India assigns every registered company a 21‑character Corporate Identification Number (CIN). Each position carries a signal: listing status, industry classification, state code, year of incorporation, then a six‑digit sequence. Anyone tracing ownership chains across borders notices quickly that the Ministry of Corporate Affairs dataset behaves unlike most European registers.

The MCA registry acts as the statutory record for Indian companies and LLPs. Most people reach it through the MCA portal. Another entry point sits in the government’s open data catalogue at data.gov.in, where parts of the register appear as downloadable datasets. OpenRegistry queries that catalogue directly. The response mirrors the upstream fields. No scoring layer. No attempt to interpret the values. If the register publishes a column, the API returns the same column.

Fields you actually get back

The MCA dataset mixes routine administrative attributes with identifiers investigators rely on when following ownership trails. A standard company profile response includes entries such as:

• CIN
• company_name
• company_status such as Active, Strike Off, or Under Liquidation
• class_of_company
• company_category
• date_of_incorporation
• registered_office_address
• roc_code, which identifies the relevant Registrar of Companies office

OpenRegistry keeps the MCA column names intact inside jurisdiction_data. That detail matters. Court filings, insolvency orders, and regulatory notices often cite those exact labels, so matching them becomes straightforward.

Officer data arrives through a separate query. Director listings typically include:

• director_name
• din (Director Identification Number)
• designation
• appointment_date

The DIN is the stable anchor. One individual may sit on dozens of boards across unrelated entities. The identifier lets you pivot cleanly from one company to another without guessing whether two similar names refer to the same person. Anyone who has tried mapping common surnames in Mumbai incorporations will recognise the problem.

Filings appear as well. When present, list_filings returns entries attached to the company’s CIN. Each item usually carries a description, the filing date, plus a document identifier. That identifier can then be passed to fetch_document if the underlying dataset exposes the file.

Gaps in the public dataset

The MCA register does not operate as a beneficial ownership database in the sense many investigators expect. India introduced Significant Beneficial Owner rules through amendments to the Companies Act. Public datasets released through data.gov.in still fall short of a full beneficial ownership register.

That gap becomes visible in cross‑border work. A CIN places an entity inside the administrative structure of the register. It does not reveal the natural person controlling the shareholding chain behind the company.

Historical data presents another constraint. The upstream dataset generally reflects the present state of the record. If a director resigned years ago and the current listing no longer shows them, the API output will not reconstruct that earlier timeline. The past disappears unless you captured it when it was still listed.

Document access varies too. Some filings referenced in the dataset link to documents that remain gated behind the MCA portal. Reporters often end up retrieving certain PDFs by hand.

Querying the MCA dataset through MCP

OpenRegistry exposes the Indian register through the same MCP tools used for the other 27 jurisdictions available through the server. The request pattern stays consistent across countries. That consistency helps once an investigation moves from one jurisdiction to another.

Searching by company name:

search_companies({
 "jurisdiction": "IN",
 "query": "Adani Enterprises"
})

Fetching the company profile using the CIN:

get_company_profile({
 "jurisdiction": "IN",
 "company_number": "L17120GJ1993PLC019067"
})

Retrieving the current directors:

get_officers({
 "jurisdiction": "IN",
 "company_number": "L17120GJ1993PLC019067"
})

Listing filings tied to the company:

list_filings({
 "jurisdiction": "IN",
 "company_number": "L17120GJ1993PLC019067"
})

Each request queries the MCA‑derived dataset rather than a rewritten aggregation layer. The raw fields appear under jurisdiction_data. That structure preserves the original schema so the response can be checked against the source register.

Practical use in cross‑border reporting

Indian entities show up frequently in ownership chains tied to commodities trading, infrastructure development, and political finance reporting. Large investigative collaborations encounter them again and again.

The CIN structure gives an early geographic hint. Characters six and seven encode the state associated with the Registrar of Companies. Gujarat incorporations use GJ. Maharashtra entries usually carry MH. A small clue, but it narrows the administrative trail before any document search begins.

DIN numbers help once directors surface across several registers. A person listed on an Indian board may appear as an officer in another jurisdiction. When building a network graph of related companies, that single identifier removes a lot of guesswork.

OpenRegistry exposes the MCA dataset through the same MCP interface used for the UK Companies House register, the Polish KRS, and Russia’s EGRUL extracts. Anyone who has spent time navigating CAPTCHA‑heavy registry sites will recognise the change in workflow.

Connection details and usage examples sit at https://openregistry.sophymarine.com.