MCP server
Connect Claude, Cursor, Codex and other AI agents to DeepScout with the Model Context Protocol.
The DeepScout MCP server gives AI agents the same functions as the API. An agent can add a website, read the sample data, scrape a catalog, match products and get the export files. You write what you want in plain language, and the agent calls the API for you.
The server follows the authenticated remote MCP specification. DeepScout hosts it, so you install nothing. Clients that support remote MCP servers connect directly. Other clients connect through the mcp-remote module.
https://mcp.deepscout.ai/mcpSetup
General
The server uses the Streamable HTTP transport. The sign-in uses OAuth 2.1 with dynamic client registration:
- Add the server URL to your client.
- Start the sign-in in the client. The client opens the DeepScout Console in your browser.
- Sign in with Google or GitHub. Your first sign-in creates your account.
- Read the name of the app and click Approve.
The app gets an API key with the scope All my projects. The key does not expire. You can see the app and disconnect it in the console, under Settings → API keys → Connected apps.
You can also send your own API key in the Authorization header and skip the sign-in. See Use an API key.
Claude Code
claude mcp add --transport http deepscout https://mcp.deepscout.ai/mcpStart a Claude Code session and run /mcp. Select deepscout, then Authenticate.
Claude
In claude.ai or in Claude Desktop, open Settings → Connectors and click Add custom connector. Enter the name DeepScout and the server URL. Then click Connect to sign in.
In a Team or Enterprise organization, an owner adds the connector for the organization first. Then each member connects with their own DeepScout account.
Codex
Codex keeps one configuration for the CLI and the IDE extension. Add the server:
codex mcp add deepscout --url https://mcp.deepscout.ai/mcpIf Codex does not open the sign-in, run codex mcp login deepscout.
You can also add the server to ~/.codex/config.toml:
[mcp_servers.deepscout]
url = "https://mcp.deepscout.ai/mcp"Cursor
Add the server to ~/.cursor/mcp.json, or to .cursor/mcp.json in your project:
{
"mcpServers": {
"deepscout": {
"url": "https://mcp.deepscout.ai/mcp"
}
}
}Open Cursor Settings → MCP and click Connect next to deepscout.
Visual Studio Code
Add the server to .vscode/mcp.json in your workspace:
{
"servers": {
"deepscout": {
"type": "http",
"url": "https://mcp.deepscout.ai/mcp"
}
}
}Click Start above the server in the file. VS Code opens the sign-in.
Other clients
If your client supports remote MCP servers, give it the server URL. If it supports only local (stdio) servers, use mcp-remote with these settings:
- Command:
npx - Arguments:
-y mcp-remote https://mcp.deepscout.ai/mcp - Environment: none
{
"mcpServers": {
"deepscout": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://mcp.deepscout.ai/mcp"]
}
}
}mcp-remote needs Node.js 18 or later.
Tools
Each tool is one step of the API. The tools call the API as you, with the key of the client. So they see the same projects and get the same errors as your requests.
| Tool | What it does | API |
|---|---|---|
scout_list_projects | Lists your projects and the customer that pays for each one. | GET /projects |
scout_list_websites | Lists the websites of a project, each with its current job and full_scrape_estimate. | GET /websites |
scout_analyze_website | Adds a website to a project. The setup job analyzes it and scrapes free sample products. | POST /jobs/setup |
scout_get_job | Reads a setup, scraping or matching job: status, progress, estimate and charge. | GET /jobs/{kind}/{job_id} |
scout_get_sample | Gives a temporary URL of the sample products of a website. | GET /samples/{website_id} |
scout_scrape_website | Creates a scraping job for the full catalog or for a list of product URLs. | POST /jobs/scraping |
scout_get_url_results | Gives a temporary URL of the CSV file with the result of each URL of a URL scrape. | GET /jobs/scraping/{job_id}/url-results |
scout_match_websites | Creates a matching job, or the free matching sample of the project. | POST /jobs/matching |
scout_approve_job | Approves a scraping or matching job. This charges your credit. | POST /jobs/{kind}/{job_id}/approve |
scout_list_exports | Lists the export files of a project. | GET /exports |
scout_get_export | Gives a temporary URL of one export file. | GET /exports/{dataset}/url |
scout_get_balance | Reads the credit of a customer: the total, the held part and the spendable part. | GET /customers/{customer_id}/billing/balance |
The tools that only read data (scout_list_*, scout_get_*) have the MCP annotation readOnlyHint. You can let your client run them without a prompt. The other tools create or approve jobs. They do not remove or overwrite data.
The server also gives the agent the order of the steps and the usual duration of each job. A scrape of 100,000 products can take one day. The agent knows this and does not report a slow job as a problem.
Sample data, the matching sample and most website analyses are free. A scrape or a matching costs the same as through the API. See Pricing.
Approvals use your credit
Only scout_approve_job charges your credit. The server tells the agent to show you the price and to wait for your answer before it approves a job. Keep the confirmation prompt of your client on for this tool.
Example prompts
Copy a prompt into your client and change the values in brackets. Each prompt names the data that the agent needs, so the agent asks fewer questions.