bible-copilot

Get Bible verse text

get_verse_text

Fetch the exact text of a Bible verse, passage, or whole chapter from a public-domain translation (kjv = King James Version). Deterministic — no AI generation.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "reference": "<reference>"
    },
    "name": "get_verse_text"
  }
}

Input Schema

Name	Required	Description	Default
`reference`	Yes	e.g. "Romans 8:28" or "Psalm 23"
`translation`	No	default: kjv

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedJul 16, 2026
- changedInput schema / properties / translation / description
```
Previous value: -"default: web"New value: +"default: kjv"
```
- changedInput schema / properties / translation / enum
```
Previous value: -[
-  "web",
-  "kjv"
-]New value: +[
+  "kjv"
+]
```
First observedJul 2, 2026

TDQS

A4.3/5.0

Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses key behavioral traits: the tool is deterministic (no AI generation), returns exact text, and uses public-domain translations. This is valuable context for an agent deciding between this and study tools. It could mention error handling or return formatting, but for a simple retrieval tool, the transparency is above average.

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

Conciseness5/5

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

Two sentences, front-loaded with purpose, followed by a key behavioral trait. Every word earns its place; no fluff or repetition. Excellent conciseness.

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

Completeness5/5

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

The tool is simple (2 parameters, no output schema). The description covers purpose, input granularity (verse/passage/chapter), translation option, and deterministic behavior. Given the low complexity, this is fully complete for an agent to select and invoke it correctly.

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. Both parameters (reference and translation) are described in the schema. The description adds minor context by explaining 'kjv = King James Version', which aids understanding of the enum, but it does not significantly add meaning beyond the schema. Baseline 3 is appropriate.

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

Purpose5/5

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

The description clearly states the tool's function: fetching exact text of Bible verses, passages, or chapters. It specifies the resource (text) and the source (public-domain translation), and distinguishes it from sibling tools like 'find_verse_study_page' or 'study_bible_passage' by focusing on raw text retrieval.

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

Usage Guidelines4/5

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 you need exact, deterministic text from a public-domain translation. It does not explicitly name alternatives or exclusions, but the deterministic/no-AI-generation note helps differentiate it from study or verification tools. Clear context, though no explicit alternative comparison is given.

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

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