MCP Server

Connect AI agents to Digispot crawl data over the Model Context Protocol — the client list, the config each one expects, and what the server exposes.

The Digispot MCP server exposes crawl data to any MCP-compatible AI client. A connected agent queries findings, starts crawls, and drafts fixes without anything being copied between tools.

Configuration is generated for you. Open a project in Spider and use Connect AI agent, or Settings → MCP Server, then pick your client. The snippets below show the shape so you know what you are pasting.

Two server variants

	Desktop Spider	Cloud Platform
Transport	stdio (local process)	HTTP (remote)
Scope	One project, enforced	Cloud account
Tools	64	Varies by plan
Auth	`--project <id>` binding	API key from Settings
Requires	Spider running, Tracker or Leader	Cloud Starter or above

Use the Desktop Spider server when crawl data lives on your machine and must stay there. Use the Cloud server when crawls run on Digispot's servers or a team shares access.

Desktop Spider: local stdio server

The server is a native binary shipped inside the app. Its filename is architecture-specific (mcp-macos-arm64, mcp-macos-x64, mcp-win-x64.exe, mcp-linux-x64), and the app resolves the right one for the current machine.

Every server is bound to one project. The --project argument takes a project id and is mandatory — the server refuses to start unbound, and no tool accepts a project id as a parameter, so an agent cannot reach another project.

Clients

Each client reads a different file, and VS Code uses a different wrapper key.

Client	Where the config goes	Wrapper key
Claude Code	`claude mcp add` (no file to edit)	—
Cursor	`~/.cursor/mcp.json`	`mcpServers`
Windsurf	`~/.codeium/windsurf/mcp_config.json`	`mcpServers`
VS Code (Copilot)	`.vscode/mcp.json` in the repo	`servers`
Claude Desktop	`~/Library/Application Support/Claude/claude_desktop_config.json`	`mcpServers`

For the JSON clients the entry is the same shape. Only the wrapper key changes:

~/.cursor/mcp.json

{
  "mcpServers": {
    "digispot-spider": {
      "command": "/path/to/mcp-macos-arm64",
      "args": ["--project", "<projectId>"]
    }
  }
}

Claude Code registers stdio servers through the CLI instead of a pasted file:

claude mcp add digispot-spider --scope local -- /path/to/mcp-macos-arm64 --project <projectId>

The -- matters. It separates Claude's own flags from the binary's arguments; without it --project is parsed by claude and the command fails. Run it from inside the repo so local scope binds the server to that folder. Use --scope project to write a committed .mcp.json the team shares.

Claude Desktop has a single global config with no per-project scope, so a binding there applies to every Claude Desktop conversation. Prefer a repo-scoped client when you work across several projects.

The server exposes 64 tools covering crawls, pages, issues, Google data, prioritization, workflows, and the Knowledge base, plus 8 packaged SEO skills registered as MCP prompts. See Spider's MCP server for the full reference.

Cloud Platform: HTTP server

The cloud server is reached over HTTP with a key instead of a local binary. It queries cloud data: projects and remaining credits, audit results and top issues, keyword and backlink data, Google metrics, and content opportunities.

Create and revoke keys under API access in the Cloud Platform, which also shows the connection details for your account. See Keys & connections.

A cloud key reaches your whole account. Keep it in an environment variable or a secrets manager, never in version control.

What to ask an agent

With a project bound, the agent works against real crawl data:

"What are the top 10 issues by severity?"
"Which pages fail Core Web Vitals on mobile?"
"Show pages missing a meta description and draft one for each."
"Start a crawl and tell me when it finishes."
"Which pages get the most traffic but fail structured-data checks?"

The last one is where MCP earns its place. The agent pulls traffic data, cross-references failing checks, and returns a prioritized plan in one response instead of you exporting two reports and joining them by hand.