Live AI-native web search with citations. One tool for every MCP client. Flat per-request pricing.
Scored across 1 tool
With only a single tool, there is no possibility of confusion or overlap. The tool's purpose is clear and distinct.
The tool name 'search' is simple and directly reflects its function. Although there is no pattern to compare, it is consistent and unambiguous.
The server has only one tool, which feels thin for a typical server. However, the tool itself is broad and covers many search types, so it earns a borderline score rather than a lower one.
The single tool covers web, news, images, places, shopping, flights, hotels, YouTube, transcripts, and URLs, providing comprehensive search coverage. There are no obvious gaps in the search domain.
Search the live web and get an AI-synthesized answer with structured citations. One endpoint covers 10 answer shapes — web, news, images, places & maps, shopping, flights, hotels, YouTube, transcripts, any URL — the right one is picked automatically from your query. Use this whenever you need fresh, factual information from the web.
| Name | Required | Description | Default |
|---|---|---|---|
| model | No | `pixserp-fast` = quick single-search lookup (default). `pixserp-standard` = balanced. `pixserp-deep` = multi-angle thorough research. `pixserp-agent` = multi-step research loop, decides itself when to stop. | pixserp-fast |
| query | Yes | What to search for. Phrase as a natural-language question or a specific topic. | |
| max_steps | No | Only used when `model = pixserp-agent`. Caps the research loop length. Default 50, max 100. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden of behavioral transparency. It discloses that the tool returns an AI-synthesized answer with citations and that the appropriate answer shape is selected automatically from the query. This conveys key behavioral attributes beyond what a schema would show, though it does not cover potential limitations like data freshness or rate limits.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and well-structured, with three sentences that each deliver value: core function, scope of answer shapes, and usage guidance. There is no redundant or filler content, making it effectively front-loaded and easy to parse.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's complexity (multiple answer shapes, model enums, and no output schema), the description offers a solid overview. It clarifies the automatic selection of answer shapes and the intended use case, which is sufficient for an agent to decide when to invoke it, though it does not detail the response structure.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, so the schema already documents all parameters. The description adds minimal parameter-specific meaning—only implying that the query determines which answer shape is used. This is consistent with a baseline score of 3 since the schema does the heavy lifting.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's function: 'Search the live web and get an AI-synthesized answer with structured citations.' It specifies the resource (live web) and the action (search), and adds detail about the 10 answer shapes, making the purpose explicit and comprehensive.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a clear usage context: 'Use this whenever you need fresh, factual information from the web.' It does not explicitly mention when not to use it or name alternatives, but given no sibling tools exist, the guideline is sufficient and well-articulated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
searchAgent-native search engine with live web research optimized for AI agents.
Your agent needs live data — a competitor's traffic, who to contact there, what people are saying, what Google and ChatGPT answer about you, a company's filings. Normally that is six vendor accounts, six sets of keys and six SDKs. This is one URL. **What you can ask for** • "How much traffic does stripe.com get, where does it come from, and who competes for the same keywords?" • "Find 20 Series-B fintech companies in Germany and the heads of marketing there, with emails." • "Does ChatGPT mention our brand when someone asks for the best CRM — and what does it cite?" • "What is X saying about $NVDA today, and what did the stock actually do?" • "Search the web for this, then scrape the three best pages into markdown." **How to use it** Point any MCP client at https://mcp.aisa.one/mcp and sign in with OAuth — there is no key to create or paste. Then just ask: the agent calls search to find the right operation and use to run it. **Why this rather than the source** 26 sources behind one account and one bill — DataForSEO, Semrush, Ahrefs, Similarweb, Apollo, X/Twitter, Instagram, Reddit, Pinterest, YouTube, Tavily, Exa, Perplexity, Firecrawl, CoinGecko, Kalshi, Polymarket, AgentMail and more, 580+ operations. tools/list returns five tools, not 580, so the introduction does not eat your context window. **What it costs** Finding and inspecting an operation is free. Running one is billed per call at API prices, with no seat and no monthly minimum, and every call takes max_price_usd so an agent cannot overspend by accident. **Where else it reaches** One slice at a time: https://mcp.aisa.one/seo/mcp · /finance/mcp · /social/mcp · /search/mcp · /sales/mcp · /mail/mcp · /gtm/mcp, or a single provider like /twitter-api/mcp. Same account, fewer tools listed, and search still reaches everything. Full list at https://mcp.aisa.one/servers
Web search, scraping, RAG answers with citations, and translation as MCP tools.
Your agent needs the open web — searched by more than one engine, and read as clean markdown rather than raw HTML. **What you can ask for** • "Search this question with two providers and tell me where they disagree." • "Scrape these 40 URLs into markdown, in one batch." • "Crawl this documentation site and give me every page." • "Do deep research on this topic and cite the sources." • "Find the academic papers behind this claim." **How to use it** Point any MCP client at https://mcp.aisa.one/search/mcp and sign in with OAuth — there is no key to create or paste. 30 tools across several independent providers: Tavily and Exa search, answers, contents and agent runs; Firecrawl scrape, batch scrape, crawl, map and search; Perplexity Sonar, Sonar Pro, reasoning and deep research; Oxylabs AI search and LLM jobs; OpenAI and Anthropic web search; and scholarly search. **Why this rather than the source** Several independent indexes behind one account, because one engine's blind spot is not visible from inside it. **It is also a door to the rest** The same login reaches 26 sources and 580+ operations. Find the page here, then ask the same agent who links to it or how much traffic it gets — without adding a second server. **What it costs** Finding and inspecting an operation is free. Running one is billed per call at API prices, with no seat and no monthly minimum, and every call takes max_price_usd so an agent cannot overspend by accident. **Where else it reaches** https://mcp.aisa.one/seo-serp/mcp for the Google results page itself, https://mcp.aisa.one/seo-serp-other-engines/mcp for Bing, Baidu and Naver.
Add one secure layer between your agents and this server.
