Figma Context MCP
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot.
作者による説明(英語の原文)
Keeps AI coding agents' plan and design markdown managed and versioned, for Claude Code and Codex.
この3つを1つのスコアにまとめることはしません。意見、測定、人気はそれぞれ別のものだからです。
このサーバーのやさしい解説はまだ書いていません。以下はレジストリから読み取った事実です。
使っているAIアプリを選んで、設定をコピーしてください。
必要なもの
どのアプリを使っていますか?
上でアプリを選んでください。選んだアプリを覚えておくので、次からはボタンに「…にインストール」と表示されます。
Claude Desktop → Settings → Developer → Edit Config を開き、claude_desktop_config.json にこれを貼り付けます
{
"mcpServers": {
"flanner": {
"command": "uvx",
"args": [
"flanner"
]
}
}
}ターミナルでこれを実行します
claude mcp add flanner -- uvx flannerプロジェクトの .cursor/mcp.json、または ~/.cursor/mcp.json に貼り付けます
{
"mcpServers": {
"flanner": {
"command": "uvx",
"args": [
"flanner"
]
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
プロジェクトの .vscode/mcp.json に貼り付けます
{
"servers": {
"flanner": {
"type": "stdio",
"command": "uvx",
"args": [
"flanner"
]
}
}
}ブラウザがアプリを開いてよいか確認し、そのあとアプリが設定を表示して確認を求めます。キーの値は空欄のままなので、自分で入力してください。
これはパソコンで動くサーバーですが、ChatGPTがつなげるのはインターネット上のサーバーだけです。ほかのアプリを選んでください。
選んだアプリは、この端末のCookieに保存されます。アカウントは不要です。
この設定は、作者のレジストリ登録情報から作成しています。READMEと違う場合は、READMEに従ってください。
パソコンで動くサーバーです。インストールすると、ツール一覧がAIアプリに表示されます。
誰でも見られる情報をチェックしており、コードは読んでいません。当てはまらない項目は数に入れていません。 · 2026年11月7日にチェック
公開者(jaysonmulwa)がリポジトリの所有者(elandlabs)ではありません。別の人が登録した可能性があります
このリポジトリはまだGitHubから読み取っていません
このリポジトリはまだGitHubから読み取っていません
これはパソコンで動くため、インターネット上のエンドポイントはありません
パソコンで動き、代わりにローカルの設定を使います
パソコンで動くサーバーです。ツール一覧を読み取れるのは、インターネット上のエンドポイントがある場合だけです
レジストリでこのカテゴリにある有効なすべてのサーバーと比較しています。スターは、公開者がリポジトリの所有者である場合だけ数えます。
当てはまる基本チェック1項目のうち0項目に合格しました。コードは読んでいません。キーやトークンを追加する前に、サーバーがどんなアクセスを求めているかを確認し、必要な権限だけを持つキーを使ってください。
レジストリには必須のキーは載っていません。ただし、最初に使うときにサインインを求めるサーバーもあります。
あなたのパソコンで動きます。必要なときにAIアプリが起動し、データは作者のサーバーを通りません(サーバー自体がオンラインサービスを呼び出す場合を除きます)。
GitHubリポジトリの最終更新は–、最新バージョン(0.16.0)がレジストリに届いたのは30 日前です。
Claude Desktop、Claude Code、Cursor、VS CodeなどのMCP対応アプリで使えます。パソコンにPython (uv)も必要です。
同じカテゴリには:Figma Context MCP, Claude Real Video, Figma MCP Server
同じカテゴリで、ほかの作者が作ったサーバー。スターの多い順。
カードの見方:★ GitHubスターi3つの柱:レビュー · チェック · 利用状況i更新=最新バージョンをレジストリに公開した日i
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.
作者のリポジトリから書かれたとおりにコピーしたものです。PopNx MCPは内容を確認・推奨していません。HTML、画像、スクリプトは取り除いています。リンクはこのサイトの外へ移動します。
A plan-file manager for AI coding agents, wired into Claude Code and other assistants over MCP (Model Context Protocol).
AI agents write markdown constantly: design docs, migration plans, architecture notes. It piles up fast, scattered across your repo, quietly going stale, and easy to commit by accident. Flanner gives those files one home, versions them automatically as the agent revises, and keeps them out of git until you decide otherwise, with a browsable reading view and an audit trail on top.
Those plan files pile up in two directions at once: scattered across your projects locally, and scattered across open issues in your project-management tool. Flanner is the choke point for both, keeping you organized on disk and linked to the issue each plan belongs to.
Flanner is local-first, and stays that way when a team uses it. Plans sync directly between your machines over an encrypted connection — there is no server holding them, and no upload step. The hosted side (Flanner Mesh) issues identities and decides who may read what; it never sees plan contents and could not read them if it wanted to. Next after that: clean links out to the tools teams already work in, from product trackers and chat to second brains like Notion.
.plans/ and are kept out of commits automatically.flanner init wires CLAUDE.md, AGENTS.md, and a guard hook so agents save plans through flanner instead of scattering raw markdown.flanner skills scan reads them all and flanner skills doctor says which copy is in effect and what is wrong with the rest. A read: nothing in a package is executed.flanner curb map checks every Claude Code and Codex launch for readable credentials and for the channels that could carry them away, and rates it High, Medium or Low with the rule behind it. Its output never names a credential or a location, whoever runs it; flanner curb show puts those in a window on your screen. flanner curb sweep finds secrets agents left behind in transcripts, sessions, instruction files, skills, MCP configs, shell history and .env files, and says which were sent to a model provider. A read: nothing is changed, and nothing leaves the machine unless you ask a secret's own issuer to check it. With Flanner Mesh, flanner curb policy takes one agent policy your organization signs, applies the changes that only tighten once you enrol, and holds anything else for your approval; flanner curb fleet shows admins each device's policy state and counts, from minimised reports each device signs. flanner curb ci, also a GitHub Action at actions/curb-ci, judges agent steps in CI workflows the same way and writes SARIF; flanner curb app finds an application's own LLM calls; and the agent-blast-radius skill lets an agent run the redacted commands itself. flanner curb attribution gives each agent a signing key of its own, kept in your OS credential store, so its commits are labelled; flanner curb verify says which agent key signed each commit, checked against your organization's signed key registry. A signature shows which key signed, not who wrote the code.flanner messages send previews before it sends, and flanner tells an agent to show a teammate's message and never act on it.LINEAR_API_KEY, flanner verifies the issue and shows its live state, in the CLI and the dashboard. Built but not supported yet: set FLANNER_INTEGRATIONS=1 to turn them on.uv tool install flanner # or: pipx install flanner, or: pip install flanner
cd your-project # a git repo where plans should live flanner init # sets up the database, MCP registration, and a project
Rather not install Python? The desktop app for Windows, macOS and Linux is the same flanner with nothing to install first: the web UI in a window, the command line, and the MCP server Claude and Codex use, with background sync and updates. Download it from flanner.io/download; desktop/README.md covers building and releasing it.
uv tool install gives flanner an environment of its own and puts both flanner and flanner-mcp on your PATH. Both matter: your agent spawns flanner-mcp by name, so a project virtualenv can hide it from an agent started outside that environment. pip install flanner works, with that caveat.
Then ask your agent to work with plans:
"Create an architecture plan for the auth service"
"Show me the history of the architecture plan"
And open the dashboard to browse them:
flanner web --open-browser # http://localhost:8080
flanner init is safe to re-run. It detects your git root, creates .plans/, updates .gitignore, and installs the agent integration.
Three agents, three different files, and init handles all of it — there is no second command to remember. It writes a project-scoped .mcp.json that Claude Code reads, registers the server at user scope and in Claude Desktop's config, and adds managed blocks to CLAUDE.md and AGENTS.md. Codex reads AGENTS.md and registers MCP servers in ~/.codex/config.toml; when Codex is installed, init adds flanner's entry there, and prints the two lines to paste only when it cannot edit the file safely. flanner status shows a row per agent, each checked where that agent actually looks, and flanner setup re-runs the registration on its own if one of them needs repairing later.
--setup picks which of them you want, and repeats: flanner init --setup codex registers Codex and nothing else. --skip-claude registers with no agent, though the repository's own files are still written.
Adopting a repository somebody else set up? flanner init --sync also imports the plan files already committed in it, so flanner list shows them straight away.
flanner init [--project-root PATH] [--plan-dir DIR] # set up a project
flanner status # projects, plan files, db path flanner list [--project NAME] [--output json] # list projects or a project's plans flanner sync [--project NAME] [--dry-run] # import existing .plans/ files flanner config NAME [--plan-dir DIR] [...] # change project settings flanner web [--port 8080] [--host 127.0.0.1] [--open-browser] flanner start [--port 8765] / flanner stop # MCP server in the background, over http flanner peer start / flanner peer stop # serve plans to teammates in the background flanner mem remember "..." --category fact # durable context for later sessions flanner mem recall "..." # search what earlier sessions knew flanner mem list / show ID / supersede ID --with "..." # browse, read, and correct flanner mem mode [off|explicit|suggest|auto_safe] # how much this project captures flanner mem share ID / flanner mem withdraw ID # give one to the team, or ask them to stop flanner skills scan / flanner skills doctor # what your agents load, and what is wrong flanner skills list [--all] / inspect NAME # browse them, or read every copy of one flanner skills observe enable / flanner skills report # record which get used; init asks flanner skills adopt NAME / install HASH / rollback ID # keep a copy, install it, put it back flanner skills share HASH / transfers / import ID # send one to the team; receiving is not installing flanner curb map [--agent A] [-- LAUNCH ...] # what each agent launch can reach flanner curb show # names and locations, in a window flanner curb inventory # agents, MCP servers, hooks, jobs flanner curb sweep [--validate] # secrets agents left behind (needs flanner[sweep]) flanner curb forget # delete Curb's reports and digest key flanner curb fix [--dry-run|--undo] # close what agents reach, after your OS says yes flanner curb test # prove each block with decoys (costs tokens) flanner curb decoys [--renew|--remove] # the decoys the tester planted flanner curb scrub FILE [--dry-run] # replace rotated secrets in a file (no undo) flanner curb log [--enable|--disable|--verify] # each tool call's metadata, hash-chained and signed flanner curb observed # what each agent has been seen using flanner curb policy [--check-in|--enrol|--approve] # your organization's signed agent policy flanner curb fleet # every device, checked by its own signature (admins) flanner curb ci [PATH] [--sarif F] [--fail-on L] # agent steps in CI workflows, as SARIF flanner curb app [PATH] [--sarif F] # LLM calls in an app's Python code flanner curb attribution [--setup|--rotate] # sign each agent's commits with its own key flanner curb verify [REV|RANGE] # which agent key signed each commit flanner register [--force] / flanner unregister # MCP registration with Claude Desktop flanner claude-info # integration status
Most MCP clients spawn their own copy of the server over stdio and need neither start nor stop. They are for a client that only speaks http, two editors sharing one server, or working with flanner on its own. The server binds 127.0.0.1 and no option widens that: every tool acts with the full authority of whoever started it, and nothing authenticates a caller.
Plan file format
Every managed plan carries YAML frontmatter, generated by the tools and never hand-written:
---
mcp_plan_file: true project_id: 3d816ecd-489a-4fa0-abe2-15ec93f60d5a plan_file_id: 59c34f9c-8471-47fc-97f2-8dcfefa15434 plan_name: architecture version: 2 created_by: claude
Your plan content here...
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