Electron Stagewrightdocs

Choose an Electron MCP server

Electron automation servers overlap in the basics: launch an app, inspect its UI, and send input. The useful choice is therefore about the workflow you need to prove, the trust boundary you can accept, and the recovery information your agent needs when a run does not go as planned — not a single tool-count or latency score.

This guide compares the public surfaces that were reviewed on 2026-07-15. Projects change; follow the linked primary documentation before making a production decision.

The practical choices

If your primary need is… Start by evaluating… Why
A compact, single-session Playwright driver for a built Electron entry point electron-driver Its public v0.3.0 README describes a 38-tool, Playwright _electron server with one owned session, selector-oriented interaction, screenshots, console capture, and main/renderer eval.
CDP-oriented automation and a configurable security-level model laststance/electron-mcp-server Its v2 README describes CDP integration, approximately 40 granular electron_* tools, and STRICT through DEVELOPMENT security profiles.
Agentic UX testing that must inspect, assert, recover, and leave evidence Electron Stagewright It combines stable snapshot refs, retrying electron_expect_* assertions, structured recovery envelopes, multi-session lifecycle control, trace/replay, and explicit first-party plugins.

None of these rows is a claim that one project is universally better. The right answer depends on your Electron app, the host agent, and the workflow you need to make repeatable.

Choose Electron Stagewright when

Evaluate alternatives on their strengths

It is healthy to keep the surrounding ecosystem in the evaluation set.

Use a disposable test app and the same host configuration for every candidate. A successful installation is not evidence that the server can prove your real workflow.

Compare workflows, not a leaderboard

Tool counts, raw request bytes, and a local latency number measure different things. A server that returns a richer recovery envelope or keeps a retry loop on the server may transfer more data for a single primitive action while reducing the number of agent turns needed to finish a workflow.

Electron Stagewright keeps a reproducible, shared-task benchmark harness in packages/bench. It records protocol facts and uses pinned adapters, but it is deliberately not a universal public ranking: one machine, one host, and a small fixture cannot predict your app's startup, renderer complexity, security policy, or agent behavior.

For a decision you can defend, run the same three workflows against each candidate:

  1. Inspect: launch or attach, find an accessible control, and obtain the state needed for the next action.
  2. Change and assert: mutate the app, then prove the expected result with a bounded wait and useful failure evidence.
  3. Recover: deliberately invalidate a ref, reload a renderer, close a window, or introduce a slow response. Check whether the host gets a stable error, an actionable next step, and enough context to continue safely.

Keep the artifacts, versions, app fixture, host configuration, and hardware facts beside the result. That evidence is more useful than a copied benchmark number.

A short selection checklist

Before committing to a server, answer these questions with a real app:

  1. Can it reach the app in the mode you need: launch, CDP attach, or process injection?
  2. Can an agent identify controls through the accessibility semantics your app actually exposes?
  3. Does a failed assertion report a machine-readable cause and a safe recovery path?
  4. Are powerful capabilities — eval, network mutation, storage reads, or native instrumentation — explicit opt-ins with an understandable operator boundary?
  5. Can you save a reproducible artifact or test specification when a workflow fails?

If the answer is consistently yes, the server is a good fit for your workflow — regardless of which name appears first in a comparison table.