# Prediction Markets Scraper - MCP Server (`jan.turon/prediction-markets-scraper-mcp-server`) Actor Scrape live prediction market events, prices, and liquidity across 13 exchanges: Polymarket, Kalshi, Limitless, Metaculus, Smarkets, and more - **URL**: https://apify.com/jan.turon/prediction-markets-scraper-mcp-server.md - **Developed by:** [Jan Turoň](https://apify.com/jan.turon) (community) - **Categories:** Automation, Other - **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $2.00 / 1,000 prediction market data This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events. 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 ## Prediction Markets Scraper — MCP Server > **One actor. Every market. AI-ready.** Scrape live prediction market events, prices, and liquidity across **13 exchanges** — Polymarket, Kalshi, Limitless, Metaculus, Smarkets, and more — powered by the [pmxtjs](https://github.com/pmxt-dev/pmxt) unified API. Runs as an **Apify actor** for scheduled scraping and one-off runs. Because Apify connects **native MCP integration**, the data this actor collects is immediately consumable by AI agents like Claude and Cursor — no extra server required. --- ### Supported Exchanges | Exchange | Region | Type | |---|---|---| | Polymarket | Global | Crypto | | Polymarket US | US | Regulated | | Kalshi | US | Regulated (CFTC) | | Kalshi Demo | US | Demo | | Limitless | Global | Crypto | | Metaculus | Global | Forecasting | | Smarkets | Europe | Exchange | | Myriad | Global | Crypto | | Probable | Global | Crypto | | Opinion | Global | Social | | Hyperliquid | Global | DeFi | | Gemini Titan | US | Regulated | | SuiBets | Global | Crypto | --- ### Apify Platform Capabilities Running this as an Apify Actor gives you the full Apify infrastructure stack on top of the scraping logic: - **Scheduled runs** — trigger on any cron schedule (hourly snapshots, daily digests, weekly archives) via the Apify Console or API. - **Webhooks** — fire a POST to any endpoint when a run finishes, enabling downstream pipelines (Slack alerts, database writes, further actors). - **Dataset storage** — all output lands in a structured Apify Dataset, queryable via REST API, exportable as JSON/CSV/XLSX, and viewable in the Console. - **Key-value store** — the actor writes a run summary (record count, exchanges queried, finish time) to the default KV store after each run. - **Apify API** — call the actor programmatically from any language, pass input overrides per run, and read results back without ever touching the Console. - **Actor-to-actor chaining** — pipe this actor's dataset output directly into downstream actors (e.g. an LLM summariser, a notifier, a database sync actor) using Apify's dataset `getItems` API or the `Actor.metamorph()` pattern. - **MCP integration** — Apify's native [Model Context Protocol](https://docs.apify.com/platform/integrations/mcp) support lets Claude, Cursor, and other AI agents call this actor as a tool directly from the chat — no extra server or wrapper needed. - **Monitoring & alerts** — set run-failure notifications and memory/timeout limits in the Console. - **Proxy support** — plug in Apify's residential or datacenter proxies if any exchange starts rate-limiting headless requests. --- ### Pricing This actor uses **pay-per-event** billing — you only pay for what you actually scrape. | Event | Price | When charged | |---|---|---| | `actor-start` | $0.01 | Once per run, before any fetching | | `prediction-market-event` | $0.002 | Per event scraped and saved to the dataset | **Example costs:** | Run | Records | Cost | |---|---|---| | 50 events from 1 exchange | 50 | ~$0.11 | | 150 events from 3 exchanges | 150 | ~$0.31 | | 500 events, deduped cross-venue | 500 | ~$1.01 | The actor respects your `maxTotalChargeUsd` budget — if the limit is reached mid-run, it saves whatever was collected and exits cleanly without losing partial results. Prices are set in the **Publication tab** of the Apify Console. The events emitted by the code are `actor-start` and `prediction-market-event`. --- ### Input Configure the actor in Apify Console or pass a JSON input file: ```json { "exchanges": ["Polymarket", "Kalshi", "Limitless"], "query": "US election 2026", "limit": 100, "status": "active", "category": "politics", "tags": ["US", "election"], "minVolume": 50000, "minLiquidity": 10000, "includeOutcomes": true, "includeSourceMetadata": false, "crossVenueDedup": true, "outputFormat": "events" } ```` #### Input Parameters | Parameter | Type | Default | Description | |---|---|---|---| | `exchanges` | `string[]` | `[Polymarket, Kalshi, Limitless]` | Exchanges to query | | `query` | `string` | — | Keyword / natural-language search. Omit for top events by volume. | | `limit` | `number` | `50` | Max results per exchange (1–1000) | | `status` | `string` | `active` | `active` | `inactive` | `closed` | `all` | | `category` | `string` | — | Category filter (e.g. `politics`, `crypto`, `sports`) | | `tags` | `string[]` | — | Tag filter — returns events matching ANY tag | | `minVolume` | `number` | `0` | Minimum total traded volume (USD) | | `minLiquidity` | `number` | `0` | Minimum market liquidity (USD) | | `includeOutcomes` | `boolean` | `true` | Include full outcomes array (for multi-outcome markets) | | `includeSourceMetadata` | `boolean` | `false` | Attach raw venue-specific metadata to each event | | `crossVenueDedup` | `boolean` | `false` | Merge same-event records from different exchanges | | `outputFormat` | `string` | `events` | `events` | `markets` | `flat` (see below) | *** ### Output Formats #### `events` — One record per event, markets nested ```json { "id": "...", "title": "Will Trump nominate Kevin Warsh as Fed Chair?", "sourceExchange": "Polymarket", "volume": 4820000, "volume24h": 130000, "category": "politics", "tags": ["US", "Fed", "economy"], "markets": [ { "marketId": "...", "title": "Kevin Warsh", "yes": { "price": 0.72, "priceChange24h": -0.03 }, "no": { "price": 0.28, "priceChange24h": 0.03 }, "liquidity": 920000, "volume": 4820000, "resolutionDate": "2026-01-31T00:00:00Z", "status": "active" } ], "scrapedAt": "2026-06-02T10:00:00Z" } ``` #### `markets` — One record per market, event info flattened ```json { "marketId": "...", "eventTitle": "Will Trump nominate Kevin Warsh as Fed Chair?", "title": "Kevin Warsh", "yes": { "price": 0.72 }, "no": { "price": 0.28 }, "volume": 4820000, "liquidity": 920000, "resolutionDate": "2026-01-31T00:00:00Z", "sourceExchange": "Polymarket", "scrapedAt": "2026-06-02T10:00:00Z" } ``` #### `flat` — One record per outcome (Yes / No / multi-outcome) Best for price comparison, arbitrage detection, and time-series storage. ```json { "eventTitle": "Will Trump nominate Kevin Warsh as Fed Chair?", "marketTitle": "Kevin Warsh", "outcomeLabel": "Yes", "price": 0.72, "priceChange24h": -0.03, "volume": 4820000, "liquidity": 920000, "resolutionDate": "2026-01-31T00:00:00Z", "status": "active", "sourceExchange": "Polymarket", "url": "https://polymarket.com/...", "scrapedAt": "2026-06-02T10:00:00Z" } ``` All prices are normalized to `0.0–1.0` (implied probability) regardless of venue. *** ### Under the Hood This actor is built on [pmxtjs](https://github.com/pmxt-dev/pmxt), the TypeScript SDK of the PMXT unified prediction market API — think of it as the [ccxt](https://github.com/ccxt/ccxt) for prediction markets. #### Core Data Flow ``` fetchEvents(params) ← pmxtjs Exchange class │ ▼ UnifiedEvent[] ← normalized, cross-exchange schema │ ┌───┴──────────────────────────┐ │ filter (volume, liquidity) │ │ dedup (crossVenueDedup) │ └───────────────┬──────────────┘ │ Apify Dataset (events | markets | flat) ``` #### Data Model ``` UnifiedEvent ├─ id, title, description, slug ├─ url, image, category, tags[] ├─ volume, volume24h ├─ sourceExchange └─ markets: UnifiedMarket[] ├─ marketId, title, description ├─ resolutionDate, status ├─ volume, volume24h, liquidity, openInterest ├─ yes: MarketOutcome { price, priceChange24h } ├─ no: MarketOutcome { price, priceChange24h } └─ outcomes: MarketOutcome[] ← multi-outcome markets ``` #### fetchEvents Parameters (pmxtjs) The actor maps its input directly to pmxtjs `fetchEvents` params: ```typescript await api.fetchEvents({ query: 'Who will be Fed Chair?', // natural-language search limit: 50, // max results status: 'active', // active | inactive | closed category: 'politics', tags: ['US', 'Fed'], // plus: offset, cursor, sort, eventId, slug, series }); ``` # Actor input Schema ## `exchanges` (type: `array`): Prediction market venues to query. Leave empty to query all supported exchanges. ## `query` (type: `string`): Keyword or natural-language search query for events. Omit to retrieve top events by volume. ## `limit` (type: `integer`): Maximum number of events to return per exchange. ## `status` (type: `string`): Filter events by resolution status. ## `category` (type: `string`): Filter by event category (e.g. politics, crypto, sports). Leave blank for all categories. ## `tags` (type: `array`): Return only events matching ANY of these tags. ## `minVolume` (type: `number`): Only include events whose total traded volume (USD) meets this threshold. ## `minLiquidity` (type: `number`): Only include markets whose liquidity meets this threshold. ## `includeOutcomes` (type: `boolean`): When true, the full outcomes array is included (useful for multi-outcome markets). When false, only the yes/no shorthand is kept to reduce payload size. ## `includeSourceMetadata` (type: `boolean`): Attach raw venue-specific metadata to each event for advanced use-cases. ## `crossVenueDedup` (type: `boolean`): When true, events that appear on multiple exchanges are merged into a single record with an 'allExchanges' array showing arbitrage opportunities. ## `outputFormat` (type: `string`): Shape of the Apify dataset records. ## Actor input object example ```json { "exchanges": [ "Polymarket", "Kalshi" ], "query": "US election 2026", "limit": 50, "status": "active", "category": "politics", "tags": [ "US", "election" ], "minVolume": 10000, "minLiquidity": 5000, "includeOutcomes": true, "includeSourceMetadata": false, "crossVenueDedup": false, "outputFormat": "events" } ``` # Actor output Schema ## `results` (type: `string`): Scraped prediction market events, markets, or outcome prices depending on the outputFormat input. ## `summary` (type: `string`): JSON summary: totalRecords, exchanges queried, outputFormat, query, limitReached, finishedAt. # 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("jan.turon/prediction-markets-scraper-mcp-server").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("jan.turon/prediction-markets-scraper-mcp-server").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 jan.turon/prediction-markets-scraper-mcp-server --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=jan.turon/prediction-markets-scraper-mcp-server", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "Prediction Markets Scraper - MCP Server", "description": "Scrape live prediction market events, prices, and liquidity across 13 exchanges: Polymarket, Kalshi, Limitless, Metaculus, Smarkets, and more", "version": "0.0", "x-build-id": "qUKbSnGpgZV2tCfGI" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/jan.turon~prediction-markets-scraper-mcp-server/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-jan.turon-prediction-markets-scraper-mcp-server", "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": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/jan.turon~prediction-markets-scraper-mcp-server/runs": { "post": { "operationId": "runs-sync-jan.turon-prediction-markets-scraper-mcp-server", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/jan.turon~prediction-markets-scraper-mcp-server/run-sync": { "post": { "operationId": "run-sync-jan.turon-prediction-markets-scraper-mcp-server", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$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": { "exchanges": { "title": "Exchanges", "type": "array", "description": "Prediction market venues to query. Leave empty to query all supported exchanges.", "items": { "type": "string", "enum": [ "Polymarket", "PolymarketUS", "Kalshi", "KalshiDemo", "Limitless", "Metaculus", "Smarkets", "Myriad", "Probable", "Opinion", "Hyperliquid", "GeminiTitan", "SuiBets" ] }, "default": [ "Polymarket" ] }, "query": { "title": "Search Query", "type": "string", "description": "Keyword or natural-language search query for events. Omit to retrieve top events by volume." }, "limit": { "title": "Max Results per Exchange", "minimum": 1, "maximum": 1000, "type": "integer", "description": "Maximum number of events to return per exchange.", "default": 50 }, "status": { "title": "Market Status", "enum": [ "active", "inactive", "closed", "all" ], "type": "string", "description": "Filter events by resolution status.", "default": "active" }, "category": { "title": "Category", "type": "string", "description": "Filter by event category (e.g. politics, crypto, sports). Leave blank for all categories." }, "tags": { "title": "Tags", "type": "array", "description": "Return only events matching ANY of these tags.", "items": { "type": "string" } }, "minVolume": { "title": "Minimum Volume (USD)", "minimum": 0, "type": "number", "description": "Only include events whose total traded volume (USD) meets this threshold.", "default": 0 }, "minLiquidity": { "title": "Minimum Liquidity (USD)", "minimum": 0, "type": "number", "description": "Only include markets whose liquidity meets this threshold.", "default": 0 }, "includeOutcomes": { "title": "Include All Outcomes", "type": "boolean", "description": "When true, the full outcomes array is included (useful for multi-outcome markets). When false, only the yes/no shorthand is kept to reduce payload size.", "default": true }, "includeSourceMetadata": { "title": "Include Source Metadata", "type": "boolean", "description": "Attach raw venue-specific metadata to each event for advanced use-cases.", "default": false }, "crossVenueDedup": { "title": "Cross-Venue Deduplication", "type": "boolean", "description": "When true, events that appear on multiple exchanges are merged into a single record with an 'allExchanges' array showing arbitrage opportunities.", "default": false }, "outputFormat": { "title": "Output Format", "enum": [ "events", "markets", "flat" ], "type": "string", "description": "Shape of the Apify dataset records.", "default": "events" } } }, "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 } } } } } } } } } } ```