselves on first use. The only prerequisite is uv (brew install uv or curl -LsSf https://astral.sh/uv/install.sh | sh).
Cold setup has two separate stages: uvx first resolves a compatible Python and the pinned server environment, then the first process_media downloads any missing media/model assets. A plugin update can create a new environment and, without system ffmpeg, fetch the ~80 MB bundled ffmpeg again; shared Whisper/OCR/diarization caches and warm, network-free jobs remain reusable. See Troubleshooting.
Two install paths — pick one, not both (the plugin already includes the server; installing both would register it twice):
Server only — the 9 tools + 6 prompts, and nothing else on your system. Choose this for a minimal setup, or when you manage MCP servers yourself across several clients:
claude mcp add -s user talkthrough -- uvx --python ">=3.11,<3.14" "talkthrough-mcp[diarization,url]"
Full plugin — the same server, plus native slash commands (/talkthrough:bug, /talkthrough:triage-recording, …) that handle the ceremony for you, a ready-made triage subagent, and an agent skill that teaches Claude the workflow. Choose this for the best out-of-the-box experience:
/plugin marketplace add korovin-aa97/talkthrough-mcp
/plugin install talkthrough@talkthrough
Claude Desktop
claude_desktop_config.json:
{
"mcpServers": { "talkthrough": { "command": "uvx", "args": [ "--python", ">=3.11,<3.14", "talkthrough-mcp[diarization,url]" ] } } }
More: integrations/claude-desktop/
Cursor
~/.cursor/mcp.json (or project .cursor/mcp.json):
{
"mcpServers": { "talkthrough": { "command": "uvx", "args": [ "--python", ">=3.11,<3.14", "talkthrough-mcp[diarization,url]" ] } } }
More: integrations/cursor/
OpenAI Codex CLI
~/.codex/config.toml (or project-scoped .codex/config.toml in trusted projects):
[mcp_servers.talkthrough]
command = "uvx" args = ["--python", ">=3.11,<3.14", "talkthrough-mcp[diarization,url]"]
More: integrations/codex/
Gemini CLI
~/.gemini/settings.json:
{
"mcpServers": { "talkthrough": { "command": "uvx", "args": [ "--python", ">=3.11,<3.14", "talkthrough-mcp[diarization,url]" ] } } }
More: integrations/gemini-cli/
Cline / Roo Code
cline_mcp_settings.json (via MCP Servers UI):
{
"mcpServers": { "talkthrough": { "command": "uvx", "args": [ "--python", ">=3.11,<3.14", "talkthrough-mcp[diarization,url]" ] } } }
More: integrations/cline/
OpenClaw
~/.openclaw/openclaw.json:
{
"mcp": { "servers": { "talkthrough": { "command": "uvx", "args": [ "--python", ">=3.11,<3.14", "talkthrough-mcp[diarization,url]" ] } } } }
More: integrations/openclaw/
OpenCode
opencode.json (project) or ~/.config/opencode/opencode.json:
{
"mcp": { "talkthrough": { "type": "local", "command": [ "uvx", "--python", ">=3.11,<3.14", "talkthrough-mcp[diarization,url]" ], "enabled": true } } }
More: integrations/opencode/
Goose
~/.config/goose/config.yaml:
extensions:
talkthrough: enabled: true type: stdio cmd: uvx args: ["--python", ">=3.11,<3.14", "talkthrough-mcp[diarization,url]"]
More: integrations/goose/
GitHub Copilot CLI
~/.copilot/mcp-config.json:
{
"mcpServers": { "talkthrough": { "command": "uvx", "args": [ "--python", ">=3.11,<3.14", "talkthrough-mcp[diarization,url]" ] } } }
More: integrations/copilot-cli/
Windsurf
~/.codeium/windsurf/mcp_config.json:
{
"mcpServers": { "talkthrough": { "command": "uvx", "args": [ "--python", ">=3.11,<3.14", "talkthrough-mcp[diarization,url]" ] } } }
More: integrations/windsurf/
Zed
settings.json (Zed):
{
"context_servers": { "talkthrough": { "source": "custom", "command": { "path": "uvx", "args": [ "--python", ">=3.11,<3.14", "talkthrough-mcp[diarization,url]" ] } } } }
More: integrations/zed/
Any other MCP stdio client uses the same server command: uvx --python ">=3.11,<3.14" "talkthrough-mcp[diarization,url]". Per-engine folders with exactly these snippets plus verification steps live in integrations/; agents can self-install via llms-install.md.
Multi-person recordings (meetings, interviews, panels) can carry S1/S2/… speaker labels. Every install button, snippet, and the plugin above already ship the [diarization] engine, so asking your agent "who said what" just works — diarization itself still runs only when requested per call (process_media(path=..., diarize=true, num_speakers= )), and its models download once on first use.
Prefer the minimal server without the diarization engine? Use uvx --python ">=3.11,<3.14" talkthrough-mcp as the command instead (the MCP registry entry also resolves to this lean form) — an explicit diarize=true will then answer with the one-line install fix. Details in Speakers.
Update your plugin or generated config, then warm its exact pinned launcher before reconnecting the MCP client:
uvx --python ">=3.11,<3.14" "talkthrough-mcp[diarization,url]==0.4.4" --version
The output should name 0.4.4 and both extras. This prepares dependencies; the first recording can still need model/tool downloads. A cold environment can exceed the client's startup timeout. See startup recovery. Existing jobs need no migration.
Regenerated configs and the plugin carry [diarization,url]. A config you wrote by hand for 0.3.x — uvx --python ">=3.11,<3.14" talkthrough-mcp, or a pin without the url extra — upgrades the server in place and lists the new process_url tool, but only direct https:// media links work until the extra is there: YouTube and video pages answer with the one-line install fix. Add url to your command (uvx --python ">=3.11,<3.14" "talkthrough-mcp[diarization,url]"), restart the client, and check with talkthrough-mcp --version (0.4.1+), which names the extras the environment has; the server logs the same line to stderr at every start, so your client's MCP log shows it too.
git clone https://github.com/korovin-aa97/talkthrougSolo se muestra el principio; lee el resto en el repo