Get a servicer scorecard, vintage performance fan, or lender transfer analysis.
| Name | Required | Description | Default |
|---|---|---|---|
| gse | No | all | |
| mode | Yes | ||
| top_n | No | ||
| lender | No | ||
| vintage | No | ||
| max_points | No |
| Name | Required | Description | Default |
|---|---|---|---|
| data | No | ||
| meta | Yes |
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 provide readOnlyHint, idempotentHint, and destructiveHint, fully covering safety. The description adds no additional behavioral traits (e.g., pagination, data sources), so it meets the baseline for annotation-rich tools without extra value.
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?
Single sentence is concise and front-loaded. However, it omits important details; conciseness should not sacrifice completeness.
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?
With 6 parameters and an output schema, the description is too minimal. It fails to describe each mode's output or parameter effects, making it incomplete for effective tool use.
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 only implicitly connects mode to outputs. It does not explain parameters like gse, top_n, lender, vintage, or max_points, leaving their semantics unclear.
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?
Description clearly states the tool gets three types of servicer analytics (scorecard, performance fan, transfer analysis) aligning with the mode parameter. It is specific about the resources but does not elaborate on each mode's output, preventing a 5.
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?
No guidance on when to use this tool versus siblings like compare_lenders or get_lender_profile. The description lacks context for tool selection, leaving the agent to infer from tool names alone.
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.
Most tools target clearly distinct data domains: lender search/profile/compare cluster around HMDA lender analytics, while market snapshot, loan performance, servicer analytics, and SEC filing tools are separate. The only minor ambiguity is between get_lender_profile, compare_lenders, and search_lenders which all deal with lender keys, though their intents (search vs. profile vs. comparison) are distinct.
Tools follow a consistent get_/search_/compare_ verb pattern with clear noun targets (lenders, market_snapshot, loan_performance, sec_filing). The one deviation is that search_lenders, search_sec_filings, and compare_lenders use non-get verbs while the rest use get_, but this is a sensible pattern matching read vs. search semantics.
At 9 tools, this is well within the ideal 3-15 range and each tool appears to represent a meaningful consumer capability for a mortgage analytics domain. The count feels appropriately scoped without redundancy or bloat.
The surface covers market data, SEC filings, lender profiles, loan performance, and servicer analytics, but there are notable gaps: there's no mutation capability (all read-oriented), no way to combine or join across these domains, and no search tool for loan performance or market data topics - those are limited to pre-bounded topics. Some domains feel like they have single query points rather than full browsing coverage.
