$0.01 via x402: Tavily-compatible POST /search. Body { query } — ranked web results, snippets, source URLs, optional answer. Same shape as Tavily x402.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Search query | |
| topic | No | ||
| end_date | No | ||
| x_payment | No | ||
| start_date | No | ||
| time_range | No | ||
| max_results | No | ||
| search_depth | No | ||
| include_answer | No | ||
| include_images | No | ||
| exclude_domains | No | ||
| include_domains | No | ||
| include_raw_content | No |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It discloses that results are 'ranked' and may include an 'optional answer', but it doesn't mention pagination, rate limits, payment failures, or behavior differences from standard Tavily. The x402 note provides some context on payment but is terse.
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 compact and front-loaded with the key info (endpoint, payment, result shape). The cost mention ($0.01) is useful. However, it's slightly fragmented with the 'Same shape as Tavily x402' tail, but overall minimal and informative.
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 has 13 parameters and no output schema, the description is insufficient to fully guide invocation. It fails to document most parameters or the response structure beyond basic snippets. For a tool this complex, more detail on parameter semantics and expected output is needed. It's decent for a simple read, but incomplete for parameter handling.
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 description coverage is only 8% (only 'query' has a description). The description mentions only '{ query }' and 'optional answer', leaving topic, time_range, include_answer, etc. entirely undocumented. The description does not compensate for the low schema coverage, so agents must guess semantics for 12 of 13 parameters.
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 performs a Tavily-compatible POST /search returning ranked web results, snippets, source URLs, and optional answers. It uses a specific verb ('search') and resource ('Tavily-compatible POST /search'), and it distinguishes from web_search/web_scrape siblings by specifying the Tavily-compatible interface and x402 payment.
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 mentions the endpoint and body format but doesn't give explicit when-to-use guidance or contrast with alternatives like web_search. The x402 payment note implies a paid usage context, but no exclusions or alternatives are named beyond the implicit 'Tavily-compatible' branding.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Many tools occupy the same conceptual space: web_scrape vs markdown_web_scraper, post_check vs brand_ai_visibility_check, llm_chat_completions vs post_api_v1_chat_completions, chain_transaction_status vs chain_confirmations, and connect_token vs token_security_check + dex_token_data. Descriptions help in places, but for an agent facing 92 tools these near-overlapping endpoints will frequently cause misselection.
Everything is snake_case, but the conventions diverge sharply: get_chain_* and chain_* coexist for the same RPC family, post_* names are HTTP-route artifacts, api_generate reverses noun_verb order, and many names are bare nouns rather than verb_noun. There is no predictable naming pattern an agent can rely on.
At 92 tools this is far beyond the range where an agent can keep the surface coherent, even for a store. The flat tool list mixes products, bundles, aliases, proxies and single-use verticals, so most of the count is noise for any given task. A catalog/search/payment model with fewer exposed tools would fit the storefront purpose better.
The server has impressive breadth and covers key storefront/market workflows: catalog, samples, credits, directory listing, notary, and the task lifecycle. But each domain is shallow: there is no chain transaction broadcast, no task update/cancel/dispute, no AI-visibility history, and many verticals are a single tool with no follow-on operation. The surface is broad but not deeply complete.