Live AI-native web search with citations. One tool for every MCP client. Flat per-request pricing.
Average 4.2/5 across 1 of 1 tools scored.
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.
searchAInspectSearch 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.
Claiming proves that you control a remote MCP connector. It does not move, proxy, or interrupt the server.
Open the connector listing, choose Claim ownership, and sign in to Glama.
Complete one verification method:
GitHub identity — fastest for official registry listings. For a namespace such as io.github.alice/server, link the matching GitHub user or an account that owns the GitHub organization, then choose Claim with GitHub.
HTTP challenge — works when you can deploy a public file. Generate a token, publish the exact JSON Glama shows at /.well-known/glama.json on the same origin as the connector, then choose Check HTTP challenge.
DNS challenge — works when you control DNS but cannot change the server. Generate a token, create the exact TXT record Glama shows, wait for it to propagate, then choose Check DNS challenge.
After verification, Glama sends a confirmation email and gives you access to listing details, thumbnails, health checks, and analytics. Keep the HTTP file or DNS record in place: Glama periodically checks it and ownership remains verified while the token is discoverable.
The HTTP ownership file has this structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"claim": "glama_claim_..."
}Claim tokens are opaque, stable, and bound to the signed-in Glama account. They contain no email address or other personal information. If Glama can no longer discover a verified HTTP or DNS token, it starts a seven-day grace period before removing claim-based access. Restore the same token during that period to keep ownership verified. Never publish an email address, Glama session token, GitHub token, or connector credential as ownership proof.
If verification fails, confirm that you copied the current token exactly. The HTTP file must be public, return valid JSON with a successful HTTP response, and stay on the connector's origin. DNS changes may need more time to propagate. A claim cannot transfer to a different origin or hostname: if the connector target changes, Glama starts the grace period and the new target must be claimed separately after the previous claim is released.
For a connector linked to the official MCP Registry, registry updates continue to replace its name, description, and URL by default. After claiming, open Manage connector and enable Use Glama listing details as the source of truth if edits made on Glama should be preserved. Categories and thumbnails are always managed on Glama; registry linkage and technical connection settings continue to sync.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
To improve your MCP server's ranking:
Claim ownership of the server listing
Complete the server profile with an accurate description and thumbnail
Provide a test profile so Glama can connect to and evaluate the server
Keep tool definitions clear and complete to earn a high Tool Definition Quality Score (TDQS)
Route real usage through the Glama Gateway; more recorded successful server uses also improve the ranking
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
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Agent-native search engine with live web research optimized for AI agents.
Web search, scraping, RAG answers with citations, and translation as MCP tools.
The Google for AI agents — company intel, competitor tracking, market research via MCP. JSON output
Scrape, crawl and search the web for AI agents via MCP.
