Compute Connector vs Figma Context MCP

A side-by-side look at the Compute Connector and Figma Context MCP MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.

C
Compute ConnectorCode Execution · Remote HTTP/SSE
Low on memory? Your bot sends heavy jobs to cloud sandboxes on your own provider keys. Flat fee.51GoodAuth: not declared
Figma Context MCP logoFigma Context MCPArchitecture & Design · Local subprocess (stdio)Provide coding agents direct access to Figma data to help them one-shot design implementation.71GreatAuth: api key required

Verdict: choose Compute Connector for code execution work over a hosted endpoint; choose Figma Context MCP for architecture & design as a local process. You can also run both side by side in one mcpServers block.

Which MCP server should you choose?

C
Choose Compute Connector when

  • You need dedicated capabilities in the Code Execution domain.
  • You prefer a remote HTTP/SSE transport.
  • You want tools like check_memory, run_job, save_provider_key.
Explore Compute Connector

Figma Context MCP logoChoose Figma Context MCP when

  • You need dedicated capabilities in the Architecture & Design domain.
  • You prefer a local stdio subprocess transport.
  • Its auth model fits you: API key required.
  • You have the keys it needs: FIGMA_API_KEY, PORT.
  • You want tools like get_figma_data, download_figma_images.
Explore Figma Context MCP

Feature & specification comparison

Rows where the two servers differ are marked.

Spec
C
Compute Connector
Figma Context MCP logoFigma Context MCP
CategoryCode ExecutionArchitecture & Design
Quality signal51/100 · Good71/100 · Great
Install commandConfirmedConfirmed
TransportRemote HTTP/SSELocal subprocess (stdio)
AuthNot declaredAPI key required
PricingBYOK (pay the provider)Free
Required env varsNone listedFIGMA_API_KEYPORT
Verified ownerCommunity listingCommunity listing
GitHub stars—16,061
Directory activity 0 views 0 installs 0 upvotes 10 views 0 installs 0 upvotes
Tools82

Tools & capabilities

Compute Connector tools 8

  • check_memoryBefore a heavy job, send how much memory the machine your agent runs on has free (free -m, os.freemem()) and what you are about to run. Get a memory warning and a verdict: run_local, or offload with the provider to use. Free watch-only logs would_offload for the weekly report; nothing runs.
  • run_jobPro: run a shell command in a fresh cloud sandbox on your own provider account (vercel (Vercel Sandbox, default), e2b, daytona, modal, workers (Workers Sandbox)) and get the exit code and the last 16 KB of stdout and stderr back. Send small input files with it. The sandbox is created for the job and stopped right after, so nothing idles on your bill. Free watch-only logs would_offload and runs nothing.
  • save_provider_keyPro, owner only: save one provider key, sealed with AES-256-GCM before it reaches the database. Providers: vercel (Vercel Sandbox, default), e2b, daytona, modal, workers (Workers Sandbox). Vercel needs team_id and project_id; Modal and Workers Sandbox need bridge_url (see provider_setup). The key is checked with a read-only call first and is never returned or logged. Free stores nothing.
  • list_providersEvery provider this connects to, how each one runs, and (with your key) the provider keys you saved: name, provider, fingerprint, default, last used. Never shows a key.
  • delete_provider_keyPro, owner only: delete a saved provider key by name. Jobs on that key stop working at once.
  • provider_setupStep-by-step setup for one provider: where to get the key, what to pass to save_provider_key, links to its docs and price page, and for Modal or Workers Sandbox the bridge code to deploy on your own account.
  • weekly_reportPlain-English summary of the last 7 days: memory checks, low-memory warnings, jobs that would have been offloaded (free) or ran (Pro) by provider, minutes and failures. Read-only; sends nothing. Needs an API key.
  • usage_and_upgradeShow today's usage for your key or IP and the $9/month upgrade link. Free tier: 500 calls/day. Not metered.

Figma Context MCP tools 2

  • get_figma_dataGet comprehensive Figma file data including layout, content, visuals, and component information
  • download_figma_imagesDownload SVG and PNG images used in a Figma file based on the IDs of image or icon nodes. Images will be saved relative to the server's image directory: /home/user

Ready-to-paste client configs

Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.

Compute Connector

mcpServers (Claude Desktop / Cursor)
{
  "mcpServers": {
    "compute-connector": {
      "command": "npx",
      "args": [
        "-y",
        "compute-connector"
      ]
    }
  }
}

Figma Context MCP

mcpServers (Claude Desktop / Cursor)
{
  "mcpServers": {
    "glips-figma-context-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "figma-developer-mcp"
      ],
      "env": {
        "FIGMA_API_KEY": "YOUR_FIGMA_API_KEY_HERE",
        "PORT": "YOUR_PORT_HERE"
      }
    }
  }
}

Frequently asked questions

Compute Connector is categorized under Code Execution and uses a remote HTTP/SSE transport. Figma Context MCP belongs to Architecture & Design and uses a local stdio subprocess. Pick Compute Connector for code execution work and Figma Context MCP for architecture & design.

Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.

Compute Connector is bring-your-own-key: usage is billed by the API provider you supply a key for. Figma Context MCP is listed as free. Auth: api key required. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.

Yes. MCP clients support multiple servers: add compute-connector and glips-figma-context-mcp as separate keys in the same mcpServers object, and your assistant will call tools from either one.

On AllMCPs, Compute Connector has a quality signal of 51/100 (Good) with 0 views, 0 installs and 0 GitHub stars. Figma Context MCP has 71/100 (Great) with 10 views, 0 installs and 16,061 GitHub stars.