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)
Score your specs before feeding them to an LLM. MCP server with radar chart visualization.
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.
You need
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Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"spec-score": {
"command": "npx",
"args": [
"-y",
"spec-score-mcp"
]
}
}
}Run this in your terminal
claude mcp add spec-score -- npx -y spec-score-mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"spec-score": {
"command": "npx",
"args": [
"-y",
"spec-score-mcp"
]
}
}
}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": {
"spec-score": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"spec-score-mcp"
]
}
}
}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.
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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 8, 2026
The registry name was verified with the GitHub account openpoem, 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.
The registry does not list a required key, though some servers ask you to sign in on first use.
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 (2.0.2) reached the registry 8 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:↓ Downloads per weeki★ 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.
Score your specs before Claude builds from them.
A balanced spec produces balanced code. An unbalanced spec produces creative fiction.
When your spec is detailed on some axes but vague on others, Claude doesn't ask for clarification — it fills in the blanks. The result compiles, the tests pass, but it's not what you meant.
This tool catches that before you start building. It scores your spec on 4 axes, tells you which one is weakest, and gives you a concrete tip to fix it.
| Axis | Question it answers |
|---|---|
| completeness | Can Claude understand the full scope of what to build? |
| clarity | Is there only one way to interpret this spec? |
| constraints | Does Claude know what NOT to build? |
| specificity | Are there concrete, testable details? |
Each axis scores 0.0 to 1.0. The balance score measures how evenly the 4 axes are covered.
Balance matters more than individual scores. A spec scoring 0.50 on all 4 axes (balance: 0.97) will produce better output than one scoring 0.95 / 0.95 / 0.20 / 0.90 (balance: 0.58). Why? That one weak axis — constraints at 0.20 — is exactly where Claude will improvise. You described what to build in detail, but forgot to say what's out of scope. So Claude builds everything you asked for, plus features you didn't.
On the radar chart: an even diamond beats a sharp spike.
| Verdict | What it means |
|---|---|
| SHIP IT | Spec is ready — Claude knows what to build and what not to |
| ALMOST | One axis needs a small fix before you start |
| DRAFT | Multiple axes need work, but the structure is there |
| VAGUE | Well-organized but too abstract to act on |
| UNBOUNDED | Clear goal but no boundaries — Claude will over-build |
| OVER-CONSTRAINED | Lots of rules but unclear what the actual goal is |
| SKETCH | Starting point — needs detail on most axes |
Not SHIP IT yet? The tool tells you which axis is weakest and what to add. Fix that axis, re-score, repeat. Most specs reach SHIP IT in 2-3 rounds.
git clone https://github.com/openpoem/spec-score-mcp.git
cd spec-score-mcp && npm install && npm run build claude mcp add spec-score -- node $(pwd)/dist/mcp.js
The 3 tools are now available in every Claude Code session.
Clone this repo to get the built-in slash commands:
/project:scan my-feature-spec.md
Reads the file, scores it, and writes a my-feature-spec.md.scored.md with scores, verdict, tip, and a radar chart.
/project:compare blueprint.md implementation.md
Scores both files and writes a compared.scored.md with side-by-side radar charts.
The 3 MCP tools work in any Claude Code conversation:
| Tool | What it does |
|---|---|
spec_score | Scores a spec on 4 axes, returns balance score and verdict |
spec_visualize | Generates an SVG radar chart from scores |
spec_compare | Side-by-side comparison of two scored specs |
Ask Claude: *"Score this spec"*, *"Show me the radar chart"*, or *"Compare these two specs"*.
This tool scoring its own spec — four rounds, each fixing the weakest axis:
Build a spec scoring tool
UNBOUNDED 0.12 Tip: What does 'scoring' mean? What axes? What output?
One axis is high (clarity — the goal is clear), everything else is near zero. Claude would build... anything. A web app? A CLI? A VS Code extension? No way to know.
Build an MCP server that scores specs on 4 axes: completeness, clarity,
constraints, specificity. Each axis is 0.0-1.0. Returns a balance score and verdict.
ALMOST 0.67 Tip: What are the verdicts? What does the tool NOT do?
Now Claude knows what to build. But constraints are still weak — it might add auto-fixing, CI integration, a database.
Three tools: spec_score, spec_visualize, spec_compare.
Non-goals: no auto-fixing, no CI integration, no storage.
SHIP IT 0.84 Tip: Add testable criteria — what balance maps to which verdict?
Crossed the threshold. Claude now knows what to build AND what not to build. Specificity is still the weakest axis.
Balance = 1 - sqrt(variance)/mean. SHIP IT > 0.75, ALMOST > 0.60,
plus pattern-based verdicts. Node.js, MCP SDK, stdio transport.
SHIP IT 0.95 Spec is ready for implementation.
Four rounds: 0.12 → 0.67 → 0.84 → 0.95. Each round fixed exactly one thing.
v / ||v||1 - sqrt(variance) / meanThe scoring intelligence comes from Claude, not from the algorithm. The algorithm only measures balance.
src/
mcp.ts # MCP server (3 tools) score.ts # Scoring engine visualize.ts # SVG radar charts .claude/ commands/ scan.md # /project:scan command compare.md # /project:compare command
OpenPoem — spec-score-mcp
MIT License.
© 2026 OpenPoem. info@openpoem.org