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mcp-server-panchangam

get_panchangam_range

Get daily Panchangam summaries for any date range up to 31 days, including tithi, nakshatra, muhurta windows, and special yogas, to compare days and plan auspicious events.

Instructions

Returns a compact Panchangam summary for each day in a date range (max 31 days). Each day includes: Tithi, Nakshatra, Yoga, Sunrise/Sunset, all auspicious and inauspicious windows, eclipse (if any), special yogas, and special day flags. New in 1.9.0: each day also carries all timing-computation fields — ghati_clock, nakshatra_pada, vishaghati, bhadra_mukha/bhadra_puchha, sankramana_avoidance, in_panchaka_nakshatra, nakshatra_mukha, anandadi_yoga, is_khar_maasa/khar_maasa_name, is_pitru_paksha, simha_stha_guru/shukra, guru_maudhya/shukra_maudhya, disha_shoola_direction, panchaka_rahita. Useful for planning muhurtas over a week or comparing multiple days. Args: start_date=YYYY-MM-DD, end_date=YYYY-MM-DD, city=city name, system=drik|surya_siddhanta|vakya (default: drik), ayanamsa=lahiri|raman|krishnamurti|true_chitrapaksha (default: lahiri).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityYes
systemNodrik
ayanamsaNolahiri
end_dateYes
latitudeNo
timezoneNo
longitudeNo
start_dateYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Addedv1.15.1
  2. Removedv1.13.0
  3. First observedv1.0.0

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the full burden, and it does well: it discloses the 31-day limit, the compact summary behavior, the version-dependent field additions, and the detailed output content. It does not cover edge behavior like invalid ranges or city lookup failures, but it provides solid behavioral context.

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 the core behavior and then lists output fields and parameters. The long field list is dense but purposeful, since it tells the agent what information can be extracted. It is not overly repetitive, though it could be slightly more compact.

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

Completeness4/5

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

The description is largely complete for a tool of this complexity: it covers the main use case, output contents, parameter formats, and limits, and an output schema exists to document return structure. The main missing context is the optional coordinate/timezone parameters and how they interact with the required city parameter.

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?

Schema description coverage is 0%, so the description must compensate. It explains date formats, city, system choices, ayanamsa choices, and defaults—valuable information absent from the schema. However, it omits the optional latitude, longitude, and timezone parameters, leaving a noticeable gap.

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 states a specific verb ('Returns') and a precise resource: a compact Panchangam summary for each day in a date range. This clearly distinguishes it from the single-day sibling `get_panchangam`, and the 'max 31 days' scope adds important specificity.

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 gives a clear use case: 'planning muhurtas over a week or comparing multiple days.' It does not explicitly name alternatives or say when not to use it, but the range-focused context is enough for an agent to select it appropriately among the siblings.

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