Drishti vs Screener.in: Which Fits Your Indian Stock Market Workflow?
Drishti and Screener.in both help people work with Indian stock market information, but they solve different parts of the research process.
Screener.in is a finished fundamental research and stock-screening application for Indian equities. Drishti is a programmable Indian stock market API and market-intelligence layer for software, research workflows, and AI agents. Choose Screener.in when you want to filter and inspect NSE/BSE companies yourself. Choose Drishti when your own system needs to retrieve, monitor, summarise, or route market events.
Key takeaways
- Screener.in wins for stock screener India workflows: ratio queries, 10–15 years of financials, company pages, peers, Excel/CSV, and email alerts.
- Drishti wins when software or an AI agent needs an Indian stock market API for NSE/BSE announcements, earnings, news, concalls, WebSockets, or MCP.
- Screener.in’s official support says it does not provide APIs; premium screen results export as CSV.
- Drishti does not ship long-history financial statements. Structured numbers from results filings are the
earnings_tableextracted from exchange announcements — on average in less than 15 seconds of the filing. - Screener.in Active Investor is listed at ₹4,999 per year; Drishti paid plans start at ₹2,000 per month (Sandbox: 1,000 trial credits).
- Many teams use both: Screener.in to discover companies, Drishti to monitor and route later events.
Which tool turns Indian stock data into AI workflows?
Drishti is the better fit when an AI workflow must retrieve Indian exchange announcements, earnings, news, concalls, or other supported market records through APIs or MCP. Screener.in is better for a person running fundamental screens and reviewing company financials. Neither product should make investment decisions for you.
Quick verdict
| If you need to... | Better fit | Why |
|---|---|---|
| Find companies using financial ratios | Screener.in | Its query builder, custom ratios, comparison columns, and saved screen alerts are made for this job |
| Study 10-15 years of company financials | Screener.in | Long-history statements, peer comparison, charts, and Excel workflows are built into the application |
| Monitor announcements, earnings, news, and concalls in your own product | Drishti | REST APIs and WebSocket streams return structured records for application workflows |
| Give Claude or another AI agent Indian-market tools | Drishti | Its hosted MCP surface is a first-party product, backed by the same market-intelligence platform |
| Download a screen into a spreadsheet | Screener.in | Premium users can export screen results to CSV and use structured Excel templates |
| Build custom routing, notifications, or a portfolio copilot | Drishti | Your code controls relevance, presentation, persistence, and delivery |
The shortest answer: Screener.in helps a person screen and analyse companies. Drishti helps software react to what is happening around those companies.
What Screener.in provides
Screener.in is designed around fundamental company research and idea discovery. Its public feature pages describe financial data for listed Indian companies, queries over 10-15 years of data, company pages, peer comparisons, watchlists, regulatory announcements, and screening with custom columns and ratios.
That makes it especially good at questions such as:
- Which companies have return on capital employed above a threshold and low debt?
- How have sales, margins, cash flow, or shareholding changed over several years?
- Which companies newly match a saved fundamental screen?
- How does one company compare with listed peers?
The research interface already exists. You write a query, inspect the results, open a company, review its financial statements and filings, and save the names you want to follow.
Screener.in also supports spreadsheet-heavy research. Its official documentation describes company exports, uploaded Excel templates, and premium CSV export for screen results. The current premium page lists a free Hobby Investor plan and an Active Investor plan at ₹4,999 per year, including higher limits for followed companies, stock and screen alerts, comparison columns, and downloads.
This is not a small advantage. If your main job is manually filtering Indian companies by fundamentals, building the same experience from APIs would add cost and engineering without improving the task.
What Drishti provides
Drishti is an Indian-market intelligence layer. Its public product and documentation expose REST APIs, WebSockets, MCP, and official JavaScript/TypeScript and Python SDKs.
The product areas include symbols, announcements, earnings, news, conference calls and transcripts, alerts, daily summaries, and batch summaries. Instead of owning the final research interface, Drishti returns structured information that another system can store, rank, display, or send somewhere else.
That fits questions such as:
- Did a portfolio company publish a material announcement?
- Can our product receive supported market-event streams without polling every page?
- Can an internal agent retrieve a recent earnings record or concall with source context?
- Can we route one event to an analyst, a review queue, Slack, email, or a customer interface?
The access method is the point. A research desk can decide which symbols matter, a fintech team can design its own user experience, and an AI agent can call a documented tool rather than depend on copied text or an undocumented scraper.
Drishti currently offers a free Sandbox with 1,000 one-time trial credits. Paid plans start at ₹2,000 per month and add the full REST catalogue, supported WebSocket products, higher limits, and MCP access for research workflows. Check current Drishti plans before designing around a specific limit.
Drishti vs Screener.in: feature comparison
| Category | Screener.in | Drishti |
|---|---|---|
| Primary product | Investor research and screening application | Market-intelligence infrastructure |
| Best-known workflow | Fundamental screens and company analysis | Event retrieval, monitoring, routing, and agent context |
| Main user | Individual investor or analyst working in a web app and Excel | Developer, fintech team, research desk, or agent builder |
| Fundamental screening | Core strength: queries, ratios, columns, screens, and alerts | Not a comparable ready-made long-history fundamental screener |
| Company research UI | Built-in company pages, charts, peer comparison, notes, and watchlists | You build or connect the interface |
| Event coverage | Announcements and updates inside the Screener.in workflow | Structured announcements, earnings, news, concalls, transcripts, and alerts |
| Programmatic access | Official support says it does not provide APIs; premium screen export is CSV | REST APIs, WebSockets, MCP, and official SDKs |
| AI workflow | Screener AI is available within Screener.in | MCP and APIs provide tools and context to external agents and applications |
| Delivery | Web interface, email alerts, Excel, and CSV | JSON responses, live streams for supported products, SDK calls, and MCP tools |
| Implementation effort | Low for the workflows already in the product | Higher, because you own the workflow and production system |
This is why calling Drishti a direct Screener.in alternative can be misleading. It is an alternative only when the real requirement is programmable market intelligence. If you want another fundamental stock screener, compare Screener.in with products that also lead with a screening interface.
The API difference matters
Screener.in can export data, but export is not the same as a production API.
Its official support article says, “Though we don't provide APIs on Screener”, and recommends premium CSV export for using screen results in Python, Java, R, Pandas, or another script. CSV is useful for periodic analysis. It is less suitable for continuous server-side retrieval, documented authentication, request limits, live delivery, or customer-facing application logic.
Drishti treats programmatic access as the product. REST works for explicit fetches and scheduled jobs. WebSockets support near-live delivery for listed streams. Official SDKs wrap application integration. Drishti MCP lets compatible AI clients call market-intelligence tools during a research or development session.
That does not make an API automatically better. It makes it better when code must own the next step.
Same company, different workflow
Suppose you are researching an Indian listed company before and after quarterly results.
With Screener.in
Before the result, you can inspect years of financial statements, compare peers, review ratios, read notes, and add the company to a watchlist. After the result, the company page and alerts help you review the updated numbers and related filings.
This is a strong workflow for an analyst or investor who wants to investigate one company at a time.
With Drishti
As soon as the exchange declares a results announcement, Drishti provides the earnings report with a structured earnings_table your application can use — on average in less than 15 seconds of the exchange filing. Your system can then retrieve or receive that event, preserve its symbol and timestamp, attach available source context, apply your own portfolio relevance rules, and route it to a product or internal process.
A team might:
- Monitor earnings and announcements for covered symbols, including the earnings report and table when the filing lands.
- Deduplicate events before saving them.
- Send high-relevance records to the responsible analyst.
- Let an internal agent prepare questions from structured context.
- Keep the source record available for human verification.
This is a stronger workflow when the research process spans several people, tools, or customer-facing surfaces.
When Screener.in is the better choice
Choose Screener.in when you want:
- A ready-made fundamental stock screener for Indian companies
- Long-history financial statements and ratio-based queries
- Company pages, peer comparison, charts, watchlists, and notes
- Saved screens and email alerts without building software
- Excel or CSV exports for manual and periodic analysis
- A lower-cost path for an individual research workflow
Screener.in is also the more sensible starting point when you do not have an engineering requirement. A flexible API is still infrastructure you have to secure, test, monitor, and turn into a usable product.
When Drishti is the better choice
Choose Drishti when you need:
- Indian-market information inside your own application or internal system
- Structured announcements, earnings, news, concalls, transcripts, or alerts
- REST for retrieval and scheduled workflows
- WebSockets for supported near-live event streams
- A first-party MCP integration for Claude or other compatible agents
- Official TypeScript or Python SDKs
- Custom relevance, routing, summarisation, storage, and user experiences
Drishti is not a shortcut around product development. It is the intelligence layer for teams that already know the workflow they need to build.
Can you use both?
Yes. For some teams, that is the most practical answer.
Use Screener.in to discover and manually study companies through fundamental filters. Use Drishti to bring subsequent announcements, earnings, news, and concall context into an internal monitor, customer product, or agent workflow.
The boundary stays clean:
- Screener.in: screen, compare, and investigate.
- Drishti: retrieve, monitor, route, and integrate.
- Your research process: verify sources, form a view, and make decisions.
Neither product removes the need to read primary filings or apply independent judgment.
Frequently asked questions
Is Drishti a Screener.in alternative?
Only for programmable workflows. Screener.in is better for fundamental screens, company pages, and long-history analysis. Drishti does not provide financial statements beyond the earnings_table extracted from exchange announcements, plus other market events via REST, WebSockets, MCP, or SDKs. Adjacent products, not drop-in replacements.
Which is better for Indian stock screening: Screener.in or Drishti?
Screener.in. For stock screener India jobs—ratio filters, long-history fundamentals, and company pages—it is the clearer fit. Choose Drishti when you need an Indian stock market API for NSE/BSE announcements, earnings tables from filings, WebSockets, or MCP agents instead of another screening UI.
Does Screener.in provide an API?
No. Screener.in’s official support says it does not provide APIs and points premium users to CSV export for screen results. That helps periodic analysis, not a documented production API. Drishti publishes REST, WebSocket, MCP, and SDK access as first-party surfaces.
How fast does Drishti return earnings tables after an exchange filing?
On average in less than 15 seconds of the exchange filing. When a results announcement is declared, Drishti can provide the earnings report with a structured earnings_table for applications to retrieve, stream, or route.
Is Drishti a fundamental stock screener?
No. It does not ship long-history financial statements or ratio screens. It delivers structured market events, including an earnings_table from results announcements. Screener.in is built for querying financial ratios and comparing companies over long periods.
Can Drishti replace Screener.in for an individual investor?
Usually not. Investors who want financials, screens, charts, and watchlists get started faster in Screener.in. Drishti helps when that information must enter custom software, automated monitoring, or an AI-assisted research process.
Do Drishti or Screener.in provide investment advice?
No. This comparison covers research tools and data workflows only. Check outputs against original company and exchange sources before any financial decision.
Which one should you choose?
Choose Screener.in for fundamental stock screening and manual Indian equity research. Choose Drishti for an Indian stock market API, custom monitoring, NSE/BSE announcement workflows, and AI-agent tooling. Use both when discovery happens in a research application but ongoing events must reach your own systems.
If the second path describes your job, start with one narrow test in the Drishti Sandbox: retrieve announcements or earnings for a small watchlist, keep the source context, and decide whether structured access improves the workflow before you build more.
