415 Tinyfish 03b55251

TinyFish

Research Date: 2026-02-23 Source URL: https://www.tinyfish.ai GitHub Repository: https://github.com/tinyfish-io/agentql-mcp (AgentQL MCP server, MIT) GitHub Repository (Cookbook): https://github.com/tinyfish-io/TinyFish-cookbook Version at Research: No versioned releases; API at https://agent.tinyfish.ai/v1 (current as of 2026-02-23) License: Commercial SaaS (AgentQL MCP server: MIT)

Overview

TinyFish is an enterprise serverless web agent API platform that enables AI agents to navigate, authenticate, extract, and transact on live websites at production scale. It eliminates the need to manage browser infrastructure, proxy configuration, or anti-bot evasion by bundling all costs — remote browsers, residential proxies, LLM inference, and anti-bot protection — into a single per-step price. The platform integrates natively with Claude and other LLM toolchains via an AgentQL MCP server, enabling agentic web scraping with a single API call.

Problem Addressed

Key Statistics

Key Features

Agentic Web Automation API

• Single REST endpoint: POST https://agent.tinyfish.ai/v1/automation/run-sse
• Natural-language goal parameter describes what to extract or do — no XPath or CSS selectors required
• Returns structured JSON (resultJson) automatically parsed from the live page
• Real-time progress streamed via Server-Sent Events (SSE); no polling required
• browser_profile: "stealth" parameter bypasses common anti-bot mechanisms

Parallel Execution at Scale

• Up to 1,000 simultaneous operations in a single plan tier
• Agent concurrency: 2 (free), 4 (Standard), 20 (Pro), unlimited (Enterprise)
• No cold start penalty — serverless infrastructure provisions on demand

Authentication and Form Handling

• Navigates behind logins, OAuth flows, and multi-step forms
• Residential proxy routing via proxy_config.country_code parameter for geo-restricted content
• Handles paywalls, CAPTCHA-challenged flows, and dynamic SPAs

AgentQL MCP Server

• Open-source MCP server (tinyfish-io/agentql-mcp, MIT license, 148 stars)
• Provides extract-web-data tool: structured data extraction from any URL using a natural-language prompt
• Compatible with Claude Desktop, Claude Code, VS Code, Cursor, and Windsurf
• Installed via npm install -g agentql-mcp; authentication via AGENTQL_API_KEY

Visual Workflow Builder (Workbench)

• No-code visual builder for defining multi-step agent workflows
• Agent observability with screenshots at each automation step
• Full run history with query and pagination options via list_runs API

Inclusive All-in Pricing

• Remote browser infrastructure: $0/hour
• Residential proxy bandwidth: $0/GB
• LLM inference costs included — no separate AI API bill
• Anti-bot protection included in every plan tier

Technical Architecture

Claude Code / Agent
       |
       v
AgentQL MCP Server (npx agentql-mcp)          OR       Direct REST API
  tool: extract-web-data                                POST /v1/automation/run-sse
       |                                                        |
       v                                                        v
TinyFish Web Agent API  (https://agent.tinyfish.ai/v1)
  - Serverless browser provisioning
  - Anti-bot evasion / stealth profiles
  - Residential proxy routing
  - LLM-driven navigation and extraction
  - Structured JSON result assembly
       |
       v
SSE Stream  (real-time event progress)
  data: { "type": "PROGRESS", ... }
  data: { "type": "COMPLETE", "status": "COMPLETED", "resultJson": {...} }

Key design decisions:

• Bundled cost model: eliminates the "browser + proxy + LLM = three bills" problem common to DIY stacks
• SSE over polling: progress events arrive continuously without client polling loops
• Goal-oriented API: agent describes the desired data in plain English; TinyFish handles DOM traversal, clicks, and form fills internally
• MCP-first integration: the AgentQL MCP server is first-class, not an afterthought — directly usable from Claude without any REST client code

Installation & Usage

AgentQL MCP Server (Claude Code / Claude Desktop)

npm install -g agentql-mcp

Claude Desktop configuration (claude_desktop_config.json):

{
  "mcpServers": {
    "agentql": {
      "command": "npx",
      "args": ["-y", "agentql-mcp"],
      "env": {
        "AGENTQL_API_KEY": "YOUR_API_KEY"
      }
    }
  }
}

Direct REST API (JavaScript)

const response = await fetch("https://agent.tinyfish.ai/v1/automation/run-sse", {
  method: "POST",
  headers: {
    "X-API-Key": process.env.TINYFISH_API_KEY,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    url: "https://example.com/products/",
    goal: "Extract all products: name, price, and stock status",
  }),
});

for await (const line of response.body) {
  const text = new TextDecoder().decode(line);
  if (text.startsWith("data: ")) {
    const event = JSON.parse(text.slice(6));
    if (event.type === "COMPLETE") console.log(event.resultJson);
  }
}

Direct REST API with Stealth and Proxy

body: JSON.stringify({
  url: "https://geo-restricted-site.com",
  goal: "Extract pricing data",
  browser_profile: "stealth",
  proxy_config: { enabled: true, country_code: "US" },
})

cURL (quick test)

curl --location 'https://agent.tinyfish.ai/v1/automation/run-sse' \
  --header 'Content-Type: application/json' \
  --header "X-API-Key: $TINYFISH_API_KEY" \
  --data '{"url": "https://amazon.com", "goal": "Find the price of AirPods Pro 3"}'

Relevance to Claude Code Development

Applications

• Claude Code research skills that need live data from dynamic or authenticated sites can use TinyFish instead of WebFetch, which cannot handle JavaScript-heavy pages or login walls
• Skills performing competitive analysis, price monitoring, or regulatory filing extraction can run hundreds of parallel site queries without managing browser infrastructure
• The AgentQL MCP server (extract-web-data tool) can be added to any Claude Code plugin, instantly enabling structured web data extraction without custom REST client code

Patterns Worth Adopting

• Goal-oriented extraction over selector-based scraping: passing a plain-English goal rather than CSS/XPath selectors is resilient to DOM changes and transfers directly to agent skill prompts
• SSE streaming for long-running agent tasks: the SSE event pattern (PROGRESS → COMPLETE) is a clean model for any skill that needs to surface intermediate results during multi-step agent workflows
• All-in cost bundling: designing agent infrastructure with bundled costs (browser + proxy + inference = one bill) reduces operational complexity and surprise overages — a pattern worth considering when building Claude Code plugins that consume external paid APIs
• MCP tool as first-class integration: the MCP server model with a single extract-web-data tool is a minimal, focused API surface that works cleanly with Claude's tool-use patterns

Integration Opportunities

• Web research skill: a web-research Claude Code skill could wrap the AgentQL MCP extract-web-data tool for structured extraction from any URL — replacing brittle regex-over-HTML approaches
• Competitive intelligence agent: an agent skill that runs parallel TinyFish operations against a list of competitor URLs and returns a structured comparison — enabled by the 1,000-concurrent-op ceiling
• Authenticated data agent: skills requiring session-based access to dashboards (analytics portals, SaaS admin pages) could use TinyFish's login handling rather than maintaining credential state manually
• Agentic form-filling workflow: a skill pattern for submitting structured data through multi-step web forms (insurance quotes, government portals, job applications) at scale

References

• TinyFish homepage (accessed 2026-02-23)
• TinyFish documentation (accessed 2026-02-23)
• TinyFish scraping examples (accessed 2026-02-23)
• TinyFish pricing (accessed 2026-02-23)
• agentql-mcp GitHub repository (accessed 2026-02-23)
• TinyFish Cookbook GitHub repository (accessed 2026-02-23)
• AgentQL MCP Server on MCP Server Hub (accessed 2026-02-23)

Freshness Tracking