Company snapshot (bundle) — One call: SEC company facts (revenue, net income, assets, EPS) + the company's most recent filings. Ticker or CIK. JSON. Price: $0.03 USDC (Base, via x402).
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ticker (AAPL) or CIK |
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?
Annotations already carry the safety profile (readOnlyHint=true, destructiveHint=false), so the description's job is to add context beyond that. It does: disclosing that the tool is paid ($0.03 USDC via x402) is critical behavioral info an agent must know before invoking, and it describes the bundle composition. No contradiction with annotations.
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?
Four distinct facts — data returned, input format, output format, and price — are packed into one compact string with zero filler. The scoping label 'Company snapshot (bundle)' is front-loaded, and every fragment earns its place.
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, read-only snapshot tool whose safety is already covered by annotations, the description covers the data returned, input format, output format, and cost — most of what an agent needs. The minor gap is the underspecified scope of 'most recent filings' (how many, which form types, what period), which matters more because no output schema exists to clarify it.
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 100% — the schema already documents id as 'ticker (AAPL) or CIK', and the description merely restates 'Ticker or CIK'. Per the high-coverage baseline, the description adds no meaning beyond the schema, so 3 is appropriate.
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 names the resource (SEC company facts) and enumerates the specific fields (revenue, net income, assets, EPS) plus the most recent filings, so an agent knows exactly what it will retrieve. The 'bundle — One call' framing implicitly differentiates it from siblings like sec_company and sec_filings_search, but it never names those alternatives, so differentiation is left to inference rather than stated.
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?
'One call' implies the usage scenario — getting both facts and filings without a second invocation — which is a legitimate but weak usage signal. There is no explicit when-to-use/when-not-to-use guidance, and no alternatives are named even though sec_company and sec_filings_search exist in the sibling list, making the routing decision a real gap.
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 are clearly separated by prefix and data source, but several bundled products overlap heavily: vehicle_deal_check vs vehicle_report, realestate_property_report vs realestate_site_risk, finance_company_360 vs finance_health_scan, and domain_due_diligence vs email_domain_check/business_vet. An agent would frequently struggle to pick the correct premium bundle.
Tool names overwhelmingly follow a consistent snake_case category-prefix pattern like weather_, crypto_, vehicle_, finance_, and geo_. Minor deviations such as bare names (domain, ip) and noun-verb forms (dns_lookup, url_check) are easy to learn and don't create real confusion.
50 tools is far beyond the typical well-scoped 3–15 range and will require heavy filtering to navigate. The broad multi-domain data marketplace partially justifies the size, but it would be more coherent split into per-domain servers or consolidated further.
For a read-only data/diligence marketplace, the surface is quite comprehensive: weather, vehicle, crypto, SEC/finance, domain/email, sanctions, and geo workflows all have core operations plus fused verdict bundles. Minor gaps exist—such as a simple crypto price lookup or vehicle market value—but agents can usually work around them.