Get all branch locations for an FDIC-insured institution.
Returns branch-level data from the Summary of Deposits (SOD) including
addresses, deposit amounts, branch type, and coordinates.
Args:
cert: FDIC certificate number uniquely identifying the institution.
| Name | Required | Description | Default |
|---|---|---|---|
| cert | Yes |
| Name | Required | Description | Default |
|---|---|---|---|
| result | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description bears full behavioral disclosure burden. It describes the return data (addresses, deposits, etc.) but does not state side effects, authorization needs, rate limits, or the read-only nature. It lacks explicit safety assurances.
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 reasonably concise: four sentences, front-loaded with the purpose. The 'Args:' section is somewhat unconventional but provides necessary parameter details given the sparse schema. No filler words.
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 simplicity (one parameter, output schema present), the description covers purpose, input, and high-level output. It mentions the data source (SOD) and return fields. It could include error behavior, but overall sufficient.
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?
The schema has 0% description coverage for the 'cert' parameter. The description compensates fully by explaining it as 'FDIC certificate number uniquely identifying the institution', which adds crucial meaning beyond the schema type.
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 'Get all branch locations for an FDIC-insured institution', which is a specific verb-resource pair. It distinguishes from siblings like get_institution (institution-level data) and get_county_branches (branches by county), making the tool's role unambiguous.
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 implies when to use this tool: when branch-level data for a specific institution is needed. However, it does not explicitly discuss when not to use it or mention alternatives (e.g., get_county_branches for county-based queries), leaving some guidance implicit.
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.
Each tool has a clearly distinct purpose targeting different FDIC data domains: bank failures, county branches, institution details, institution branches, and institution search. There is no overlap in functionality, and the descriptions clearly differentiate between failure records, branch data, and institution information.
All tools follow a consistent verb_noun pattern with clear, descriptive names: get_bank_failures, get_county_branches, get_institution, get_institution_branches, and search_institutions. The naming convention is uniform throughout the set, using snake_case and appropriate verbs (get/search) that match the action.
With 5 tools, this server is well-scoped for its FDIC banking data domain. Each tool serves a specific, non-overlapping function, covering key aspects like failures, branches, institution details, and search. The count is neither too sparse nor bloated, fitting typical MCP server ranges.
The tool set provides comprehensive coverage for querying FDIC data, including failures, branches, and institution details with search capabilities. A minor gap exists in update or administrative functions (e.g., no tools for modifying data), but this is reasonable for a read-only data server, and agents can fully navigate the available information.