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)
Self-contained SearXNG metasearch MCP server. One Docker image, 200+ engines, privacy-first.
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
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": {
"searxng-http": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/whw23/searxng-http-mcp",
"--stdio"
]
}
}
}Run this in your terminal
claude mcp add searxng-http -- docker run -i --rm ghcr.io/whw23/searxng-http-mcp --stdioPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"searxng-http": {
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/whw23/searxng-http-mcp",
"--stdio"
]
}
}
}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": {
"searxng-http": {
"type": "stdio",
"command": "docker",
"args": [
"run",
"-i",
"--rm",
"ghcr.io/whw23/searxng-http-mcp",
"--stdio"
]
}
}
}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.
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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 whw23, 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 (2026.55.0) reached the registry 6 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Docker 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.
中文 · Quick Start · Features · Architecture · Comparison · Usage · MCP Tools · Client Config · Plugin · Contributing
A self-contained MCP server that wraps SearXNG — a free, privacy-respecting metasearch engine that aggregates results from 200+ search engines.
Server mode — deploy once, connect from any client:
docker run -d --name searxng-mcp --restart unless-stopped \
-p YOUR_PORT:8888 --memory=512m --cpus=1 \ ghcr.io/whw23/searxng-http-mcp:latest
Then connect your client to http://YOUR_HOST:YOUR_PORT/mcp/. To enable API key auth, see Authentication.
Local mode — no server needed, run directly in your client:
docker run --rm -i --memory=512m --cpus=1 ghcr.io/whw23/searxng-http-mcp:latest --stdio
Add this as a stdio MCP server in your client — see Client Configuration for details.
uvx mode — if you already have SearXNG running (install guide):
uvx searxng-http-mcp
Set SEARXNG_URL to point to your SearXNG instance (default: http://127.0.0.1:8080).
x-api-key + HTTP Basic Authgraph LR
Client(["client:YOUR_PORT"]) --> Expose(":8888")
subgraph Container["🐳 Docker Container"] direction LR Expose --> Auth{Auth} Auth -->|/mcp| MCP[FastMCP Server] Auth -->|/*| Proxy[Reverse Proxy] MCP --> SearXNG[SearXNG :8080] Proxy --> SearXNG end
style Expose fill:none,stroke:#2496ed,stroke-dasharray:5 5,color:#2496ed
style Client fill:#4a90d9,color:#fff,stroke:#3a7bc8 style Container fill:#f0f4f8,stroke:#2496ed,stroke-width:2px,color:#2496ed style Auth fill:#f5a623,color:#fff,stroke:#d4900e style MCP fill:#50c878,color:#fff,stroke:#3da85e style Proxy fill:#9b59b6,color:#fff,stroke:#8344a5 style SearXNG fill:#e74c3c,color:#fff,stroke:#c0392b
Why these five?
There are 20+ SearXNG MCP servers and many more general-purpose search MCPs. Most SearXNG wrappers only expose a basic search tool, leaving SearXNG's categories, autocomplete, and engine metadata unused. We picked five alternatives that each represent a distinct category:
Feature ✨ This project 88plug/searxng-mcp ihor/mcp-searxng open-webSearch exa-mcp-server Perplexity MCP
Search 200+ engines via SearXNG ✅ ✅ ✅ ❌ ❌ ❌ 30+ search categories ✅ ❌ ❌ ❌ ❌ ❌ Multi-page fanout ✅ ❌ ❌ ❌ ❌ ❌ Autocomplete suggestions ✅ ❌ ❌ ❌ ❌ ❌ Engine discovery tool ✅ ❌ ❌ ❌ ❌ ❌ Dynamic tool descriptions ✅ ❌ ❌ ❌ ❌ ❌ Infrastructure Self-contained (built-in search) ✅ ❌ ❌ ✅ N/A N/A Zero-install Docker deploy ✅ ❌ ❌ ✅ ❌ ❌ HTTP + stdio transport ✅ ✅ ✅ ✅ ✅ ✅ Authentication ✅ ❌ ❌ ❌ ✅ ✅ Web UI reverse proxy ✅ ❌ ❌ ❌ ❌ ❌ AI Coding Agent Plugin ✅ ❌ ❌ ❌ ❌ ✅ General Free & open source ✅ ✅ ✅ ✅ ❌ (paid API) ❌ (paid API) Privacy (self-hosted) ✅ ✅ ✅ ✅ ❌ ❌ Language Python Python Node.js TypeScript TypeScript TypeScript GitHub Stars
Why fewer tools?
MCP is designed for composition — clients connect multiple specialized servers, each doing one thing well. Some alternatives bundle URL fetching, rendered page extraction, multi-query fan-out, or research modes into the search server. We k
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