# Indian IPO Tracker — API (`contented_academy/indian-ipo-tracker-api`) Actor Read API for the Indian IPO Tracker. Polling clients query IPO state via HTTPS; lazy-enqueues parses on demand. Backed by the same Postgres canonical store as the batch tracker. - **URL**: https://apify.com/contented\_academy/indian-ipo-tracker-api.md - **Developed by:** [Ujjawal Yadav](https://apify.com/contented_academy) (community) - **Categories:** Automation, MCP servers, AI - **Stats:** 1 total users, 1 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $10.00 / 1,000 get ipo detail + prospectuses This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## Indian IPO Tracker — API & MCP server A **fast read API** and **MCP server** for Indian IPO data — mainboard & SME, from DRHP filing to listing. It serves a canonical Postgres store that's kept fresh by the [Indian IPO Tracker](https://apify.com/contented_academy/indian-ipo-tracker) batch actor, so responses are **sub-second** instead of a full live scrape. Covers: SEBI DRHP filings, grey-market premium (GMP), live subscription multiples, lifecycle status, calendar dates (open / close / listing), full issue terms (price band, lot size, min investment, fresh-issue vs OFS), basis-of-allotment + anchor book, listing prices, and parsed prospectus financials (revenue / EBITDA / PAT, use of proceeds, lead managers). Two ways to call it: - **Run-based (recommended for AI agents via the Apify MCP):** call the Actor with an `action` input (e.g. `{ "action": "live_upcoming_listed" }`); results are written to the run's dataset. This is the zero-setup path for anyone who already has the Apify MCP configured. - **Standby (always-on HTTP):** call the REST endpoints directly, or connect to its `/mcp` server. ### Pricing Pay-per-event. You're charged per successful data request: | Event | When | |---|---| | `api-list-request` | listing/searching IPOs (`GET /api/ipos`, MCP `list_ipos`) | | `api-detail-request` | one IPO + prospectus (`GET /api/ipos/:id`, MCP `get_ipo`) | | `api-timeline-request` | subscription/state timeline (MCP `get_ipo_timeline`) | | `api-refresh-request` | force-refresh an IPO (premium; rate-limited) | Health/meta calls (`/healthz`, `/api/freshness`, `get_freshness`) and `304 Not Modified` responses are **free**. ### REST API Base URL: `https://contented-academy--indian-ipo-tracker-api.apify.actor` Authenticate with your Apify token (`?token=` or `Authorization: Bearer `). | Method & path | Description | |---|---| | `GET /api/ipos` | List/search IPOs (returns ALL matching rows, no pagination). Query: `view` (`live_upcoming` \| `live_upcoming_listed`, default), `category` (`mainboard`\|`sme`), `q` (name search), `gmp_min`, `listing_date_gte`, `listing_date_lte`. | | `GET /api/ipos/:id` | Full record for one IPO incl. prospectus, basis-of-allotment, anchors, and latest GMP. | | `GET /api/ipos/:id/timeline` | Subscription-bidding timeline + lifecycle state history. | | `POST /api/ipos/:id/refresh` | Bump an IPO to the front of the refresh queue (premium, rate-limited). | | `GET /api/events` | Recent lifecycle state-change events (paginated). | | `GET /api/freshness` | Pipeline health snapshot (free). | | `GET /healthz` | Liveness (free). | Responses are cached (60 s) and carry strong `ETag`s — send `If-None-Match` to get a free `304`. #### Example ```bash curl "https://contented-academy--indian-ipo-tracker-api.apify.actor/api/ipos?status=SUBSCRIPTION_OPEN&category=sme&token=$APIFY_TOKEN" ```` ### MCP server Endpoint: `/mcp` (Streamable HTTP). Discoverable + callable through the Apify hosted MCP at `https://mcp.apify.com`, or connect directly to the standby URL `…/mcp`. | Tool | Arguments | Returns | |---|---|---| | `list_ipos` | `view?` (`live_upcoming`|`live_upcoming_listed`), `category?`, `q?`, `gmp_min?`, `listing_date_gte?`, `listing_date_lte?` | IPO summaries (GMP, subscription, dates, lot size) + count | | `get_ipo` | `ipo_id` | Full IPO record incl. prospectus financials, basis-of-allotment, anchors, latest GMP | | `get_ipo_timeline` | `ipo_id` | Subscription timeline + state history | | `get_freshness` | — | Pipeline health snapshot (free) | | `refresh_ipo` | `ipo_id` | Force-refresh (premium, rate-limited) | Typical agent flow: `list_ipos` to find an `ipo_id`, then `get_ipo` for full detail. ### Run-based (call-actor) If you call the Actor through the Apify MCP's generic `call-actor` (or the Apify API / Console), pass an `action` and read the run's dataset: ```json { "action": "live_upcoming_listed", "gmp_min": 30 } ``` `action` values: `live_upcoming`, `live_upcoming_listed` (default), `get` (needs `ipo_id`), `timeline` (needs `ipo_id`), `freshness`. List actions return ALL matching IPOs (no pagination), ordered by lifecycle relevance (live → upcoming → listed). ### Notes - Data is sourced from public sources (SEBI, BSE, NSE, GMP aggregators) and parsed prospectus PDFs. Figures are best-effort and should be verified against the official filing before any financial decision. - Freshness depends on the batch tracker's worker cadence; `GET /api/freshness` reports the most recent update timestamps. # Actor input Schema ## `action` (type: `string`): What to fetch. 'live\_upcoming' = IPOs open for subscription now + the upcoming pipeline (filed/approved, not yet open). 'live\_upcoming\_listed' = the above plus recently listed IPOs (everything except withdrawn/expired). Both return ALL matching IPOs, ordered by lifecycle (live → upcoming → listed). 'get' = one IPO + prospectus (needs ipo\_id). 'timeline' = subscription + state history (needs ipo\_id). 'freshness' = pipeline health snapshot. ## `ipo_id` (type: `string`): Canonical IPO id (required for action 'get' and 'timeline'). Obtain it from a list run. ## `category` (type: `string`): Board type. ## `q` (type: `string`): Case-insensitive company-name search (2-80 chars). ## `listing_date_gte` (type: `string`): YYYY-MM-DD lower bound on listing date. ## `listing_date_lte` (type: `string`): YYYY-MM-DD upper bound on listing date. ## `gmp_min` (type: `integer`): Only return IPOs whose current grey-market premium is at least this many rupees. ## Actor input object example ```json { "action": "live_upcoming_listed" } ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("contented_academy/indian-ipo-tracker-api").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("contented_academy/indian-ipo-tracker-api").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call contented_academy/indian-ipo-tracker-api --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=contented_academy/indian-ipo-tracker-api", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Indian IPO Tracker — API", "description": "Read API for the Indian IPO Tracker. Polling clients query IPO state via HTTPS; lazy-enqueues parses on demand. Backed by the same Postgres canonical store as the batch tracker.", "version": "0.2", "x-build-id": "ZnqZeDN7j4Y2cxThY" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/contented_academy~indian-ipo-tracker-api/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-contented_academy-indian-ipo-tracker-api", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/contented_academy~indian-ipo-tracker-api/runs": { "post": { "operationId": "runs-sync-contented_academy-indian-ipo-tracker-api", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/contented_academy~indian-ipo-tracker-api/run-sync": { "post": { "operationId": "run-sync-contented_academy-indian-ipo-tracker-api", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": { "action": { "title": "Action", "enum": [ "live_upcoming", "live_upcoming_listed", "get", "timeline", "freshness" ], "type": "string", "description": "What to fetch. 'live_upcoming' = IPOs open for subscription now + the upcoming pipeline (filed/approved, not yet open). 'live_upcoming_listed' = the above plus recently listed IPOs (everything except withdrawn/expired). Both return ALL matching IPOs, ordered by lifecycle (live → upcoming → listed). 'get' = one IPO + prospectus (needs ipo_id). 'timeline' = subscription + state history (needs ipo_id). 'freshness' = pipeline health snapshot.", "default": "live_upcoming_listed" }, "ipo_id": { "title": "IPO id", "type": "string", "description": "Canonical IPO id (required for action 'get' and 'timeline'). Obtain it from a list run." }, "category": { "title": "Category (list)", "enum": [ "mainboard", "sme" ], "type": "string", "description": "Board type." }, "q": { "title": "Search query (list)", "type": "string", "description": "Case-insensitive company-name search (2-80 chars)." }, "listing_date_gte": { "title": "Listing date from (list)", "type": "string", "description": "YYYY-MM-DD lower bound on listing date." }, "listing_date_lte": { "title": "Listing date to (list)", "type": "string", "description": "YYYY-MM-DD upper bound on listing date." }, "gmp_min": { "title": "Minimum GMP ₹ (list)", "minimum": 0, "type": "integer", "description": "Only return IPOs whose current grey-market premium is at least this many rupees." } } }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```