Fresh web search
Search returns fresh URLs from the live web and is described as real browser-rendered search that can return structured JSON from dynamic pages and fast-changing sources.
TinyFish
RevendiquerTinyFish is an enterprise platform for AI web agents with live search, page fetching, browser automation, and multi-step workflows for dynamic sites at scale.
Overview
TinyFish is enterprise infrastructure for AI web agents. It combines Search, Fetch, Browser, and Agent capabilities into a single platform for web search, page extraction, browser automation, and workflow execution.
The product is designed for teams that need to work with live websites at scale, including dynamic pages, authenticated flows, and structured outputs. The homepage emphasizes a fully serverless architecture and describes the platform as suitable for running many websites simultaneously.
Core capabilities
Clean page extraction
Fetch renders a page in a real browser and returns clean markdown, JSON, or HTML, so downstream systems can work with the page as it actually appears.
Multi-step web automation
Agent can navigate pages, fill forms, authenticate into sites, and return structured results for production workflows that need multi-step execution.
Stealth browser sessions
Browser provides stealth sessions for login walls, anti-bot protections, and dynamic rendering, with persistent state and fast cold starts described on the page.
Parallel execution at scale
The platform is presented as serverless and able to run hundreds of websites simultaneously, which supports large-scale parallel web workflows.
Multiple integration paths
TinyFish is MCP-native and also exposes direct API access, with examples for Claude Code, CLI tools, npm, Python, Cursor MCP, AG2, and Vercel.
Typical use cases
Web research and monitoring
Use Search to find live results from the web, then Fetch to turn pages into clean content for research pipelines, monitoring, or news-driven workflows.
Authenticated workflow automation
Use Browser and Agent to sign in, navigate dynamic interfaces, and submit forms when a task depends on authenticated portals or interactive pages.
Structured data extraction
Use Fetch to convert rendered pages into markdown, JSON, or HTML for downstream models and data pipelines that need structured page content.
High-volume web operations
Use the platform for parallel jobs across many websites when teams need to run the same workflow repeatedly at scale.
Agent stack integration
Use the MCP and API options to add live web capabilities to agent stacks such as Claude Code, Cursor, or custom Python and npm workflows.
Pros and Cons
Pros
- Combines search, fetch, browser automation, and agent execution in one platform.
- Supports live web access rather than relying only on cached or static content.
- Returns structured outputs such as JSON, markdown, or HTML from fetched pages.
- Includes stealth browser sessions for login-protected or anti-bot-protected sites.
- Is positioned for parallel, serverless execution across many websites.
Cons
- The pricing page was blocked by security verification in the collected sources, so plan details and pricing structure are not visible.
- The integrations and compare pages were also blocked, limiting verification of the full connector list and comparison claims.
FAQ
What is TinyFish?
TinyFish provides enterprise infrastructure for AI web agents, including Search, Fetch, Browser, and Agent capabilities. The site describes it as a single API for web search, page fetching, browser automation, and multi-step workflows.
How can TinyFish be integrated into a workflow?
The source describes TinyFish as MCP-native and available through direct API access. It also shows examples for Claude Code, CLI, npm, Python, Cursor MCP, AG2, and Vercel, but does not provide a full supported integrations list from the blocked integrations page.
What kinds of tasks is TinyFish designed for?
TinyFish is positioned for tasks that depend on dynamic pages, authenticated flows, structured outputs, and production reliability. The site highlights use cases such as research pipelines, monitoring, web automation, and agent workflows that need a real browser.
Is pricing available from the source?
The pricing page is behind security verification in the collected sources, so the exact plan structure, limits, and billing details are not visible. The home page does state that Search and Fetch are free API access for agents and that both are included on every plan and use no credits.
Quick Facts
- Category
- AI Web Agents
- Platform
- Serverless web automation platform
- Primary users
- Teams building web agents and automation workflows
- Core modules
- Search, Fetch, Browser, Agent
- Integration style
- MCP-native and direct API
- Source domain
- mino.ai
Alternatives à TinyFish
Termo
Termo is an AI agent platform with dedicated VMs for browsing, code execution, memory, and scheduled automation for research and build tasks.
Orca
Orca is an Agent Development Environment for shipping with coding agents, running multiple CLI agents in parallel across isolated worktrees, with desktop and mobile workflows.
AI Magicx
AI Magicx is a unified AI workspace for chat, image, video, voice, music, email and developer tasks, helping teams and creators manage multiple models in one place.
Paper
Paper is a design tool that connects canvas, code, and AI agents so teams can create, share, and ship work in one workflow. Includes desktop app and MCP access.
blop
blop is a QA agent that writes browser tests as code in your repo, runs them in CI, clusters repeated failures, and can open PRs to fix broken tests.
RLAMA
RLAMA is a local AI platform for building RAG systems and intelligent agents on macOS, Linux, and Windows, with HTTP API support.