api_seo_reportFull SEO audit report of a domain: health score 0-100, prioritized issues list, title/description/H1/canonical, robots.txt review, word count. Returns ready markdown report. ?url=https://example.com [HTTP x402 price: $0.99]
| Name | Required | Description | Default |
|---|---|---|---|
| params | No |
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
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, the description carries the full burden of behavioral disclosure. It does provide useful context: it returns a ready markdown report and includes pricing/cost information. It does not disclose potential side effects, network request behavior, rate limits, error handling for invalid URLs, or authentication requirements, leaving some uncertainty.
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 short and front-loaded with the core function and output details. The trailing '?url=https://example.com [HTTP x402 price: $0.99]' is slightly noisy, but it communicates the invocation example and cost without bloating the text.
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?
For a one-parameter tool with an output schema, the description covers the main purpose, the expected input example, and the high-level output format. It does not provide explicit selection guidance, but that is addressed in the usage_guidelines dimension; otherwise nothing essential is missing for basic invocation.
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 0%, but the description offers a concrete invocation example '?url=https://example.com' and clarifies that the tool acts on a domain. This gives agents a usable input format beyond the bare schema. It does not explain optionality or null behavior, but with only one optional parameter this is a meaningful improvement.
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 that the tool produces a full SEO audit report for a domain and enumerates concrete outputs: health score, prioritized issues, title/description/H1/canonical, robots.txt review, and word count. It is specific and easy to understand, though it does not explicitly name sibling tools such as api_seo_meta or api_robots_audit to differentiate them.
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 phrase 'Full SEO audit report' implies this tool is for comprehensive domain audits rather than narrower SEO checks, giving some usage context. However, there is no explicit when-to-use guidance, no mention of alternatives, and no exclusions, so an agent must infer when to choose this over related sibling tools.
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.
Several tools have unclear boundaries: api_search and api_serp_google both return Google results, api_scrape and api_render_text both extract page text, and api_hash_multi overlaps with api_sha256 for SHA-256/SHA-512. While many tools are distinct, these overlapping pairs create real misselection risk.
Every tool follows the same api_<snake_case> pattern with no mixed conventions or casing styles. The prefix makes the server immediately recognizable and the action/resource is consistently readable across all 44 tools.
44 tools is well over the 25+ threshold for a well-scoped set, making the server feel like a grab-bag of unrelated utilities. Even though each tool is small and individually useful, the overall surface is too large and would benefit from consolidation into focused sub-servers.
The set covers many common utility categories—encodings, conversions, text analysis, web scraping, SEO, and trends—but has notable one-way gaps: CSV/YAML/TOML all convert to JSON but not back, and markdown converts to HTML but not the reverse. The broad domain makes full completeness hard to define, so only major reverse-conversion gaps stand out.