# India Tender Intelligence MCP (`nachiketagrawal/india-tender-intelligence-mcp`) Actor AI-native tender search across 50+ Indian government portals (CPPP, GeM, state e-procurement). Connect Claude, Cursor, or any MCP client to find, analyze, and monitor tenders with smart filtering and alerts via natural language. - **URL**: https://apify.com/nachiketagrawal/india-tender-intelligence-mcp.md - **Developed by:** [Nachiket Agrawal](https://apify.com/nachiketagrawal) (community) - **Categories:** MCP servers, Automation, E-commerce - **Stats:** 1 total users, 0 monthly users, 0.0% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing from $3.00 / 1,000 results 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 ## 🏛️ India Tender Intelligence MCP **The first AI-native tender search engine for India.** Stop checking 50+ government portals manually — let AI find your tenders. ### What does India Tender Intelligence MCP do? India Tender Intelligence MCP is a **Model Context Protocol (MCP) server** that gives AI agents (Claude, Cursor, Windsurf, and any MCP-compatible client) the ability to **search, analyze, and monitor government tenders** across India's fragmented procurement ecosystem. It scrapes and normalizes data from **CPPP (Central Public Procurement Portal)** and returns structured tender data that AI agents can reason about — including title, organization, estimated value, deadlines, and document links. **Why Apify?** Built on Apify's Standby mode for 24/7 availability, with built-in proxy rotation, pay-per-event billing, and seamless cloud deployment. ### Why use India Tender Intelligence MCP? - **Unified Search**: Query CPPP (and soon GeM + 28 state portals + PSUs) in one call - **AI-Native**: Works with Claude Desktop, Cursor, and any MCP client — ask questions in natural language - **Real-Time Data**: Fresh tender data scraped on-demand with intelligent caching - **Structured Output**: Clean JSON with normalized dates, values, and categories - **Pay-Per-Use**: Only $0.05 per search, $0.03 per detail fetch — no monthly subscription required - **Smart Filtering**: Filter by keyword, category, state, value range, deadline, and organization ### How to use India Tender Intelligence MCP #### Step 1: Connect via MCP Add to your MCP client configuration: ```json { "mcpServers": { "india-tenders": { "url": "https://YOUR_USERNAME--india-tender-intelligence-mcp.apify.actor/mcp" } } } ```` #### Step 2: Search for tenders Ask your AI agent: > "Find road construction tenders in Maharashtra closing next month" Or use the tool directly: ```json { "tool": "search_tenders", "arguments": { "keyword": "road construction", "state": "Maharashtra", "category": "Works", "max_results": 10 } } ``` #### Step 3: Get tender details ```json { "tool": "get_tender_detail", "arguments": { "tender_id": "cppp_ref-12345", "include_documents": true } } ``` ### Input | Parameter | Type | Default | Description | |---|---|---|---| | `defaultState` | string | `""` | Default state filter for searches | | `cacheTtlMinutes` | integer | `60` | Cache TTL in minutes (5–1440) | | `maxResultsPerSearch` | integer | `20` | Max results per search (1–100) | ### Output Example JSON output from `search_tenders`: ```json { "success": true, "data": [ { "tender_id": "cppp_nit-2026-road-mh-001", "title": "Construction of 4-lane highway NH-48 bypass", "organization": "National Highways Authority of India", "state": "Maharashtra", "category": "Works", "estimated_value": 150000000, "value_currency": "INR", "bid_submission_closing": "2026-07-15T17:00:00.000Z", "status": "active", "portal_url": "https://eprocure.gov.in/cppp/..." } ], "metadata": { "cached": false, "resultCount": 1, "portalSource": "cppp" } } ``` You can download the dataset in various formats such as JSON, HTML, CSV, or Excel from the Apify Console. ### Data Fields | Field | Type | Description | |---|---|---| | `tender_id` | string | Unique composite ID (portal\_referenceNo) | | `title` | string | Tender title/subject | | `organization` | string | Issuing government organization | | `state` | string | Indian state or "Central" | | `category` | string | Works, Goods, Services, or Consultancy | | `estimated_value` | number | Estimated value in INR | | `bid_submission_closing` | string | Deadline (ISO 8601) | | `status` | string | active, closing\_today, closed, cancelled, awarded | | `portal_url` | string | Direct link to tender on portal | | `contact_officer` | string | Contact person name | | `contact_email` | string | Contact email | ### How much does it cost to search Indian tenders? | Event | Price | Description | |---|---|---| | Tender Search | $0.05 | Each search query across portals | | Tender Detail | $0.03 | Fetching full tender details | | Document Extract | $0.10 | PDF text extraction (coming soon) | | Monitor Setup | $0.50 | Creating an alert rule (coming soon) | | Monitor Alert | $0.02 | Each alert notification (coming soon) | | Analytics Report | $0.25 | Historical analysis (coming soon) | Apify offers a free tier. Check [Apify pricing](https://apify.com/pricing) for details. ### Tips - Use **specific keywords** (e.g., "CCTV cameras" instead of "electronics") for better results - Filter by **state** to reduce noise — CPPP covers all central government tenders - Set `max_results` to 5–10 for faster responses; use higher values for comprehensive searches - Cached results return instantly — set `cacheTtlMinutes` based on your freshness needs ### FAQ and Support **Is it legal to scrape government tender portals?** Yes. Government tender data is public information published for transparency. We only scrape publicly available data and respect `robots.txt` and rate limits. **Which portals are currently supported?** MVP supports CPPP (eprocure.gov.in). GeM, state portals, and PSU portals are being added in Phase 2. **How fresh is the data?** Search results are cached for 1 hour by default. You can configure this via `cacheTtlMinutes`. Detail pages are cached for 2 hours. **I found a bug or have a feature request.** Please use the Issues tab on this Actor's page to report bugs or request features. **Need a custom tender intelligence solution?** Contact us for enterprise integrations, white-label options, or custom portal coverage. # Actor input Schema ## `defaultState` (type: `string`): Default Indian state to filter tender searches. Leave empty to search all states. ## `cacheTtlMinutes` (type: `integer`): How long to cache search results before fetching fresh data from portals. ## `maxResultsPerSearch` (type: `integer`): Maximum number of tenders returned per search query. ## Actor input object example ```json { "defaultState": "", "cacheTtlMinutes": 60, "maxResultsPerSearch": 20 } ``` # Actor output Schema ## `overview` (type: `string`): No description # 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("nachiketagrawal/india-tender-intelligence-mcp").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("nachiketagrawal/india-tender-intelligence-mcp").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 nachiketagrawal/india-tender-intelligence-mcp --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=nachiketagrawal/india-tender-intelligence-mcp", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "India Tender Intelligence MCP", "description": "AI-native tender search across 50+ Indian government portals (CPPP, GeM, state e-procurement). Connect Claude, Cursor, or any MCP client to find, analyze, and monitor tenders with smart filtering and alerts via natural language.", "version": "0.0", "x-build-id": "cOAvxfav6fqRqMLW9" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/nachiketagrawal~india-tender-intelligence-mcp/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-nachiketagrawal-india-tender-intelligence-mcp", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/nachiketagrawal~india-tender-intelligence-mcp/runs": { "post": { "operationId": "runs-sync-nachiketagrawal-india-tender-intelligence-mcp", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/nachiketagrawal~india-tender-intelligence-mcp/run-sync": { "post": { "operationId": "run-sync-nachiketagrawal-india-tender-intelligence-mcp", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "defaultState": { "title": "Default State Filter", "type": "string", "description": "Default Indian state to filter tender searches. Leave empty to search all states.", "default": "" }, "cacheTtlMinutes": { "title": "Cache TTL (minutes)", "minimum": 5, "maximum": 1440, "type": "integer", "description": "How long to cache search results before fetching fresh data from portals.", "default": 60 }, "maxResultsPerSearch": { "title": "Max Results Per Search", "minimum": 1, "maximum": 100, "type": "integer", "description": "Maximum number of tenders returned per search query.", "default": 20 } } }, "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 } } } } } } } } } } ```