Figma Context MCP (glips) vs Stata MCP
Two MCP servers from our design ranking, compared on live data - updated nightly, never sponsored.
Bottom line · 2026-09-18
Figma Context MCP (glips) records significantly more monthly package installs (307,488 vs 12,422); both are actively maintained, with commits inside the last month.
How they differ in kind
Figma Context MCP (glips) focuses on: Give your coding agent access to your Figma data. Stata MCP focuses on: MCP-for-Stata is an open-source MCP server and CLI that lets any AI agent you use invoke local Stata on your device for regression analysis, econometrics, paper replication, and empirical research. Environment-variable extraction: Figma Context MCP (glips) yielded no variables extracted; Stata MCP yielded 1 variable. Implementation languages differ (TypeScript vs Python).
What each one does
Figma Context MCP (glips)
Give your coding agent access to your Figma data. Implement designs in any framework in one-shot. It runs locally over stdio via the published package.
From the project's README.
Stata MCP
MCP-for-Stata is an open-source MCP server and CLI that lets any AI agent you use invoke local Stata on your device for regression analysis, econometrics, paper replication, and empirical research. It provides command guards, resource monitoring, automatic log capture, and cross-platform client installation, while you retain control of your data and Stata license.
From the project's README.
14 signals, side by side
| Signal | Figma Context MCP (glips) | Stata MCP |
|---|---|---|
| Monthly installs | 307,488 | 12,422 |
| GitHub stars | 15,874 | 260 |
| Last commit | 2026-09-18 | 2026-09-14 |
| Releases · last 90 days | 0 | 10+ |
| In the registry since | Sep 2025 | Feb 2026 |
| Registry versions | 15 | 32 |
| Documented tools | not extracted - see README | not extracted - see README |
| Env vars extracted | none extracted - see README | 1 |
| Runs | local (stdio) | local (stdio) |
| Endpoint auth | local only | local only |
| Maintenance | actively maintained | actively maintained |
| License | MIT | AGPL-3.0 |
| Language | TypeScript | Python |
| Category rank | #1 of 85 | #3 of 85 |
Environment variables found in the READMEs
These are extracted names, not a requiredness check. Project docs may mark them optional or require other setup.
Figma Context MCP (glips)
No environment variables were extracted from the README setup. Check the project documentation for other authentication or configuration steps.
Stata MCP
- STATA_MCP__CWD
Which one, for what
Derived from the signals above, not hands-on testing.
Pick Figma Context MCP (glips) if…
- → you want the more widely installed option - 307,488 monthly installs vs 12,422
- → you prefer a TypeScript codebase to extend or audit
Pick Stata MCP if…
- → release velocity matters - 10+ releases in 90 days vs 0
- → you prefer a Python codebase to extend or audit
Who's behind them
Figma Context MCP (glips) - glips: 1 MCP server tracked, 1 maintained, 15,874 combined stars.
Stata MCP - sepinetam: 2 MCP servers tracked, 2 maintained, 263 combined stars. Full record.
Not sold on either?
The next-ranked design servers we track:
Quick answers
Is Figma Context MCP (glips) better than Stata MCP?
Package installs favor Figma Context MCP (glips): 307,488 monthly installs to 12,422. Stata MCP still ranks #3 of 85 maintained design servers. Data as of 2026-09-18; we haven't hands-on tested either.
Can I use Figma Context MCP (glips) and Stata MCP together?
Yes - MCP clients accept multiple servers in one config, so you can enable both design servers side by side. If their tools overlap, keep the one whose toolset fits to keep your agent's tool list lean.
What environment variables do their READMEs document?
Figma Context MCP (glips): no environment variables extracted from the README setup; Stata MCP: 1 environment variable extracted from the README setup. Extraction does not rule out other authentication or configuration steps; check each project's current documentation.
Keep exploring: best design servers · TypeScript servers · Python servers · all comparisons · every server
Methodology: package-usage signal = npm/PyPI installs (last month, platform APIs) · maintenance = commit recency + release cadence (GitHub) · tool lists and environment-variable names extracted from each project's README · endpoint auth from our own nightly probes. We haven't hand-tested these servers; everything here is data as of 2026-09-18.