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indic-normalize-mcp — SCAFFOLD

Indic-language transliteration + Indian name/address normalization. Wraps Wikidata + Aksharamukha + OpenStreetMap. Tiny niche, sticky usage — every India-targeted agent product needs it.

Status: scaffolded. Idea #32 in ../../../ai-as-customer-ideas.md.


Planned tools

Tool

What it returns

transliterate(text, from_script, to_script)

"मुकेश अंबानी" → "Mukesh Ambani" (or vice-versa). Supports Devanagari, Tamil, Telugu, Kannada, Bengali, Gujarati, Malayalam, Punjabi, Odia, Marathi, plus IAST and ISO 15919 Latin.

detect_script(text)

Script + language probability.

normalize_name(name)

Canonical form + variants ("Sri", "Shri", "Sree", "Shree").

normalize_address(address)

Parse Indian address → {line, locality, city, state, pincode}. PIN-code derives state.

pincode_to_locality(pincode)

Pincode → city/state via India Post + OSM.

state_from_pan(pan)

Validates PAN format + extracts state code.

Related MCP server: OSM Edit MCP Server

Audience

  • Every agent product targeting India.

  • Pairs naturally with indian-regulatory-mcp — same audience.

  • Indian e-commerce, fintech, gov-tech agents.

Pricing

Lower-traffic but indispensable for the audience. Free tier 200/mo to drive adoption.

Open / closed split

  • Open: Aksharamukha wrapper, regex-based detection, basic transliteration.

  • Closed: name-variant database (hand-curated), pincode → locality fast lookup (precomputed from India Post + OSM), address parser ML model.

Notes

  • Aksharamukha is open-source — full credit + sponsorship. Don't try to compete with it; use it via their hosted API or self-host.

  • This is a "boring infrastructure" play — never hits viral growth, but installs once and stays installed.

See also


Sister MCPs

All from the same operator, all live on <product>.prakhar-cognizance.workers.dev, all free-tier friendly:

Full catalog: https://github.com/guptaprakhariitr · ⭐ = empty-quadrant / highest-conviction pick.

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license - not found
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quality - not tested
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maintenance

Maintenance

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