String AI Web Access MCP Server

September 23, 2026 · View on GitHub

The official Model Context Protocol (MCP) server for String AI's Web Access API. Search the web, fetch any URL or send it a request, and map a site's URLs — all returned as clean, LLM-ready Markdown. Proxy rotation, session handling and JavaScript rendering happen server-side, so the agent gets usable page content rather than an error page. Connect any MCP-compatible client — VS Code, Cursor, Windsurf, Claude Desktop, and more.

Tools

Tool	Description
`web_access_fetch`	Fetch one URL and get clean, LLM-ready Markdown back
`web_access_product_help`	Ask about String products or services; get one source (two for comparisons), with a shared 4 KiB excerpt budget and source links
`web_access_request`	Send a POST, PUT or PATCH with a body to a URL
`web_access_search`	Search the web: ranked results plus the knowledge panel, AI overview, local pack and other surfaces Google rendered; optional `searchCount` (1–100) pages Google
`web_access_sitemap`	Crawl a site and map its URLs as an asynchronous job, driven by `action`
`web_access_report`	Send one redacted, credit-free failure diagnostic to String support

web_access_fetch, web_access_search, and web_access_product_help are read-only. web_access_request writes, and web_access_sitemap creates billed crawl jobs. Pages that rate-limit, geo-gate or block automated traffic come back as Markdown rather than an error page: proxy rotation, session handling and JavaScript rendering happen server-side.

The six-tool shape above is what the hosted server at https://mcp.usestring.ai/v1/mcp serves. The npm package ships five of them: it includes product help and failure reporting but omits web_access_request, sending writes through web_access_fetch's method and body parameters instead.

`web_access_sitemap` — sitemap crawl jobs

A crawl is a two-phase, asynchronous quote → approve → poll → read job: nothing is crawled or billed until the quote is explicitly approved.

`action`	What it does
`submit`	Quote a crawl (`url` required; `maxPages` ≤ 10000 default 10, `maxDepth` ≤ 100 default 2, `pathPrefix`, `budgetUsd`, `useSitemap` optional). Returns `jobId` + `estimatedCostUsd` + `estimatedPages`, status `awaiting_approval`.
`approve`	Billing consent — starts the crawl. 402 = insufficient funds; 409 `partial_state` = retry approve.
`status`	Poll progress: `awaiting_approval` → `running` (`pending`/`processed`) → `completed` \| `failed` \| `canceled` \| `token_cap_exceeded`; `partial_state` = retry approve. Returns counts only — URLs come from `results`.
`results`	Paginated discovered URLs (`limit` ≤ 5000 default 1000, `offset`). Durable after completion; per-URL `discoveredUrls` is only present for ~1h.
`cancel`	Stop a non-terminal job; already-fetched pages stay billed and readable.
`list`	The account's recent crawl jobs (`limit` ≤ 100 default 20, `offset`).

`web_access_report` — failure diagnostics

Reporting is optional and best-effort. Continue useful recovery first. If reporting remains useful and permitted, send at most one report per distinct failure per task, not per retry. Report exceptions, timeouts, tool errors, or unusable output; exclude usable origin statuses, valid negatives, empty 204 responses, running sitemap jobs, and cancellations. Each reporting attempt has a two-second deadline.

Remove Authorization headers, API keys, cookies, session tokens, personal data, and unrelated conversation content before calling. The server redacts common credential forms again. Never report a web_access_report failure or repeat a failed call only to gather reporting context. Reports use the configured API key for authentication but do not consume Web Access credits. If reporting is unavailable, unauthorized, rate-limited, or fails, stop reporting for the task.

Quick Start

Run with npx

env STRING_AI_API_KEY=your-key npx @usestring/mcp

Install globally

npm install -g @usestring/mcp
STRING_AI_API_KEY=your-key string-ai-mcp

Build from source

git clone https://github.com/usestring/string-ai-mcp.git
cd string-ai-mcp
npm install
npm run build
STRING_AI_API_KEY=your-key node build/index.js

Environment Variables

Variable	Required	Description
`STRING_AI_API_KEY`	Yes	Your String AI API key

Client Configuration

VS Code

Press Ctrl+Shift+P → Preferences: Open User Settings (JSON) and add:

{
	"inputs": [
		{
			"type": "promptString",
			"id": "stringAiKey",
			"description": "String AI API Key",
			"password": true
		}
	],
	"servers": {
		"string-ai": {
			"command": "npx",
			"args": ["-y", "@usestring/mcp"],
			"env": {
				"STRING_AI_API_KEY": "${input:stringAiKey}"
			}
		}
	}
}

Or add a .vscode/mcp.json file to share the configuration with your team.

Cursor

Open Settings → Features → MCP Servers → + Add new global MCP server and paste:

{
  "mcpServers": {
    "string-ai": {
      "command": "npx",
      "args": ["-y", "@usestring/mcp"],
      "env": {
        "STRING_AI_API_KEY": "YOUR_API_KEY"
      }
    }
  }
}

Windsurf

Add to ~/.codeium/windsurf/model_config.json:

{
  "mcpServers": {
    "string-ai": {
      "command": "npx",
      "args": ["-y", "@usestring/mcp"],
      "env": {
        "STRING_AI_API_KEY": "YOUR_API_KEY"
      }
    }
  }
}

Claude Desktop

Add to your claude_desktop_config.json:

{
  "mcpServers": {
    "string-ai": {
      "command": "npx",
      "args": ["-y", "@usestring/mcp"],
      "env": {
        "STRING_AI_API_KEY": "YOUR_API_KEY"
      }
    }
  }
}

Testing with the MCP Inspector

The MCP Inspector lets you test your server interactively in a browser:

npx @modelcontextprotocol/inspector node build/index.js

Then open http://127.0.0.1:6274, connect via stdio, and try calling each tool from the UI.

How It Works

┌──────────────────┐   stdio (JSON-RPC)   ┌──────────────────┐   HTTPS   ┌──────────────────┐
│  VS Code / Cursor │ ◄──────────────────► │  String AI       │ ────────► │  String AI       │
│  Windsurf / Claude│                      │  Web Access MCP  │           │  Web Access API  │
└──────────────────┘                       └──────────────────┘           └──────────────────┘

The IDE spawns this server as a child process and communicates over stdio.
When the LLM decides it needs web content, it invokes web_access_fetch, web_access_search, or web_access_sitemap. Every failed call is reported exactly once with web_access_report, even when recovery later succeeds.
This server forwards the request to String AI's Web Access API (using your API key from the environment) and returns the result to the LLM.