Design Intelligence Platform (Local MVP)

A local, high-performance replacement for the hosted Figma MCP server. It downloads Figma files once into a SQLite cache, builds a full-text search index over them, and exposes a local MCP endpoint that Cursor (or any MCP client) queries — without touching the Figma API.

Cursor ──► http://localhost:8787/mcp ──► SQLite cache ──► FTS5 search index
                                              ▲
                                              │ only during explicit sync
                                          Figma API

The cache is the source of truth. The Figma API is called in exactly three situations: validating your token on connect, a cheap version check at the start of a sync, and the full file download when the version changed (or --force).

Architecture

Clean architecture with constructor-based dependency injection; src/app.ts is the composition root that wires everything together.

src/
  api/            REST routes (connect, sync, projects, status, logs, health)
  mcp/            MCP server: 8 tools over Streamable HTTP (stateless)
  figma/          Figma REST API client (axios, typed errors, request logging)
  sync/           Parser: Figma document tree -> flattened node rows + search docs
  database/       Drizzle schema, better-sqlite3 client (WAL), idempotent migrations
  search/         FTS5 search repository (safe query building, bm25 ranking, snippets)
  cache/          Cache metadata key/value store (file versions, bookkeeping)
  config/         Zod-validated .env configuration
  services/       AccountService, SyncService (job engine), QueryService, simplifier
  repositories/   Row-level access: accounts, files/pages, nodes, components, styles, variables
  types/          Figma API types + simplified domain types
  utils/          Structured logger (JSON lines + ring buffer for the dashboard)
  shared/         Typed application errors
frontend/         React + Vite + Tailwind dashboard (Connect / Projects / MCP Status)
tests/            Vitest suites incl. end-to-end MCP-over-HTTP tests with a mocked Figma API
scripts/          CLI sync

How data is stored

A Figma file is a single huge JSON tree. Instead of storing one blob (slow to query) or fully normalizing every property (schema churn), each node becomes one row: queryable columns (node_id, parent_id, page_id, type, name, depth, child_index) plus the node's own JSON with children stripped. Subtrees are rebuilt breadth-first at query time down to a depth limit. Search runs over an FTS5 virtual table indexing names and text content.

Simplified node format

get_node defaults to a compact design representation built for code generation: hex colors, auto-layout expressed as flex terms (mode/gap/padding/justify/align), resolved typography, and component instance names. Raw Figma JSON is available with format: "raw".

Installation

Requires Node.js 20+.

npm install
cp .env.example .env   # optional; defaults work out of the box
npm run dev

• Dashboard (dev): http://localhost:5173 (proxies to the API)
• API + MCP server: http://localhost:8787

For a production-style run: npm run build && npm start — the built dashboard is then served directly at http://localhost:8787.

Environment variables

Variable	Default	Description
PORT	8787	REST + MCP server port
DATABASE_URL	sqlite.db	SQLite database file path
LOG_LEVEL	info	debug | info | warn | error
FIGMA_MAX_RATE_LIMIT_RETRIES	3	Automatic retries on a Figma 429 (0 disables)

Using it

1. Connect — open the dashboard, paste a Figma personal access token (Figma → Settings → Security → Personal access tokens). When creating the token, grant these scopes:

   • current_user:read — used once to validate the token
   • file_content:read — required to download files
   • file_metadata:read — recommended; lets re-syncs use the cheap Tier 3 metadata endpoint (the app falls back to a Tier 1 shallow fetch without it)
   • file_variables:read — optional, Enterprise plans only

   The token is validated against /v1/me and stored in the local SQLite database. It is stored in plaintext — this is a single-user local dev tool; treat sqlite.db accordingly.

2. Sync — paste a file key (the segment after figma.com/design/ in a file URL) and click Sync. The full file is downloaded, flattened into SQLite, and indexed. Re-syncs first do a cheap version check and no-op when nothing changed.

3. Connect Cursor — add to your Cursor MCP settings:

{
  "mcpServers": {
    "design-intelligence": {
      "type": "http",
      "url": "http://localhost:8787/mcp"
    }
  }
}

Then ask Cursor things like "Generate the Login page", "Find all buttons", "List every page", "Find typography styles" — all answered from the local cache.

CLI sync

npm run sync -- <fileKey>            # sync (version-checked)
npm run sync -- <fileKey> --force    # re-download unconditionally

MCP tools

Tool	Purpose
sync_file	Explicitly (re)download a file into the cache; chunked for huge files
sync_node	Incrementally re-sync one node/frame/page subtree (must already be cached)
get_file_summary	One-call overview: counts, page list, top components — orient before drilling in
list_pages	Pages of a cached file with their top-level frames
get_node	Node subtree — simplified (default) or raw; depth bounds the size
search	FTS over pages, frames, components, text and styles; limit/offset
list_components	Components / component sets with descriptions; limit/offset + total
get_styles	Shared styles and design variables; limit/offset + totals

fileKey is optional on read tools when exactly one file is cached. Read tools are marked readOnlyHint so clients like Cursor can auto-run them safely.

REST API

POST /api/connect · POST /api/sync · POST /api/sync-node · GET /api/projects · GET /api/status · GET /api/logs · GET /api/health · GET /api/connection

How sync works

1. GET /v1/files/:key/meta — compare version against the cached one; stop if unchanged. This is a Tier 3 endpoint (large rate budget). Without the file_metadata:read scope it falls back to GET /v1/files/:key?depth=1 (Tier 1).
2. GET /v1/files/:key — full download (no vector geometry). Tier 1 — the scarcest rate-limit class (per Figma's rate limits, roughly 10–20 requests/min on Dev/Full seats since Nov 2025), which is exactly why this platform caches instead of proxying.
3. Parse: flatten the document tree into node rows and search documents.
4. Single SQLite transaction: replace file, pages, nodes, components, styles.
5. Variables via GET /v1/files/:key/variables/local — Enterprise-plan only; a 403 is expected on personal/pro plans and logged as a warning, not an error.
6. Rebuild the FTS5 index for the file.

Sync runs as a background job; poll GET /api/status or watch the dashboard. Nothing else ever calls the Figma API.

For very large files, pass chunked: true (the sync_file tool / POST /api/sync) to download page-by-page — a shallow ?depth=1 fetch for the page list, then one ?ids=<pageId> request per page — instead of one giant whole-file response. It bounds peak payload/memory at the cost of more Tier-1 requests (the 429 retry above absorbs transient limits).

Incremental sync

Iterating on one screen shouldn't re-download the whole file. sync_node (MCP) / POST /api/sync-node fetches a single node via GET /v1/files/:key/nodes?ids=, re-roots the returned subtree from the cached node's position, and atomically replaces just that branch — node rows and their search index — while upserting any component/style metadata the response carries. The node must already be cached from a prior full sync; a full sync_file remains the way to reconcile structural changes such as added or deleted pages.

Scripts

npm run dev · npm run build · npm start · npm test · npm run lint · npm run format · npm run sync -- <fileKey>

Error handling

Typed errors with stable codes surface everywhere: INVALID_TOKEN, NOT_CONNECTED, FILE_NOT_FOUND, CACHE_MISS, CACHE_EMPTY, RATE_LIMITED, SYNC_IN_PROGRESS, VALIDATION_ERROR, FIGMA_API_ERROR. MCP tools return them as tool errors instead of crashing the transport.

Future roadmap (designed for, not implemented)

Multiple accounts (the API client is already token-stateless), semantic/vector search (sits next to the FTS table), AI code generation (consumes the simplified node format), background sync, component dependency graphs, and Electron packaging.