Tripitaka MCP (hosted)

Verify Quote

verify_quote

Read-onlyIdempotent

Verify, check, or confirm a Buddha quote — does the canon really say it?

Fact-check a quotation attributed to the Buddha. Catches fake, misquoted, misattributed and misremembered passages, and finds the true reading.

Paste a line that has been quoted or half-remembered — Pāli or English — and this says whether the canon really contains it, cites where, and if not, shows the closest thing that is actually there.

🧭 When to use this:

A quote is attributed to the Buddha and you are not certain it is real. A fabricated line that sounds canonical is the hardest error to catch by reading, because it reads correctly. Check it instead of trusting it.
Someone recalls a passage imperfectly, or a chanted form has drifted from the written one. The tool shows the received text beside theirs.
Before repeating any Pāli you did not get from these tools, verify it. This is cheap and it is the difference between citing and guessing.

⚠️ Do not present an unverified passage as canonical. If the verdict is not_found, say plainly that the line is not in the canon rather than quoting it with a hedge — a hedged fabrication still spreads.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`text`	Yes	The passage as quoted. Diacritics optional, folded internally. One line works best; the canon is segmented line by line, so a quote spanning several segments may only match in part.
`limit`	No	How many near matches to return when it is not exact (1–10).

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

TDQS

A4.6/5.0

Behavior5/5

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

Even with readOnlyHint and idempotentHint present, the description adds meaningful behavioral detail: it returns a verdict, cites where the canon contains the quote, shows the closest existing passage when not found, folds diacritics, and warns that multi-segment quotes may only partially match. Nothing asserts a behavior that contradicts the annotations.

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

Conciseness4/5

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

The description is front-loaded with a clear purpose and uses headers, bold text, and bullets to stay scannable. It is longer than typical, but most sections earn their place; only the motivational aside ('the difference between citing and guessing') is discretionary.

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 description covers selection criteria, invocation behavior, not_found handling, input formatting constraints, and output expectations. With an output schema present and annotations covering safety, nothing essential is missing for an agent to choose and call the tool correctly.

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

Parameters4/5

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

The schema already documents text and limit with good coverage, so the baseline is 3. The description adds value by noting that Pāli or English input is expected and explaining why one line works best because the canon is segmented line by line—this goes beyond the schema and helps an agent use the text parameter correctly.

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 opening line states a specific verb and resource: fact-check a quotation attributed to the Buddha against the canon. It also distinguishes itself from sibling search and translation tools by saying it catches fake, misquoted, misattributed, and misremembered passages and finds the true reading.

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?

It provides three concrete when-to-use bullets and an explicit warning about handling not_found verdicts. It does not name sibling alternatives directly, so an agent must infer the routing distinction from the purpose statement rather than from explicit comparisons.

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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TDQS

A4.7/5.0

Disambiguation5/5

Each tool has a clearly distinct purpose. Search tools are differentiated by strategy (keyword, hybrid, semantic, exhaustive). Reading tools separate content retrieval, comparison, and viewer rendering. Parsing and definition tools have complementary roles. No overlapping functionality.

Naming Consistency5/5

All tools follow a consistent verb_noun pattern in snake_case, e.g., compare_translations, get_sutta, list_editions, search_by_keyword. The only slight deviation is open_sutta_viewer using 'open' instead of 'view', but it still fits the pattern.

Tool Count5/5

12 tools is well within the ideal range for a domain-specific server. Each tool addresses a distinct need: retrieval, search, parsing, dictionary, citation, structure overview, and comparison. No bloat or thinness.

Completeness5/5

The tool surface covers the full lifecycle for a read-only Pāli canon server: fetching content, searching (multiple modes), viewing with translations, comparing translations, parsing words, looking up definitions, listing editions and structure, and generating citations. There are no obvious gaps for the intended use case.

Resources

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