SEOBolt exposes audit, issues, fix-plan, and checkout tools over MCP. Your agent can inspect the crawl, update your repo, and trigger another crawl to verify the result.
Crawler-backed checks, not marketing copy: audits now emit AI Search issues into dashboard reports, fix plans, REST API responses, and MCP tools.
Create an API key and configure the SEOBolt MCP server.
Run seo_start_crawl from the agent session.
Call seo_fix_plan and let the coding agent patch the repo.
Run seo_audit after deployment to confirm the health score moved.
Traditional SEO still matters, but AI search adds new failure modes: blocked AI crawlers, missing entity context, thin llms.txt files, and pages that answer engines cannot cite. SEOBolt reports those as first-class audit issues with fix templates.
{
"mcpServers": {
"seobolt": {
"command": "npx",
"args": ["-y", "mcp-server-seobolt"],
"env": {
"SEOBOLT_API_KEY": "sk_live_your_key"
}
}
}
}Every MCP tool maps to an authenticated API endpoint with API-key rate limits.
The agent does not need to interpret a PDF; it receives snippets and affected URLs.
SEOBolt is built around re-crawling after fixes, not stopping at the audit.
SEOBolt's Model Context Protocol (MCP) server enables AI coding agents (Claude, Cursor, Codex) to run site audits, retrieve structured fix plans with code snippets, patch repository files, and trigger re-crawls directly inside your coding workflow.
The MCP server includes tools like seo_projects, seo_start_crawl, seo_audit, seo_issues, seo_fix_plan, seo_fix_suggestions, and seo_content_score.
Pass your SEOBolt API key as SEOBOLT_API_KEY in your agent's MCP server environment configuration.
Check your homepage for AI search access, llms.txt quality, crawler rules, structured data, Open Graph, canonical tags, and the first fixes to apply.
Run the audit