Connect Asva AI to Claude, ChatGPT, Cursor or VS Code and ask about your AI-search visibility, citations and share of voice in the thread you already work in — backed by your live workspace, not a training-data guess.
https://mcp.asvaai.com/mcpAn MCP server is a standard endpoint that lets an AI assistant call external tools.
Asva AI's exposes your answer-engine-optimization tracker as those tools. The Asva AI MCP server exposes your live tracker — mention rate, share of voice, citations, sentiment and competitor rank across ChatGPT, Perplexity, Gemini, Copilot, Grok, Meta AI and Google AI Mode — as OAuth-authed MCP tools any compatible assistant can call.
Once you add it, you can ask "what's my share of voice on Perplexity this month?" and the model calls Asva, reads your workspace, and answers in chat. No dashboard round trip, no export, no copy-paste. The dashboard is where you build; the MCP server is where you ask.
It authenticates over OAuth 2.1 with PKCE and speaks Streamable HTTP (MCP spec 2025-03-26), so a hosted client connects with a sign-in pop-up and no token handling.
No competing AI-visibility platform ships an installable MCP server for AI assistants today.
Every comparable tool is a dashboard plus, at best, a REST API you write code against. None exposes its tracker as an MCP server you drop into an assistant. This is a specific, falsifiable claim — verified across the category in September 2026.
Your visibility data reaches the assistant you already brief, prompt and write in. Ask the number in the same thread where you draft the fix — no dashboard round trip.
Because it is MCP, your data joins whatever else the client can reach — your repo in Cursor or VS Code, your other connectors in Claude — so an agent can read your share of voice and act on it in one turn.
The server exposes your live AEO tracker as read-only tools any assistant can call.
Every analytics tool takes a parent_brand_id, so list_brands is always the first call — resolve the name to its id, then query. All tools are read-only except the two writers (the Quick Report audit and the llms.txt generator). The full contract for each tool lives in the reference.
list_brands
Resolve a brand name to the id every other tool needs.
get_brand_visibility, get_share_of_voice, get_competitors, get_leaderboard, get_platform_breakdown, get_sentiment_analysis, get_regional_visibility
Mention rate, share of voice, competitor rank, per-platform and per-region rollups.
get_citation_metrics, get_gpt_shopping_visibility
Top citing domains and category mix; visibility inside ChatGPT Shopping cards.
list_topics, list_prompts, get_prompt_responses
Drill from a tracked topic to the prompts and the actual AI answers, with citation URLs.
generate_visibility_audit, list_my_visibility_reports, get_visibility_report
Kick off a self-serve audit on any domain (runs ~20–30 min), poll, then fetch the full report.
generate_llms_txt
Generate an llms.txt for a site — it pairs naturally with the AEO workflow.
Add the endpoint once, and your assistant queries your visibility data in-context.
Settings → Connectors → Add custom connector → paste the URL → sign in when the OAuth pop-up appears.
Full steps in the docsRun claude mcp add --transport http asvaai https://mcp.asvaai.com/mcp, then confirm with claude mcp list.
Full steps in the docsAdd a server entry to ~/.cursor/mcp.json (or the per-project file); Cursor opens a browser to finish OAuth.
Full steps in the docsAdd an HTTP server to .vscode/mcp.json with the top-level servers key, click Start, then pick it in the Tools picker.
Full steps in the docsSettings → Cascade → MCP Servers, add the config with serverUrl, save and restart.
Full steps in the docsUse the HTTP transport URL directly, or bridge with npx mcp-remote. Spec-compliant clients self-register via Dynamic Client Registration.
Full steps in the docsChatGPT reaches your Asva workspace through a custom connector you enable in settings.
Asva AI, and paste the URL https://mcp.asvaai.com/mcp.A published ChatGPT app built on the Apps SDK is planned, not shipped. Today you connect Asva AI as the custom connector above; there is no published Asva AI app in the ChatGPT directory yet. We will update this page and the docs when that path is live.
Ask in plain language; the model picks the right tool and answers.
All numbers come from your live Asva workspace; the assistant cannot answer these from its training data — that is the point.
Every call is a short-lived OAuth bearer, scoped to brands you can access.
For the full data-handling policy, see the Privacy Policy and the Terms of Service.
Common questions about connecting Asva AI as an MCP server.
A Model Context Protocol endpoint that exposes your live AI-visibility data as tools any MCP client can call. Once connected, an assistant reads your Asva AI workspace and answers questions about mention rate, share of voice, citations, sentiment and competitor rank in natural language.
Claude (Web, Desktop and Code), ChatGPT, Cursor, VS Code (Copilot agent mode), Windsurf, and any MCP-compatible client via the HTTP transport. The full setup for each is in the docs at /docs/mcp.
No. Hosted clients authenticate through an OAuth pop-up, so you never paste a token. Self-hosted bridges use a token you generate in the dashboard.
Every call rides a short-lived OAuth 2.1 bearer, scoped to the brands you can access, audit-logged, and revocable from the Connectors page in your dashboard. The server stores no credentials.
No AI-visibility platform ships an installable MCP server today. Every comparable tool is a dashboard plus, at best, a REST API you write code against. The MCP server is unique to Asva AI as of September 2026.
No. This server reads your AI-visibility data. The separate agentic-commerce MCP (a different product on a different domain) lets AI agents transact against a product catalog. Different servers, different jobs.
Connect the endpoint to your assistant with the step-by-step docs, or run a free scan to see where your brand stands in AI search first.