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Pincushion Plugin

by jcooley8

Turns live-app feedback pins into MCP work packets that coding agents can inspect, implement, and resolve with commit traceability.

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Install Pincushion Plugin

Pick your client, then add it in one click or paste the config.

STDIONode.js
~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "jcooley8-pincushion-plugin": {
      "command": "npx",
      "args": [
        "-y",
        "pincushion-mcp"
      ]
    }
  }
}

Settings → Developer → Edit Config, merge this into mcpServers, then fully quit and reopen Claude Desktop.

Install not yet sandbox-tested— the server itself is confirmed live (we called its tools/list endpoint). The stdio install command is a separate, ongoing check.

Overview

jcooley8/pincushion-plugin MCP server connects coding agents to Pincushion feedback, exposing pins with URLs, selectors, screenshots, DOM context, threads, and acceptance criteria. Agents can search and summarize feedback, inspect component-specific issues, reply to stakeholders, and resolve completed work with optional commit, branch, and pull-request links. It also supports deployment capture, critique, QA-result import, verification, and agency-coordination workflows. Reach for it when visual feedback from a live application needs to become actionable implementation work inside an agent workflow.

Use cases

  • Retrieve live-app feedback before changing code
  • Search annotations by selector, component, comment, or tag
  • Batch implementation work for one page
  • Record commits and pull requests when resolving pins
  • Import parsed QA findings as agent pins

Key features

  • Reads Pincushion pins with visual and DOM context
  • Filters and searches feedback by page, component, and status
  • Replies to threads and resolves completed annotations
  • Links fixes to commits, branches, and pull requests
  • Supports deployment capture, critique, QA import, and verification workflows
  • Provides a Claude Code plugin and REST mode

Tools65

What Pincushion Plugin lets your agent do. Expand a tool for its parameters.

Verified live~16.8k tokens of context

Security & health

What it can reach and how reliably it runs — from our own checks, not the maintainer’s claims.

ActiveLast checked 1d ago

Recent health check succeeded.

19/19 checks healthy over the last 78d

Supply-chain signal

No high-severity advisories surfaced by our automated scan.

Critical 0High 0Medium 0Low 0

Scanned 10d ago via OSV.dev · pincushion-mcp (npm)

Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks — not a rating.

GitHub stars1Stargazers on the source repository.
npm downloads2kPackage downloads in the last 30 days.
Last commit5d agoMost recent push to the default branch.
Tools exposed65Callable tools this server registers over MCP.
Directory activity2 viewsConfig copies, upvotes, and views on AllMCPs.

How Pincushion Plugin works

What jcooley8/pincushion-plugin MCP server does

jcooley8/pincushion-plugin turns Pincushion annotations into implementation-oriented work packets for AI coding agents. A pin can carry the affected page URL, element selector, screenshot, viewport, DOM excerpt, discussion thread, project context, likely files, and acceptance criteria. This gives an agent both the location of a problem and the context needed to investigate it.

The server supports the full feedback loop: read incoming pins, search or group them, ask questions in a thread, apply a fix, and mark the item resolved. Resolution can include the commit SHA, branch name, and pull-request URL so the dashboard can connect feedback to shipped code.

How it works

The package runs with npx pincushion-mcp. By default it uses MCP over stdio and reads local project feedback from .feedback/. Hosted cloud synchronization can be enabled through sign-in; the normal hosted setup does not require a separate Supabase project, database, or backend API key. A REST mode is also available when an HTTP endpoint is preferred.

The repository includes a Claude Code plugin that starts the MCP process for the open project and provides commands for viewing pins, implementing work, resolving feedback, reviewing summaries, and setup. The server can also be used from other MCP-compatible editors and agents.

Setup and configuration

For hosted setup, run:

Terminal
npx pincushion-mcp setup

The setup wizard signs in, asks for project URLs, and lets the user select an editor. Restart the editor afterward and verify the connection by asking the agent to call a project-context or actionable-pins tool. If authentication is missing or expired, run npx pincushion-mcp login.

Useful command-line options include:

  • --project-dir PATH to select the project containing .feedback/.
  • --cloud-sync to explicitly enable hosted synchronization.
  • --rest to run the REST API mode.
  • --port PORT to choose the REST port, which defaults to 3456.
  • --sync-url URL and --api-key KEY for the optional legacy self-host adapter.
  • --license-key KEY to provide an explicit account credential override.

The documented runtime requirement is Node.js 22.22+ within Node 22, or Node 24.

Tools and capabilities

Feedback discovery includes annotation retrieval with page, LWC component, and status filters; full-text annotation search; status, page, priority, and component summaries; and component-specific feedback with implementation-oriented summaries. get_implementation_packet can collect the pins for one page, while assign_pin_to_agent places a pin in the local agent queue.

Conversation and completion tools include add_agent_reply, resolve_annotation, fix_and_resolve, and the Pincushion-specific bot reply flow. The combined fix-and-resolve operation can retain file, line, commit, branch, and pull-request details.

Additional workflows cover deployment frame refreshes, pending critique requests, deployment page registration and capture results, AI-authored critique or agent pins, QA JSON imports, time-to-fix metrics, and verification evidence. Pilot agency tools provide private labels, internal messages, and owner/editor coordination state.

Limitations and notes

Some operations are intentionally restricted to particular workflows. Bot replies and critique pins are reserved for Pincushion AI flows, while agent pins represent third-party QA or browser agents. Deployment capture requires exact page and device receipts from the active run, and the server rejects missing, stale, replayed, cross-deployment, or expired evidence.

QA imports normalize already-parsed axe or Playwright JSON; they do not read files, fetch URLs, call a provider, or upload repository contents. Caller-reported verification is not independent proof of a deployment, check execution, or client acceptance. Time-to-fix metrics include a threshold signal and are intended to be hidden when fewer than five resolved pins are available.

Read the full README View source on GitHub

Reviews

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Frequently Asked Questions about Pincushion Plugin

jcooley8/pincushion-plugin is an MCP server that connects AI coding agents to Pincushion feedback pins from live applications. Its main tools retrieve, search, summarize, reply to, assign, and resolve annotations, while also recording commit, branch, and pull-request details for completed fixes.

Install it by running `npx pincushion-mcp setup` from the application repository. The wizard signs you in, reviews project URLs, and writes supported editor configuration when safe. Restart the editor, then verify the connection by asking the agent to read project context or actionable pins.

Yes, jcooley8/pincushion-plugin supports Cursor. The hosted setup wizard can configure supported project MCP settings, and the maintained setup guide provides the current Cursor commands. After setup, restart Cursor and test an actual feedback read rather than relying only on configuration being written.

Yes, `fix_and_resolve` accepts a commit SHA, branch name, and pull-request URL. It resolves the pin and lets the Pincushion dashboard link the feedback to the implementing work. The pull request URL can use GitHub, GitLab, or Bitbucket formats.

Yes, `import_qa_results` accepts already-parsed axe JSON or Playwright JSON from an authenticated project user. Use dry-run mode to preview normalization and deduplication. Failed observations can create or update open agent pins; passed, skipped, and inconclusive observations do not resolve pins.

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