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dhamma-seeker

tripitaka-mcp

by dhamma-seeker
OverviewSchemaRelated ServersScoreDiscussions
Python
Hybrid

List Tipiṭaka Structure

list_structure
Read-onlyIdempotent

Retrieve the hierarchical structure of all three Pitakas with coverage statistics, including segment counts and active status for each nikaya.

Instructions

Show the structure of all three pitakas with coverage statistics.

💡 Use this tool when:

  • The user asks for an overview of the Tipiṭaka (what's in it / which collections).

  • You need to check coverage before promising a search will find something — segment_count > 0 is the active-loaded signal.

  • Verifying scope when compiling an artifact.

📊 Current state (v1.1+, at parity with SuttaCentral bilara-data):

  • Sutta Piṭaka complete: DN 37, MN 155, SN 1,829, AN 1,419, KN 2,351 sections (~284,702 segments) — Pāli + Sujato EN

  • Vinaya Piṭaka complete: Bhikkhu Vibhaṅga 222, Bhikkhunī Vibhaṅga 127, Khandhaka 22, Parivāra 51 + Pātimokkha 2 (~71,557 segments) — Pāli + Brahmali EN

  • Abhidhamma Piṭaka complete: 7 books (ds, vb, dt, pp, kv, ya, patthana) ~88,414 segments — Pāli only (bilara has no English for any Abhidhamma book)

  • Total ~444,673 segments in the DB

⚠️ Known quirks:

  • The schema carries duplicate legacy + SC-modern codes side by side:

    • Vinaya: vin-v/vin-m/vin-c/vin-p (legacy, segment_count = 0) alongside pli-tv-bu-vb/pli-tv-bi-vb/pli-tv-kd/pli-tv-pvr (active, populated).

    • Abhidhamma: ym/pt (legacy = 0) alongside ya/patthana (active).

  • Use the active flag — each nikaya carries active: true/false (true ⇔ segment_count > 0). Pick active nikayas; the others are metadata placeholders from an older migration.

🌐 Languages: Returns Pāli + Thai + English labels regardless of enabled set (these are metadata, not segment text). Text content follows ENABLED_LANGUAGES. Thai translations aren't loaded yet.

Returns: Hierarchical structure: - pitakas{vinaya/sutta/abhidhamma} → nikayas[] - Each nikaya: code, name (3 languages), sutta_count, segment_count.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Tool Definition Quality

A4.7/5.0
Behavior5/5

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

Annotations declare read-only and idempotent. Description adds rich behavioral details: legacy codes side-by-side with active codes, active flag, languages returned, and segment counts. No contradictions.

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?

Well-structured with emoji sections for usage, current state, known quirks, languages, and return format. Every sentence provides value, no fluff.

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 fully explains the tool's output (hierarchical structure with pitakas, nikayas, codes, counts) and covers all necessary context given output schema exists.

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?

No parameters (baseline score 4). Description adds no parameter info, but schema coverage is 100% (no parameters to document).

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 it shows the structure of all three pitakas with coverage statistics. It distinguishes from sibling tools like search_by_keyword and get_sutta by focusing on structural overview and coverage.

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?

Explicit usage guidance provided: use when user asks for overview, to check coverage before searching, or when verifying scope for an artifact. Lacks explicit when-not-to-use statement but effectively implies alternatives.

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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