2026-09-19 — MCP · Agents · Tutorials

Ask ChatGPT from inside your editor — MCP setup for Cursor and Claude

Your AI editor can write code — but it can’t tell you what ChatGPT told a customer this morning. The MCP server fixes that: every engine becomes a tool the editor calls like any other.

Claude Code

claude mcp add --transport http answerline \
  https://mcp.answerline.dev/mcp \
  --header "Authorization: Bearer $API_KEY"

Cursor, Windsurf, others

Any MCP-capable client takes the same remote server URL:

{
  "mcpServers": {
    "answerline": {
      "url": "https://mcp.answerline.dev/mcp",
      "headers": { "Authorization": "Bearer sk_…" }
    }
  }
}

What the agent can then do

• chatgpt, perplexity, gemini, copilot, grok — ask each engine a question and get the parsed answer with sources
• google, google_news, google_ai_mode, google_ai_overview — the search surfaces
• credits — check the remaining balance before a long run

A realistic session: “Before we launch this landing page, check what ChatGPT and Perplexity say about our three competitors — pull the sources they cite so I can see what content is winning.” The agent calls the tools, reads sources[], and summarizes — you never left the editor.

Why tools, not copy-paste

The answer lives in the editor’s context — it can diff two engines’ citations, turn searchQueries[] into a keyword list, or write the monitoring script itself using the live API shapes it just observed. MCP guide for the full tool list; agent integration post for the architecture.

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