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Use case · AI agents

Build an AI agent for Indian stock research

An AI agent for Indian stock research works from the data it can reach. DalalOS gives your agent 59 current MCP capabilities spanning Indian-market research, with market-data reads kept read-only. Point your agent at the endpoint and it can run repeatable, sourced workflows.

This page covers personal AI agents for Indian stock research and gives builders enough technical detail to start.

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Why agents need a dedicated data layer

Autonomous and semi-autonomous agents plan, call tools and synthesise results. For Indian markets, they need a trustworthy data source to call on each loop. DalalOS supplies that layer: structured, source-backed data with read-only market-data research capabilities and explicit freshness and provenance context.

How it works

01

Give the agent capabilities

Connect DalalOS so the agent can call search, quotes, financials, filings, peers and market context.

02

Define the workflow

The agent searches a name, pulls financials, compares peers and reads filings and ownership, in that order.

03

Synthesise & cite

The agent assembles a sourced research note and surfaces the available freshness context.

Workflows you can automate

  • Watchlist monitoring: refresh quotes, ratios and upcoming results on a schedule.
  • Company briefs: search → profile/report → financials → peers → ownership, assembled into a note.
  • Screening pipelines: filter the market by transparent raw/mechanical criteria, then enrich the hits.
  • Sector and market scans: pull sectors, indices, breadth, flows or macro context and drill into constituents.
  • Event tracking: search disclosures, inspect filing context, and surface results/corporate-action calendars.

Example agent prompts

EXAMPLE PROMPTS

  • For each name on my watchlist, fetch the latest financials and flag any with rising promoter pledge.
  • Screen mid-caps with ROCE above 20% and D/E below 0.5, then write a one-paragraph sourced brief for the first five matches.
  • Build a peer-comparison table for three private banks and note data freshness.
  • List all Nifty 500 results due this week and summarise each company's latest reported quarter.

Safety by design

  • Market-data research figures are read from cache. Filing tools may queue processing and consume quota. No tool places brokerage orders.
  • The watchlist actions add or remove symbols from the authenticated caller's DalalOS watchlist.
  • Official and public source provenance keeps inputs traceable.
  • DalalOS gives sourced facts and measures computed from fixed formulas, with no buy/sell calls.
  • Freshness context lets you gate downstream agent behavior on data age.

Dig into the data model in Indian stock market data for AI agents, or read the MCP server overview.

FAQ

Common questions

Can I build an AI agent for Indian stock research?
Yes. Connect your AI agent to DalalOS, an MCP server exposing 59 current capabilities over streamable HTTP. The agent can then search, fetch quotes, read financials and filings, compare peers, screen the market and analyse ownership and market context for NSE/BSE companies.
Do agents get trading or order access?
No. DalalOS has no brokerage or order execution tools. Market figures are read from cache. Filing tools can queue processing and use on-demand quota. 2 account-scoped actions only add or remove symbols from the caller's DalalOS watchlist. There are no buy/sell calls or target prices.
Why use MCP for an agent instead of scraping?
MCP gives the agent structured, consistent tool responses from official and public sources. Scraping pages on every run is less reliable and harder to trace. Market-data responses also carry source and freshness context.
Is the data real-time?
No. Quote-style prices are end-of-day; filings and other domains follow their publication cadence. Build agent logic around the returned freshness context, not intraday ticks.

Connect your AI to Indian stock market data

Add DalalOS as a connector and sign in once. Free to start with no card and no waitlist; paid plans from ₹199 a month when you need more.

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