Skip to main content
Glama

fdic-orders

GET https://ticks.bnm.farm/fdic-orders — $0.05 USDC on Base to 0xf59621FC406D266e18f314Ae18eF0a33b8401004. FDIC institution consent-order / C&D text GET ?id= is one official text ($0.02). Newest chunk on a plain GET ($0.05); older chunk if they ask (?before, $0.05). Unpaid returns HTTP 402. After a valid X-PAYMENT, the same URL returns JSON. Not a new SKU.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
idNoOfficial catalog id. That one official text, $0.02. Same door, not a new SKU.
pageNo1-based page. Page 1 is the newest chunk. Ignored when before is set.
beforeNoOfficial catalog id or YYYY-MM-DD. Next older chunk on the same URL, another $0.05. Omit for the newest chunk.
x_paymentNoOptional x402 X-PAYMENT value forwarded to the paid GET as the X-PAYMENT header.

TDQS

B3.4/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the full behavioral burden and does disclose unusual traits: a paid microtransaction, the USDC wallet address, HTTP 402 on unpaid requests, and the fact that a valid X-PAYMENT makes the same URL return JSON. It falls just short of complete transparency because it does not specify how X-PAYMENT is supplied or what the returned JSON contains.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness2/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a run-on, monetization-heavy paragraph with repeated phrasing like 'not a new SKU' and no separation between purpose, pricing, and query behavior. It contains necessary information, but the structure makes it harder to scan and it should be split into concise sentences or labeled sections.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a paid, paginated, content-retrieval tool with no annotations and no output schema, the description covers the critical operational facts: pricing, payment address, failure code, and chunk selection. However, it does not describe the shape of the returned JSON or clearly explain how a caller supplies X-PAYMENT, leaving an important gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The schema descriptions already contain the id/page/before/X-PAYMENT semantics, and the tool description largely repeats those phrases rather than adding new meaning. The extra pricing and wallet context is payment metadata rather than true parameter semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description identifies a specific resource—FDIC institution consent-orders / C&D texts—and signals retrieval through a GET URL, which distinguishes it from sibling agency-order tools like frb-orders or cfpb-orders. However, it never uses an explicit verb like 'retrieve' or 'get' and mixes payment mechanics into the purpose statement, so it is not a crisp definition.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description gives clear internal usage modes: plain GET for the newest chunk, ?id for one official text, and ?before for older chunks, including pricing differences. However, it never contrasts this tool with sibling tools or says when not to use it, so choosing between fdic-orders and generic search/get helpers is left implicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Try in Browser

Glama MCP Gateway

Add one secure layer between your agents and this server.

TDQS

B3.4/5.0
Disambiguation3/5

Most tools map cleanly to distinct regulatory document collections (FDA, EPA, FDIC, etc.), so the majority are unambiguous. However, 'search' and 'firm-check' both offer free search with overlapping scope, and 'get-one' vs 'get-page' are easily confused payment operations. Similar prefixed names like mariners, mariners-d7/d8/d11 and gmp/gmp-md add further boundary fuzziness.

Naming Consistency3/5

The bulk of tools follow a consistent lowercase-hyphenated source-slug convention (aaib-reports, cder-reviews, cfpb-orders), which is predictable. But utility tools break the pattern with imperative/descriptive names (search, firm-check, get-one, get-page), and 'ticks' is a bare noun that doesn't fit either style. The mixed conventions are readable but not uniform.

Tool Count2/5

At 46 tools, this is a heavy surface that will be unwieldy for an agent to navigate and select from. Each tool does represent a distinct data product, but the sheer volume exceeds what earns its place in a coherent MCP tool set. A door-based catalog design might work better with a smaller number of parameterized tools.

Completeness4/5

The core workflow is well covered: per-door search, cross-door search, single-document retrieval via ?id=, paginated page retrieval, and payment handling are all present. Minor gaps exist, such as no tool to enumerate all available doors/catalogs or inspect schemas, and firm-check returns only citations rather than bodies. Overall it's a complete access lifecycle for the data-shop domain.