# Proofsource [Health: Active]

**Category:** 🎯 Marketing  
**Repository:** https://github.com/lcbasu/proofsource-plugins  
**GitHub Stars:** 0  
**Views:** 1  
**Installs:** 0  
**Upvotes:** 0  
**Directory Page:** https://allmcps.com/mcp/proofsource

## Description
AI visibility for your brand: which buyer questions name you in ChatGPT, Perplexity, Claude and Google AI Overviews, which competitors AI recommends instead, which sources it cites, and what to fix. Remote server with OAuth sign-in.

## Tools
Capabilities this server exposes over MCP:

- **list_brands** — The brands this Proofsource workspace tracks in AI answers, with ids and websites. Call first; every other tool takes a brand_id.
- **list_topics** — The topics and buyer questions Proofsource asks ChatGPT, Perplexity, Claude and Google AI for a brand. Gives the topic_id create_prompt needs.
- **get_visibility** — How often ChatGPT, Perplexity, Claude and Google AI mention the brand when buyers ask about its category. by=engine (default): mention rate, share of voice, average position, citation share and sentiment per engine, with the change from the previous period. by=question: each buyer question's mention rate and rank.
- **get_competitors** — The competitors AI answers name for the brand's buyer questions, per engine, with each one's share of voice against the brand and how it changed over the window.
- **get_citations** — The websites AI answers cite for the brand's buyer questions, ranked by share of citations and by how many answers cite them, and where the brand's own site ranks.
- **get_changes** — What moved over the window: the daily mention-rate trend, how much the engines' answers changed, notable changes on competitors' websites, and new pages about the category.
- **list_fix_opportunities** — The gaps that keep AI engines from citing or recommending the brand, each with its evidence and the suggested fix. Gives the gap_id mark_fix_shipped needs.
- **get_fix_verification** — Each fix marked shipped for the brand with its mention rate before and after and a verdict: moved (beyond normal answer churn), within_noise, or awaiting_samples. Fixes marked "Not a fix" are left out; auto-detected page changes carry source auto_detected.
- **create_prompt** — Adds a buyer question to a topic so Proofsource asks it on every engine in the plan from the next run. Counts toward the plan's question limit. Calling again with the same text returns the existing question, never a duplicate.
- **mark_fix_shipped** — Records that a fix shipped, against a gap_id from list_fix_opportunities or a published content_draft_id, so get_fix_verification can measure whether it moved the brand's mention rate. Calling again with the same fix and description returns the existing record.
- **add_brand** — Start measuring a brand: does ChatGPT, Perplexity, Claude or Google AI mention it, and who does AI recommend instead? Give the brand's website (or its app store, Google Maps, YouTube or Instagram link). Proofsource reads the site, picks the buyer questions, and starts the first scan across the AI engines. Reading the site takes 1-2 minutes; if it is still running, call again with the same link and it picks up the same run, never a second one. Returns the brand_id; then use get_scan_status.
- **get_scan_status** — Progress of a brand's first scan after add_brand: the stage, how many AI answers are in out of how many expected, per engine, and when it should finish. Once complete, use get_visibility for the results.
- **get_report_link** — A link to the brand's AI visibility report to share with a team or client: how often AI answers mention the brand, which competitors they name instead, and which sources they cite. Returns the newest finished report's own unlisted link. Reports are built automatically after a brand's first scan.
- **see_example** — Shows what Proofsource measures, without signing in: a real visibility card for one example brand (Tesla), from answers Proofsource collected from ChatGPT, Perplexity, Claude and Google AI Overviews. It shows how often AI answers mention the brand, per engine, which competitors they name instead, and sample answers. Use it when someone asks whether their brand shows up in AI answers and has not signed in. It always shows the example brand; to check their own brand they sign in.

## Claude Desktop Quick Installation
Remote MCP endpoint (confidence: high). Install path detected from listing signals. Add as a URL/SSE server in your client:

```json
"mcpServers": {
  "proofsource": {
    "url": "https://app.proofsource.co/v1/mcp"
  }
}
```

## Documentation

## What Proofsource MCP server does

The Proofsource MCP server measures how often AI-generated answers mention or recommend a tracked brand. It works across ChatGPT, Perplexity, Claude, and Google AI Overviews, using buyer questions associated with the brand's tracked topics.

Results include mention rate, share of voice, average position, citation share, and sentiment. You can examine results by engine or by individual buyer question. Additional tools identify competitors named instead of the brand, the websites cited in answers, changes during a selected period, and gaps that may prevent AI systems from citing or recommending the brand.

A workspace can also record shipped fixes and later compare mention rates before and after the change. Verification classifies the result as moved, within normal answer variation, or awaiting enough samples.

## How it works

Start by listing the brands in the workspace. Most brand-specific tools require the returned `brand_id`. Topics and buyer questions are available through `list_topics`; `create_prompt` can add a question to a topic for future engine runs, subject to the plan's question limit.

For a new measurement, `add_brand` accepts a website or an app store, Google Maps, YouTube, or Instagram link. Proofsource reads the supplied source, selects buyer questions, and begins an initial scan. `get_scan_status` reports progress by stage and engine. Once the scan is complete, visibility, competitor, citation, and change tools can retrieve the results.

The `see_example` tool provides an unsigned example using Tesla. It is intended to demonstrate the type of visibility data available; checking a user's own brand requires signing in.

## Setup and configuration

The remote MCP endpoint is `https://app.proofsource.co/v1/mcp`. It uses OAuth 2.1 and a Proofsource email with a one-time sign-in code. In Claude, add the endpoint as a custom connector. In Claude Code, add it with the HTTP transport and then authenticate through `/mcp`. Cursor, VS Code, Cline, Windsurf, and other MCP clients can add it as a remote Streamable HTTP server.

Claude users can also install the supplied plugin through the Claude plugin marketplace. The plugin provides an AI visibility audit and a fix-planning skill, and its setup then asks the user to select the Proofsource MCP server and sign in.

New accounts using a work email receive two free scans. Personal email addresses can create an account but do not receive scans.

## Tools and capabilities

Read tools cover:

- Workspace brands and tracked topics
- Visibility by engine or buyer question
- Competitors and comparative share of voice
- Cited websites and the brand site's citation position
- Daily trends, answer changes, and new category pages
- Open fix opportunities and fix verification
- Initial scan progress and finished report links
- An unsigned example report

Write tools cover adding a brand, creating a buyer question, and marking a fix as shipped. These actions apply to the user's workspace and are restricted by the account's plan and role. Repeating an identical brand addition, prompt, or shipped fix does not create a duplicate record.

## Limitations and notes

The initial site-reading step can take one to two minutes. A scan must finish before its visibility results are available, and report links are generated from the newest completed report. Added questions run from the next engine run rather than changing past measurements.

Fix verification depends on subsequent samples and may remain awaiting samples or fall within normal answer churn. The service measures the engines and questions configured in the Proofsource plan; adding questions counts toward the plan's limit.

_Full upstream README: https://allmcps.com/mcp/proofsource/readme_