MCP server

Proofsource Official

co.proofsource/proofsource

Checked 25 Oct 2026, 20:29 UTC · Connected to it and listed its tools

AI visibility: which buyer questions name your brand in ChatGPT, Perplexity, Claude, AI Overviews.

Website Source

At a glance

Type

MCP server

Publisher

proofsource.co (verified by the MCP Registry)

Status

Working at last check

Tools

14

Token cost

About 2,893 tokens per request

Sets up in

Claude Code, Claude Desktop, Codex, Gemini CLI, Cursor, VS Code, Antigravity, ChatGPT, OpenAI API, Grok

Last checked

25 Oct 2026, 20:29 UTC

Connect it to your agent

Add to CursorAdd to VS CodeVS Code Insiders

Opens the app, which shows the server and asks you to confirm. For other apps, copy the setup below.

Claude Code

claude mcp add --transport http proofsource https://app.proofsource.co/v1/mcp

Claude Desktop

Settings → Connectors → Add custom connector, and paste the URL.

Codex (config.toml)

[mcp_servers.proofsource]
url = "https://app.proofsource.co/v1/mcp"

Gemini CLI

{"mcpServers":{"proofsource":{"httpUrl":"https://app.proofsource.co/v1/mcp"}}}

Cursor

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

VS Code

{"servers":{"proofsource":{"type":"http","url":"https://app.proofsource.co/v1/mcp"}}}

Antigravity

agy mcp add proofsource https://app.proofsource.co/v1/mcp

ChatGPT

Settings → Apps & Connectors → Advanced settings: turn on Developer mode, then Create a connector and paste the URL. Which plans can do this varies.

OpenAI API (Responses tools)

{"type":"mcp","server_label":"proofsource","server_url":"https://app.proofsource.co/v1/mcp","require_approval":"always"}

Grok (xAI API tools)

{"type":"mcp","server_label":"proofsource","server_url":"https://app.proofsource.co/v1/mcp"}

Tools

• add_brand ~270 tokens
  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). It reads the site, picks the buyer questions, and starts the first scan across the AI engines. Re
• create_prompt ~238 tokens
  Adds a buyer question to a topic so it is asked 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.
• get_changes ~158 tokens
  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.
• get_citations ~276 tokens
  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_competitors ~246 tokens
  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_fix_verification ~199 tokens
  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.
• get_report_link ~160 tokens
  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.
• get_scan_status ~133 tokens
  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_visibility ~318 tokens
  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
• list_brands ~67 tokens
  The brands this workspace tracks in AI answers, with ids and websites. Call first; every other tool takes a brand_id.
• list_fix_opportunities ~153 tokens
  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.
• list_topics ~112 tokens
  The topics and buyer questions this workspace asks ChatGPT, Perplexity, Claude and Google AI for a brand. Gives the topic_id create_prompt needs.
• mark_fix_shipped ~343 tokens
  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.
• see_example ~220 tokens
  Shows what Proofsource measures, without signing in: a real visibility card for one example brand (Tesla), from answers 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 ans

Browse

• Claude tools
• Perplexity tools
• Social media
• Mobile apps
• YouTube
• Calling other AI models

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