Look up a biblical person, place, event, or people group by name (Theographic knowledge graph). Returns details and where they appear. entity_type optional: person | place | event | people_group.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | ||
| entity_type | No |
| Name | Required | Description | Default |
|---|---|---|---|
| result | 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?
With no annotations provided, the description carries the burden of disclosure. It does mention the return content (details and where they appear), which is helpful. However, it doesn't disclose what happens with ambiguous names, whether partial matches are supported, case sensitivity, or whether it returns one result or multiple. It's a read tool so no mutation concerns, but behavioral detail is thin.
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?
Two concise sentences with zero waste. The first establishes purpose and output, the second documents the optional parameter's allowed values. Every sentence 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?
The tool has an output schema (which explains return value structure), reducing the burden on the description for output details. With 2 params (only 1 required) and modest complexity, the description covers purpose and parameter options adequately. However, given 0% schema coverage and no annotations, it could do more with edge cases like ambiguity handling, given the sibling ecosystem has several search/citation tools that could overlap.
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 coverage is 0%, so the description must compensate. It does explain what entity_type means with enumerated allowed values (person | place | event | people_group), which adds value. However, it provides no detail on what the name parameter expects (exact match? partial? canonical form?) or how entity_type interacts with name filtering beyond being optional.
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 the verb (Look up) and resource (biblical person, place, event, or people group via a Theographic knowledge graph), and mentions it returns details and appearances. It's clear but doesn't explicitly distinguish from siblings like get_citations or get_cross_references, though the domain (biblical entities) is somewhat distinct.
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 notes entity_type is optional with allowed values, providing light guidance. However, there's no explicit when-to-use guidance, no mention of how this differs from correlated tools like semantic_search, word_study, or search, and no exclusions or alternative tool pointers.
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 targets a distinct function: text retrieval, interlinear, word study, cross-refs, citations, entities, search, similarity, reading works, and corpus info. Even search, semantic_search, and find_similar are clearly differentiated by input type (keyword, theme, passage reference) and purpose.
The set mixes verb-prefixed names like get_passage and read_work with noun-style names like corpus_info and word_study, plus bare verbs like search. All use snake_case, but the lack of a uniform prefix or consistent verb-noun pattern reduces predictability.
13 tools is well within the ideal range for a specialized study server. Each tool addresses a distinct research need, from scripture retrieval to original-language analysis, without redundancy or bloat.
The surface covers the full biblical research workflow: text retrieval, comparison, interlinear, word study, cross-references, patristic citations, entities, multiple search modes, and reading related prose works. Search and semantic_search fill discovery gaps, and corpus_info provides structural orientation.