JetBrains IDEs were among the last major editors to get full streamable HTTP support, which meant JetBrains users spent a long time watching the MCP ecosystem from the outside. That gap has closed. AI Assistant now connects to remote MCP servers over streamable HTTP directly, so ContextBolt SEO works in IntelliJ IDEA, WebStorm, PyCharm, PhpStorm, GoLand, RubyMine, and Rider with one config entry and no bridge.
One config, every IDE
The MCP panel lives inside AI Assistant rather than in any individual IDE, which is genuinely useful if you work across several. The same server entry lights up WebStorm for front-end work and PyCharm for the backend, and you configure it once.
Go to Settings, then Tools, then AI Assistant, then Model Context Protocol (MCP), and click Add:
{
"mcpServers": {
"contextbolt-seo": {
"type": "streamable-http",
"url": "https://seo.contextbolt.app/mcp/YOUR_TOKEN",
"headers": {}
}
}
}
Because your token sits in the URL path, the headers block stays empty. It is there for servers that expect a bearer token instead.
The hyphen that breaks configs
JetBrains expects streamable-http. Goose expects streamable_http. VS Code just wants http. All three describe the same transport, which means a config copied from a working setup in another tool looks entirely correct and quietly does nothing.
If you have pasted a config and the tools never appear, check that value before you check anything else. It accounts for most failed JetBrains MCP setups.
Recent releases also added auto-reconnect across all transports, so a dropped network connection no longer means re-adding the server by hand.
What this changes for backend-heavy teams
JetBrains users tend to be underserved by MCP content, because the ecosystem writes for VS Code and its forks. The practical effect is that SEO work gets done somewhere else entirely, in a dashboard, by a different person, usually after the page has shipped.
Having the tools in the IDE moves that decision earlier. You are building a marketing page in WebStorm, you ask what it should target, and you write the copy against a real query instead of a guess. When it ships, you ask for an audit and fix what comes back in the same session.
Plan before you build: keyword research and difficulty scoring, while the file is open.
Audit after you ship: point page_audit at the live URL and work the fix list.
Read your own data free: the Search Console tools never spend lookups, so checking what moved this month costs nothing.
The full tour is in the ContextBolt SEO guide, and the background on how an SEO MCP server works is worth ten minutes before you set one up.
How to connect ContextBolt SEO to JetBrains
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Subscribe and get your MCP URL
Subscribe to ContextBolt SEO ($35/month for 1,000 lookups). Your private MCP URL arrives by email and looks like https://seo.contextbolt.app/mcp/YOUR_TOKEN. Keep it private, like a password.
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Open the MCP settings panel
Go to Settings, then Tools, then AI Assistant, then Model Context Protocol (MCP). This panel is shared across every JetBrains IDE, so the same setup works in IntelliJ IDEA, WebStorm, PyCharm, PhpStorm, GoLand, RubyMine, and Rider.
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Add the server as streamable-http
Click Add and paste a config with type streamable-http and your MCP URL. Note the hyphen: JetBrains expects streamable-http, where Goose uses streamable_http with an underscore and VS Code just uses http. Copying between tools is where this usually goes wrong.
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Confirm the tools and connect Search Console
Apply the settings, open AI Assistant chat, and ask 'what SEO tools do you have?'. Then ask 'connect my Google Search Console' and approve read-only access to read your real clicks and positions. The Search Console tools are free and never spend your monthly lookups.
Example prompts for ContextBolt SEO + JetBrains
Once connected, try asking JetBrains:
Chains keyword_research and keyword_difficulty so you choose a target and see the realistic cost of competing for it.
Calls serp_overview and returns the live page-one results, so you can see the shape of what Google wants before writing.
Runs competitor_keywords and returns the gap list, turning your content backlog into something data-led.
Reads your own Search Console data to flag pages losing position, free and without spending lookups.
What you can do with ContextBolt SEO in JetBrains
Run keyword research in plain English inside any JetBrains IDE
Score how hard a keyword is to rank for before you write
See who ranks in Google's top 10 for any query
Size up any domain's traffic, keywords, and authority
Find the keywords a competitor already ranks for
Spot backlink gaps: who links to rivals but not you
Connect your own Google Search Console, read-only and free
One config that works across IntelliJ, WebStorm, PyCharm, and the rest