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)
Product design with Claude: phases, requirements, user stories, RICE, flows, dashboard, Jira.
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.
PRODUCT_DESIGN_DB, JIRA_SITE, JIRA_EMAIL, JIRA_API_TOKENValues marked secret are keys to your account. Never share them or paste them into a chat.
You need
Which app do you use?
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": {
"yeti": {
"command": "npx",
"args": [
"-y",
"yeti-mcp"
],
"env": {
"PRODUCT_DESIGN_DB": "your-value",
"JIRA_SITE": "your-value",
"JIRA_EMAIL": "your-value",
"JIRA_API_TOKEN": "your-value"
}
}
}
}Run this in your terminal
claude mcp add yeti --env PRODUCT_DESIGN_DB=your-value --env JIRA_SITE=your-value --env JIRA_EMAIL=your-value --env JIRA_API_TOKEN=your-value -- npx -y yeti-mcpFill in the empty values before running it.
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"yeti": {
"command": "npx",
"args": [
"-y",
"yeti-mcp"
],
"env": {
"PRODUCT_DESIGN_DB": "your-value",
"JIRA_SITE": "your-value",
"JIRA_EMAIL": "your-value",
"JIRA_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": {
"yeti": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"yeti-mcp"
],
"env": {
"PRODUCT_DESIGN_DB": "your-value",
"JIRA_SITE": "your-value",
"JIRA_EMAIL": "your-value",
"JIRA_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.
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.
PRODUCT_DESIGN_DB envJIRA_SITE envJIRA_EMAIL envThese 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 macorifice, 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: JIRA_API_TOKEN
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 (1.1.0) reached the registry 7 days 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.
An MCP server for product design with Claude. It takes a project from the problem to a verified scope: requirements, user stories, RICE priorities and flow diagrams. Then it sends the work to Jira.
Add Yeti to Claude Desktop, in claude_desktop_config.json, then restart Claude Desktop:
{
"mcpServers": { "yeti": { "command": "npx", "args": ["-y", "yeti-mcp"], "env": { "PRODUCT_DESIGN_DB": "/Users/you/yeti/yeti.sqlite" } } } }
Set PRODUCT_DESIGN_DB to a file in a folder you keep. With npx the package lives in a cache that can be cleared, and a database stored there would go with it. Yeti needs Node.js 22.13 or later.
Then ask Claude:
Create a project "Quotes for craftsmen" with Yeti. Problem: writing quotes takes hours. Users: plumbers and painters. Goal: a quote in five minutes.
Open the Yeti dashboard.
A project goes through five phases, in order:
must requirement completed and covered by a user story, then the project closesProjects have a mode, chosen at creation:
advance_phase tells you what is missing.Projects
| Tool | What it does |
|---|---|
create_project | Start a project in the discovery phase, in strict or free mode |
list_projects | List projects with id, name, phase and mode; archived ones are hidden unless includeArchived is set |
get_project | Show phase, what is missing, and linked items |
project_summary | Progress overview: requirements by priority and status, musts covered by stories, criteria done, RICE leader, Jira links, and what is missing to close |
update_project | Change a project's name, problem, users or goal |
advance_phase | Move to the next phase, or list what is missing |
set_project_mode | Switch a project between strict and free |
duplicate_project | Copy a project's requirements and stories into a new project, as open items (a template) |
create_project_from_template | Create a project from a starter template: a marketplace MVP or a customer portal, with linked requirements and stories |
list_templates | List the starter project templates |
archive_project | Hide a project from list_projects without deleting it |
delete_project | Permanently delete a project and its items. Requires confirm: true; Jira issues are not touched |
Requirements and user stories
| Tool | What it does |
|---|---|
add_requirement | Add a requirement with a MoSCoW priority |
list_requirements | List requirements, filtered by priority, status or project |
update_requirement | Change a requirement's title, description or priority |
set_requirement_status | Mark a requirement open or done |
delete_requirement | Delete a requirement and unlink it from stories |
add_user_story | Create a user story with acceptance criteria, optionally linked to requirements (requirementIds) |
add_decision | Record a design decision with its reason and the options rejected |
list_decisions | List a project's design decisions, oldest first |
list_stories | List user stories with their ids, links, criteria state and Jira key |
update_user_story | Change a story's persona, goal, benefit, linked requirements or criteria. Changing criteria resets their done state |
set_criterion_status | Mark one acceptance criterion of a user story as done or not done |
delete_user_story | Delete a user story |
search_items | Search requirements and stories by text, optionally within one project |
Prioritization and flows
| Tool | What it does |
|---|---|
prioritize_rice | Compute and sort RICE scores |
map_user_flow | Generate a Mermaid flow diagram, with Yes/No branches, next and ends |
list_flows | List the flow diagrams saved in a project, with their index |
delete_flow | Delete one saved flow diagram, by the index shown by list_flows |
Import, export and dashboard
| Tool | What it does |
|---|---|
export_backlog | Export a project backlog as Markdown or CSV; with save, also writes it to data/exports/ |
import_requirements | Import requirements and user stories from CSV in the export_backlog format. Story-to-requirement links are not restored |
open_dashboard | Start the live, read-only dashboard and return its local address |
export_dashboard | Write a static HTML snapshot of the dashboard to data/exports/dashboard.html |
Jira
| Tool | What it does |
|---|---|
set_project_tracker | Bind a project to its work tracker: a Jira project key (e.g. PROJ) or GitHub owner/repo. Set it once; a project cannot change tracker once its items are linked |
push_to_tracker | Create the project's work items in its tracker: requirements become Tasks (Jira) or labelled issues (GitHub), stories become Stories or issues. Dry run by default; limit sends a subset; items already sent are skipped |
sync_tracker | Mark items done or open from the status of their issues in the project's tracker. Read-only on the tracker |
Requirements, stories, RICE scores and flows accept an optional projectId to link them to a project.
You need Node.js 22.13 or later (Yeti uses the built-in node:sqlite module).
git clone https://github.com/macorifice/yeti.git
cd yeti npm install npm run build
Then add it to claude_desktop_config.json, using the absolute path to dist/index.js on your machine:
{
"mcpServers": { "yeti": { "command": "node", "args": ["/absolute/path/to/yeti/dist/index.js"] } } }
Restart Claude Desktop after editing the file.
Once connected, you work with Yeti by talking to Claude. A typical project looks like this.
1. Create a project
Create a project "Quotes for craftsmen". Problem: writing quotes takes hours. Users: plumbers and painters. Goal: a quote in five minutes.
Yeti creates the project in the discovery phase.
2. Move through the phases
must requirement is done and covered by a user story.In strict mode (the default), Yeti will not advance until the phase is complete, and it tells you what is missing. In free mode, it advances and lists what it skipped. You can switch with set_project_mode.
3. Work on the backlog
4. Export
Export the project backlog as Markdown and save it to a file.
With save: true, the file is written to data/exports/ next to the database.
Good to know
data/yeti.sqlite. The content still passes through the chat, so do not put sensitive data in it.A small project from requirements to Jira, using the Mastro example: creating the project, requirements and user stories, RICE prioritisation, a flow diagram, the verification gate, sending to Jira, and keeping the status in sync.
Yeti has a read-only dashboard for the design side of your projects: the phase each project is in, what is missing to move on, which musts are covered by user stories, acceptance criteria, RICE scores and flow diagrams. It does not show a task board: execution belongs in Jira.
Open it from Claude:
Open the Yeti dashboard.
Claude calls open_dashboard and gives you an address such as http://127.0.0.1:4321. Or start it from a terminal:
npx yeti-mcp dashboard --port 4321
127.0.0.1 only, so it is not reachable from other machines, and it refuses requests for other host names.JIRA_SITE is set.export_dashboard still writes a static snapshot to data/exports/dashboard.html, for sharing.
Yeti works without any account. Only one tool talks to an external service:
| Variable | Value |
|---|---|
JIRA_SITE | Your Jira site, e.g. https://your-team.atlassian.net |
JIRA_EMAIL | The email of your Atlassian account |
JIRA_API_TOKEN | An API token created at id.atlassian.com → Security → API tokens |
Set them in your shell profile, for example in ~/.zshrc:
export JIRA_SITE="https://your-team.atlassian.net"
export JIRA_EMAIL="you@example.com" export JIRA_API_TOKEN="your-token-here"
Never put the token in the repository, in a config file you commit, or in a chat. If a token is exposed, revoke it in the same page and create a new one.
For GitHub Issues, set GITHUB_REPO (owner/repo) and GITHUB_TOKEN instead. Without the variables for the bound tracker, sending is refused and the message names what is missing. Dry-run previews work without them.
Yeti supports two work trackers, Jira and GitHub Issues. A project is bound to one of them with set_project_tracker. Each sits behind a common interface, so more can be added: see CONTRIBUTING.md.
For GitHub Issues, set GITHUB_REPO to owner/repo and GITHUB_TOKEN to a token with issues write access. Requirements become issues labelled requirement and priority: must (or should, could, wont); user stories become issues labelled user-story. An item is done when its issue is closed. The GitHub integration has been checked end-to-end against a real repository: an item was sent, its issue was closed by hand, and the sync marked the item done.
Data is stored in SQLite. From a source checkout the default is data/yeti.sqlite inside the project folder; with npx, set PRODUCT_DESIGN_DB as shown in the quick start. Earlier versions used data/db.json: it is imported automatically the first time the new version runs, and then left untouched. To use another location, set the PRODUCT_DESIGN_DB environment variable:
"env": { "PRODUCT_DESIGN_DB": "/absolute/path/to/yeti.sqlite" }
`
Only the beginning is shown; read the rest in the repo