# Brazil Gov IT Opportunities Monitor (`viniman27/brazil-gov-it-opportunities`) Actor Find Brazilian PNCP public procurement opportunities related to IT/software, enrich them with items and edital/TR/ETP evidence, and output a clean scored dataset. - **URL**: https://apify.com/viniman27/brazil-gov-it-opportunities.md - **Developed by:** [Vinicius Assumpção de Araujo](https://apify.com/viniman27) (community) - **Categories:** Business, Lead generation, Automation - **Stats:** 2 total users, 1 monthly users, 77.8% runs succeeded, 0 bookmarks - **User rating**: No ratings yet ## Pricing Pay per usage This Actor is paid per platform usage. The Actor is free to use, and you only pay for the Apify platform usage, which gets cheaper the higher subscription plan you have. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-usage ## 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 ## Brazil Gov IT Opportunities Monitor Find Brazilian public procurement opportunities related to IT, software, cloud, data center, public management systems, support, and digital transformation. This Actor monitors PNCP open-proposal opportunities, enriches candidate tenders with PNCP items and document metadata, optionally downloads selected edital/TR/ETP PDF or DOCX attachments, extracts text locally, and returns a scored dataset with evidence snippets. It is designed for: - IT vendors tracking public-sector opportunities in Brazil; - consultants building bid pipelines; - market researchers monitoring public procurement demand; - teams feeding Sheets, Notion, CRM, BI, or alert workflows. ### Why this is useful PNCP is public, but raw search is noisy. Generic keywords catch health procedures, public servants, social programs, and administrative text. This Actor narrows the mess into a small set of scored opportunities and keeps the evidence: matched terms, item-level signals, documents, extracted snippets, deadlines, agencies, and values. ### Data sources - Open proposal list: `https://pncp.gov.br/api/consulta/v1/contratacoes/proposta` - Items: `https://pncp.gov.br/api/pncp/v1/orgaos/{cnpj}/compras/{ano}/{sequencial}/itens` - Documents: `https://pncp.gov.br/api/pncp/v1/orgaos/{cnpj}/compras/{ano}/{sequencial}/arquivos` - Optional local extraction from selected PDF/DOCX attachments using PyMuPDF and python-docx. ### Input | Field | Type | Default | Notes | | --- | --- | --- | --- | | `dataFinal` | string | today + 30 days | Search opportunities with proposal deadlines up to this date. Accepts `YYYY-MM-DD` or `YYYYMMDD`. | | `uf` | string | empty | Optional Brazilian state filter, e.g. `SP`, `RJ`, `DF`. | | `keywords` | array/string | IT terms | Terms used for scoring. Prefer specific phrases. | | `enrichDetails` | boolean | true | Fetch PNCP items and document metadata. | | `maxDetailRequests` | integer | 20 | Limit enriched opportunities to control runtime and rate limits. | | `extractDocuments` | boolean | false | Download and parse selected edital/TR/ETP PDF/DOCX attachments. | | `maxDocumentsToExtract` | integer | 2 | Max selected attachments parsed per enriched opportunity. | | `maxDocumentBytes` | integer | 8000000 | Hard cap per downloaded document. | | `maxExtractedChars` | integer | 18000 | Text cap per parsed document. | | `maxPages` | integer | 3 | PNCP pages to scan. Each page can return up to 50 opportunities. | | `pageSize` | integer | 50 | PNCP accepts 10 to 50. | | `minScore` | integer | 12 | Minimum IT fit score to output. | Example input: ```json { "dataFinal": "2026-07-31", "keywords": ["software", "sistema de gestão", "sistemas de gestão", "sistema informatizado", "tecnologia da informação", "informática", "computadores", "notebook", "servidor de rede", "data center", "licença de software", "cloud", "nuvem", "segurança da informação"], "enrichDetails": true, "maxDetailRequests": 20, "extractDocuments": true, "maxDocumentsToExtract": 2, "maxDocumentBytes": 8000000, "maxExtractedChars": 18000, "maxPages": 2, "pageSize": 50, "minScore": 12 } ```` ### Output dataset Each row includes: - `opportunity_id` - `title` - `matched_keywords` - `it_fit_score` - `estimated_value_brl` - `proposal_open_at` - `proposal_deadline` - `published_at` - `modality` - `purchase_status` - `agency`, `agency_cnpj`, `unit`, `city`, `state` - `item_count` - `document_count` - `matching_items` - `matching_documents` - `extracted_documents` - `pncp_url` - `summary_pt_br` `extracted_documents` contains only compact evidence, not the full document text: - document title/type/URL; - matched terms found inside the parsed attachment; - snippet around the match; - extracted character count; - download/parse errors when present. A run summary is also stored in the default key-value store as `SUMMARY`. ### Example result A local validation run scanning 100 PNCP opportunities with detail enrichment and attachment extraction found a high-confidence opportunity: - agency: Município de Osório/RS - estimated value: R$ 2.159.171,68 - score: 100 - PNCP items: 10 - PNCP documents: 13 - parsed attachments with IT evidence: 2 - detected signals: software, sistemas de gestão, informática, data center, cloud Attachment snippets confirmed systems for public management, cloud computing, data center infrastructure, migration, support, licensing, and maintenance. ### Cost and performance notes Local validation on a Mac with `maxPages=2`, `pageSize=50`, `maxDetailRequests=20`, and `extractDocuments=true` took about 46 seconds for 100 listed opportunities. For cloud/commercial runs: - start with `extractDocuments=false` for cheap broad monitoring; - enable `extractDocuments=true` for high-confidence runs or smaller state/agency slices; - measure real Apify CU after first cloud run before enabling paid pricing; - keep `maxDocumentBytes` and `maxDocumentsToExtract` conservative. No Apify Proxy is required. This Actor uses public PNCP APIs. ### Local development ```bash cd ~/Apify/actors/brazil-gov-it-opportunities /opt/homebrew/bin/python3.12 -m venv .venv . .venv/bin/activate python -m pip install -r requirements.txt python -m unittest discover -s tests -v apify validate-schema apify run --purge ``` ### Limitations - It does not submit bids or interact with procurement systems. - It does not provide legal advice. - PNCP API availability and rate limits can affect runs. - Scanned PDFs without embedded text may require OCR; this MVP intentionally avoids heavy OCR models. - Classification is keyword/scoring based, not legal analysis. ### Guardrails - Uses public PNCP data only. - Does not require Apify Proxy. - Does not require secrets in input. - Does not store full edital text by default; it stores compact snippets and evidence. - Review ToS/legal/commercial positioning before paid Store launch. # Actor input Schema ## `dataFinal` (type: `string`): Search PNCP open proposal opportunities up to this date. Use YYYY-MM-DD or YYYYMMDD. Defaults to today + 30 days. ## `uf` (type: `string`): Brazilian UF abbreviation, e.g. SP, RJ, DF. Leave empty for all Brazil. ## `keywords` (type: `array`): Keywords used to classify IT/software opportunities using base opportunity text plus PNCP item and document metadata. ## `enrichDetails` (type: `boolean`): When enabled, enriches candidates via PNCP /itens and /arquivos endpoints before scoring. ## `maxDetailRequests` (type: `integer`): Limits how many candidate opportunities receive item/document enrichment to control runtime and PNCP rate limits. ## `extractDocuments` (type: `boolean`): When enabled, downloads selected PDF/DOCX documents and extracts text locally with PyMuPDF/python-docx. Disabled by default in cloud runs until cost is measured. ## `maxDocumentsToExtract` (type: `integer`): Maximum selected edital/TR/ETP files to download and parse for each enriched opportunity. ## `maxDocumentBytes` (type: `integer`): Hard cap per downloaded file. Protects local/cloud runs from huge annexes. ## `maxExtractedChars` (type: `integer`): Text cap per document after extraction. ## `maxPages` (type: `integer`): Each PNCP page can return up to 50 opportunities. Keep low for tests. ## `pageSize` (type: `integer`): PNCP accepts 10 to 50. ## `minScore` (type: `integer`): Only output opportunities at or above this score. ## Actor input object example ```json { "dataFinal": "2026-07-31", "keywords": [ "software", "sistema de gestão", "tecnologia da informação", "informática", "computadores", "notebook", "servidor de rede", "data center", "licença de software", "cloud", "segurança da informação" ], "enrichDetails": true, "maxDetailRequests": 20, "extractDocuments": false, "maxDocumentsToExtract": 2, "maxDocumentBytes": 8000000, "maxExtractedChars": 18000, "maxPages": 3, "pageSize": 50, "minScore": 12 } ``` # Actor output Schema ## `results` (type: `string`): Dataset rows containing PNCP opportunities scored as IT/software-related. ## `summary` (type: `string`): Summary JSON stored in the default key-value store under SUMMARY. # 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 = { "dataFinal": "2026-07-31", "keywords": [ "software", "sistema de gestão", "tecnologia da informação", "informática", "computadores", "notebook", "servidor de rede", "data center", "licença de software", "cloud", "segurança da informação" ] }; // Run the Actor and wait for it to finish const run = await client.actor("viniman27/brazil-gov-it-opportunities").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 = { "dataFinal": "2026-07-31", "keywords": [ "software", "sistema de gestão", "tecnologia da informação", "informática", "computadores", "notebook", "servidor de rede", "data center", "licença de software", "cloud", "segurança da informação", ], } # Run the Actor and wait for it to finish run = client.actor("viniman27/brazil-gov-it-opportunities").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 '{ "dataFinal": "2026-07-31", "keywords": [ "software", "sistema de gestão", "tecnologia da informação", "informática", "computadores", "notebook", "servidor de rede", "data center", "licença de software", "cloud", "segurança da informação" ] }' | apify call viniman27/brazil-gov-it-opportunities --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=viniman27/brazil-gov-it-opportunities", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Brazil Gov IT Opportunities Monitor", "description": "Find Brazilian PNCP public procurement opportunities related to IT/software, enrich them with items and edital/TR/ETP evidence, and output a clean scored dataset.", "version": "0.2", "x-build-id": "JqXp4EbKz4C1fGosa" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/viniman27~brazil-gov-it-opportunities/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-viniman27-brazil-gov-it-opportunities", "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/viniman27~brazil-gov-it-opportunities/runs": { "post": { "operationId": "runs-sync-viniman27-brazil-gov-it-opportunities", "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/viniman27~brazil-gov-it-opportunities/run-sync": { "post": { "operationId": "run-sync-viniman27-brazil-gov-it-opportunities", "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": { "dataFinal": { "title": "Proposal deadline search horizon", "type": "string", "description": "Search PNCP open proposal opportunities up to this date. Use YYYY-MM-DD or YYYYMMDD. Defaults to today + 30 days." }, "uf": { "title": "State filter (optional)", "type": "string", "description": "Brazilian UF abbreviation, e.g. SP, RJ, DF. Leave empty for all Brazil." }, "keywords": { "title": "IT keywords", "type": "array", "description": "Keywords used to classify IT/software opportunities using base opportunity text plus PNCP item and document metadata.", "items": { "type": "string" } }, "enrichDetails": { "title": "Fetch PNCP items and documents", "type": "boolean", "description": "When enabled, enriches candidates via PNCP /itens and /arquivos endpoints before scoring.", "default": true }, "maxDetailRequests": { "title": "Maximum enriched opportunities", "minimum": 0, "maximum": 200, "type": "integer", "description": "Limits how many candidate opportunities receive item/document enrichment to control runtime and PNCP rate limits.", "default": 20 }, "extractDocuments": { "title": "Download and extract edital/TR/ETP documents", "type": "boolean", "description": "When enabled, downloads selected PDF/DOCX documents and extracts text locally with PyMuPDF/python-docx. Disabled by default in cloud runs until cost is measured.", "default": false }, "maxDocumentsToExtract": { "title": "Documents to extract per opportunity", "minimum": 0, "maximum": 20, "type": "integer", "description": "Maximum selected edital/TR/ETP files to download and parse for each enriched opportunity.", "default": 2 }, "maxDocumentBytes": { "title": "Maximum bytes per document", "minimum": 100000, "maximum": 50000000, "type": "integer", "description": "Hard cap per downloaded file. Protects local/cloud runs from huge annexes.", "default": 8000000 }, "maxExtractedChars": { "title": "Maximum extracted characters per document", "minimum": 1000, "maximum": 200000, "type": "integer", "description": "Text cap per document after extraction.", "default": 18000 }, "maxPages": { "title": "Maximum PNCP pages", "minimum": 1, "maximum": 20, "type": "integer", "description": "Each PNCP page can return up to 50 opportunities. Keep low for tests.", "default": 3 }, "pageSize": { "title": "PNCP page size", "minimum": 10, "maximum": 50, "type": "integer", "description": "PNCP accepts 10 to 50.", "default": 50 }, "minScore": { "title": "Minimum IT fit score", "minimum": 0, "maximum": 100, "type": "integer", "description": "Only output opportunities at or above this score.", "default": 12 } } }, "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 } } } } } } } } } } ```