AnswerixAI ships a Model Context Protocol server at /api/mcp on your AnswerixAI host so AI assistants can query your brand visibility data through natural-language conversation. No npm package, no local process — just a URL and an API key.
Generate an API key
- Open your AnswerixAI dashboard → Settings → API Keys
- Click New key, give it a memorable name (e.g. Claude — laptop)
- Copy the token (it starts with
ans_). It's shown once — store it in your password manager
Connect Claude Desktop
Edit ~/Library/Application Support/Claude/claude_desktop_config.json (macOS) or %APPDATA%\Claude\claude_desktop_config.json (Windows):
{
"mcpServers": {
"answerix": {
"url": "https://your-answerix-host/api/mcp",
"headers": {
"Authorization": "Bearer ans_..."
}
}
}
}
Restart Claude Desktop. Type "List my AnswerixAI brands" — Claude should call the list_brands tool and show your brands inline.
Connect Claude Code
claude mcp add answerix --transport http https://your-answerix-host/api/mcp \
--header "Authorization: Bearer ans_..."
Self-host? Point at your own instance
The MCP endpoint lives at /api/mcp on whatever host runs the AnswerixAI app. If you self-host at answerix.mycompany.internal, use that base URL instead.
Available tools
| Tool | What it does |
|---|---|
list_brands |
List brands the authenticated user can access. |
get_visibility_summary |
Aggregate visibility score, mentions, citations, top competitors for a brand over an optional date range / model / region. |
get_visibility_trend |
Day-by-day visibility series for charting movement over time. |
list_topics |
List the topics on a brand with a prompt count per topic. Use for coverage audits (empty / over-concentrated topics). |
list_prompts |
List the prompts tracked on a brand, optionally filtered by topic, active status, or capped via limit. |
get_prompt_performance |
Per-prompt visibility with platform breakdown. |
get_prompt_volumes |
Estimated AI search volumes for tracked prompts. |
list_citations |
The URLs AI engines cite alongside the brand, with source-type classification. |
get_competitor_comparison |
Side-by-side visibility vs. named competitors. |
get_ai_traffic |
Real visits arriving from AI answer engines (pixel data). |
list_content_opportunities / get_content_opportunity |
Content gaps ranked by opportunity score. |
generate_content_brief |
Generate (or fetch the cached) structured editorial brief for an opportunity. |
update_opportunity_status |
Move an opportunity between new / sent / in_progress / done / dismissed. |
list_shopping_cards / get_product_visibility |
Product card presence in shopping-style AI answers. |
run_site_audit / list_site_audits / get_site_audit / get_site_audit_quota |
Trigger and inspect AI-readability site audits. |
Try it
Ask your client things like:
- "List my AnswerixAI brands."
- "What's my visibility score on ChatGPT for the last 7 days?"
- "Are my topics balanced?" / "Which topic has the most prompts?"
- "Show me the prompts in my pricing topic."
- "Who are my top 5 competitors by mention count this month?"
- "Run a site audit on my primary domain and summarize the weakest category."
The model picks the right tool, fills in the brand id and filters, and answers in plain English using the returned data.
REST mirrors
Every MCP tool is also exposed as a plain REST endpoint under /api/mcp/* (e.g. GET /api/mcp/brands, GET /api/mcp/visibility-summary?brand_id=…) using the same ans_ bearer key — handy for scripts and integrations that don't speak MCP. See the API reference.
Revoking access
If a key leaks or you stop using a client, open Settings → API Keys and click the trash icon. Clients using that key lose access immediately.
Transport
The server speaks the MCP Streamable HTTP transport in stateless mode — every request is self-contained, no session state is kept between calls. This makes it work cleanly behind any HTTP load balancer.