Internet search and content material retrieval have quietly turn into a very powerful infrastructure choices in AI agent growth. Brokers with out dependable entry to stay net knowledge are successfully working on outdated data. This can be a extreme limitation for manufacturing deployments that deal with analysis, lead enrichment, aggressive intelligence, or real-time monitoring. In 2026, the search and fetch API ecosystem has matured significantly, with specialised instruments changing the previous sample of wrapping uncooked Google SERP knowledge and passing it on to language fashions.
This text describes the highest search and fetch APIs based mostly on our analysis throughout output codecs, agent-native design, token effectivity, free tier generosity, latency, and framework integration.
tiny fish
TinyFish is a crucial entrant into this area and probably the most direct agent-native within the group. Its search and retrieval endpoints are free, have beneficiant fee limits, one API key, and no bank card required. The free plan consists of searches at 5 requests/minute and retrieval at 25 requests/minute. Search is powered by api.search.tinyfish.ai and returns rank-stable structured JSON tailor-made for agent search fairly than human shopping. TinyFish states that the p50 search delay is lower than 0.5 seconds. That is quick sufficient to suit inside the agent’s device loop with out degrading the person expertise. Powered by api.fetch.tinyfish.ai, Fetch performs true full-browser rendering on any URL, together with JavaScript-heavy SPAs, dynamic content material, and anti-bot pages, and returns clear markdown, JSON, or HTML. Failed URLs are free.
The token effectivity angle would be the strongest differentiator. Most native fetch instruments (and the built-in fetches in LLM shoppers) return uncooked HTML, together with scripts, navigation, advertisements, and cookie banners. TinyFish Fetch removes all of this earlier than the content material reaches the mannequin, lowering token consumption per web page and LLM value per name. The platform operates your personal customized Chromium fleet end-to-end with out middleware, enabling each free pricing and output high quality. Importantly, these are the identical endpoints that drive the manufacturing agent workload, not a degraded demo tier. Even for those who transfer past the free plan, the identical API key and dashboard will carry over. No code adjustments required.
TinyFish is on the market for all surfaces that builders are already utilizing. Direct entry is by way of the REST API (api.search.tinyfish.ai and api.fetch.tinyfish.ai). MCP help is a single JSON configuration drop-in for Claude, Cursor, Codex, ChatGPT Desktop, or any MCP-enabled consumer. The CLI (npm set up -g @tiny-fish/cli) writes outcomes on to the file system fairly than piping them by means of the mannequin’s context window, preserving token utilization low and offering structured output. The agent talent (npx talent add github.com/tinyfish-io/tinyfish-cookbook –talent tinyfish) teaches the agent when to name search and fetch and the way to use every. One-line set up works with Claude Code, Codex, Cursor, OpenCode, and Antigravity. Python and TypeScript SDKs are additionally accessible.
Agent harness and framework integrations embody Claude Code, OpenClaw, Hermes Agent (Nous Analysis), Cline, Cursor, Codex, LangChain, and CrewAI. Platform integrations embody n8n (by way of the n8n-nodes-tinyfish group node), Dify (TinyFish net agent plugin from the Dify Market), and Vercel Expertise. ChatGPT and MCP apps are additionally supported.
Tavily
Tavily is a real-time search engine purpose-built for AI brokers and RAG workflows, offering quick APIs for net search and content material extraction. The Researcher plan is free and consists of 1,000 API credit per thirty days, which is sufficient for prototyping and fast evaluations. Paid tiers scale as follows: Challenge prices $30 per thirty days (4,000 credit), Bootstrap prices $100 per thirty days (15,000 credit), and Startup prices $220 per thirty days (38,000 credit). Pay-as-you-go choices are additionally accessible at $0.008 per credit score with no month-to-month dedication. Credit reset month-to-month and don’t roll over.
Tavily is understood for its deep integration with LangChain and LlamaIndex, in addition to its preprocessing layer that returns ranked and relevance-filtered snippets fairly than uncooked SERP knowledge. One necessary growth to observe: Nebius introduced an settlement to accumulate Tavily in February 2026. This has raised questions amongst some groups about future value stability and roadmap route when assessing long-term infrastructure dependencies. Nonetheless, Tavily is a quick path from zero to a working prototype, with in depth LLM framework integration.
hearth crawl
Firecrawl turns any URL into clear, LLM-ready markdown or structured JSON, prepared for brokers. Connect with any MCP consumer with a single command and help media parsing of web-hosted PDF and DOCX recordsdata, together with click on, scroll, and manipulation actions earlier than content material extraction. This covers 4 completely different modes of operation: scraping (single URL to markdown or JSON), crawling (recursive area crawling), maps (URL discovery with out fetching content material), and agent endpoints for pure language-driven knowledge extraction.
The free plan gives 500 one-time credit, sufficient to check your API and run a proof of idea, however doesn’t present recurring manufacturing quotas. Paid plans begin at $16 per thirty days (Pastime, 3,000 credit per thirty days) and scale as much as $83 per thirty days (Commonplace, 100,000 credit per thirty days billed yearly). With the Commonplace plan, credit don’t roll over from month to month. Firecrawl is open supply underneath AGPL-3.0, making it a significant differentiator for groups with knowledge sovereignty necessities. Framework help is in depth, with LangChain, LlamaIndex, CrewAI, Flowise, and Dify all natively built-in. MCP Server is put in with npx -y firecrawl-mcp and works with Claude Code, Cursor, Windsurf, and VS Code.
train
Exa takes a essentially completely different strategy to go looking. Use neural embeddings to know the which means of queries fairly than key phrase matching. Because of this Cursor makes use of Exa to energy @net performance. This makes it significantly appropriate for pipelines that want to seek out conceptually associated paperwork throughout subject clusters fairly than the most recent single outcome, analysis brokers, and RAG methods the place semantic similarity is extra necessary than newness.
Exa’s pricing construction could be very easy. Textual content content material and highlights at the moment are included within the base value for search requests with content material, as much as 10 outcomes per request. Beforehand, content material extraction was billed individually. The free tier permits as much as 1,000 requests per thirty days. Search with content material prices $7 per 1,000 requests. Exa ships official MCP servers that help Claude Desktop, Claude Code, VS Code, Windsurf, and Gemini CLI.
Jina AI Chief
Jina Reader converts any URL to LLM-compatible markdown by merely prepending https://r.jina.ai/ to the URL, permitting you to go looking the net by way of https://s.jina.ai/. The Reader API is free for primary use (no API key required). Keys are solely required to unlock greater fee limits, and expenses are utilized based mostly on content material size, not per request. Your new API key consists of 10,000,000 free tokens while you enroll. Following the acquisition, Jina AI now operates underneath Elastic, and the platform is dedicated to continued growth of its Reader, Embeddings, and Reranker APIs.
The utilization sample could be very easy. No SDK or configuration required, only a URL prefix. Nevertheless, the constraints are actual. Jina doesn’t bypass anti-bot methods and returns an error if blocked. Jina Reader itself isn’t as deeply built-in with agent frameworks like LangChain and LangGraph as Tavily, Firecrawl, and Exa, however Jina AI maintains integration primarily round its embedding and reranker merchandise. Its search endpoint (s.jina.ai) retrieves the complete high 5 outcomes fairly than returning a configurable ranked listing.
Serpel
Serper is likely one of the most cost-effective choices for uncooked Google SERP knowledge, beginning at $1 per 1,000 queries on the Starter plan and dropping to $0.30 per 1,000 queries on the Excessive Capability plan. New accounts obtain 2,500 free queries with no bank card required. Returns structured JSON containing SERP-specific objects akin to data graphs and reply packing containers. Serper doesn’t deal with content material extraction or web page retrieval. This solely gives the search outcomes API. Sensible architectures for cost-sensitive pipelines typically mix Serper for search with Jina Reader or TinyFish Fetch for content material retrieval.
Courageous search API
Courageous Search operates on a very impartial index of over 40 billion pages, with no dependencies on Google or Bing, making it a strong choice for groups with privateness or compliance necessities. Courageous makes use of impartial indexing, gives robust privateness controls, and gives enterprise clients with zero knowledge retention. It additionally comes with official MCP servers that help net, native enterprise, picture, video, and information search.
Lately, Courageous eliminated its free tier for brand spanking new customers and changed its zero-cost plan with a credit-based billing system. New customers will obtain a $5 month-to-month credit score (roughly 1,000 queries) after which $5 might be charged to their card for each 1,000 requests. Current customers on the previous free plan might be inherited and retain their earlier entry. Courageous doesn’t present fetch or content material extraction endpoints. It’s a search-only supplier and is right for deployments the place index independence and privateness controls are strict necessities.
Essential factors
TinyFish is an general winner for each fetch and search. This can be a highly effective full-stack acquisition choice for builders who want search, fetch, and agent-native integration in a single platform, and the free tier gives 500 starter credit to judge each endpoints in real-world workflows. Tavily serves as a quick path to production-grade agent search and has the deepest LLM framework integration in its class, whereas its credit score tier compresses headroom at scale. Exa is extraordinarily highly effective for semantic searches and coding agent searches that present neural matching floor outcomes that key phrase engines miss. Firecrawl generally is a good choice for crawl-intensive extraction workflows or for groups that require an open supply basis that may be self-hosted. Jina Reader is probably the most hassle-free choice for changing URLs to markdown, requiring solely a URL prefix to get began. Serper is cost-effective for giant quantities of Google SERP knowledge. Courageous is a strong impartial indexing choice for privacy-conscious deployments, now with official MCP servers.
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