About optiqra-mcp
optiqra-mcp wraps OptiQra’s website auditing and AI analysis API as an MCP server for compatible AI clients. It covers SEO, GEO, AEO, performance, accessibility, and security, and can generate fixes for reported issues.
Key features
- 01Crawl URLs for comprehensive audits
- 02Generate AI fixes for report issues
- 03Create site-wide AI strategy summaries
- 04Test AI provider configuration
Use cases
- 01Review a site's SEO and security
- 02Get fixes for issues found in an audit
MCP support
The MCP server exposes four OptiQra API endpoints as tools for MCP clients.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
npx -y optiqra-mcpOPTIQRA_BASE_URLBase URL of the OptiQra instance to call. Defaults to https://optiqra.vercel.app.OPTIQRA_PROVIDER_API_KEYSecretDefault AI-provider API key used by the ai-fix/ai-insights/ai-test tools if the caller doesn't pass one.OPTIQRA_TIMEOUT_MSRequest timeout in milliseconds. Defaults to 120000.Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.
Tools
4Saved tool list · updated 2w ago
| Parameter | Type | Required | Description |
|---|---|---|---|
| url | string | Yes | The URL of the website to analyze, e.g. https://example.com |
Details
From the project READMEoptiqra-mcp
An MCP (Model Context Protocol) server that exposes every tool in OptiQra's API to MCP-compatible AI clients (Claude Desktop, Claude Code, Cursor, etc.).
OptiQra has four HTTP endpoints. This server wraps all four as MCP tools:
| Tool | OptiQra endpoint | What it does |
|---|---|---|
optiqra_analyze | POST /api/analyze | Crawls a URL and runs the full SEO/GEO/AEO/perf/a11y/security audit |
optiqra_ai_fix | POST /api/ai-fix | Generates an AI-written fix for one issue from a report |
optiqra_ai_insights | POST /api/ai-insights | Generates a site-wide AI strategy summary across a full report |
optiqra_ai_test | POST /api/ai-test | Verifies a provider/API key/model combo works before using the two above |
By default it talks to the public demo, https://optiqra.vercel.app. Point
it at your own deployment (see OptiQra's own DEPLOYMENT.md/Docker setup)
with an env var — see below.
Install
npm install
(or, once published, npm install -g optiqra-mcp / run directly with npx optiqra-mcp)
Configuration (environment variables)
| Variable | Required | Purpose |
|---|---|---|
OPTIQRA_BASE_URL | No | Base URL of the OptiQra instance to call. Defaults to https://optiqra.vercel.app. |
OPTIQRA_PROVIDER_API_KEY | No | A default AI-provider API key used by optiqra_ai_fix/optiqra_ai_insights/optiqra_ai_test if the model doesn't pass one. Recommended over letting the model handle the key in plaintext. |
OPTIQRA_TIMEOUT_MS | No | Request timeout in ms. Defaults to 120000 (full-site crawls can be slow). |
Run it standalone
node src/index.js
It speaks MCP over stdio, so you won't see anything happen — it's waiting for an MCP client to connect.
Wire it into an MCP client
Claude Desktop / Claude Code
Add to your MCP config (claude_desktop_config.json, or via claude mcp add
for Claude Code):
{
"mcpServers": {
"optiqra": {
"command": "node",
"args": ["/absolute/path/to/optiqra-mcp/src/index.js"],
"env": {
"OPTIQRA_BASE_URL": "https://optiqra.vercel.app",
"OPTIQRA_PROVIDER_API_KEY": "sk-..."
}
}
}
}
Any other MCP-compatible client (Cursor, Windsurf, etc.) uses the same
`command`/`args`/`env` shape — check that client's docs for where the config
file lives.
## Notes on the AI-key tools
`optiqra_ai_fix`, `optiqra_ai_insights`, and `optiqra_ai_test` all need a
provider API key, exactly like pasting one into OptiQra's own UI — OptiQra's
server forwards it straight to the provider (OpenAI, Anthropic, Google, Groq,
OpenRouter, Mistral, DeepSeek, or xAI) and never stores it. This server does
the same: it never persists keys. Prefer setting `OPTIQRA_PROVIDER_API_KEY`
in your MCP client's env config over having the model pass a key through
chat.
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.