# Data Source: https://docs.platform.statista.ai/api-reference/data-api/get-consumerinsights GET /v1/data/consumer-insights Retrieve cross tabulated survey data for a combination of question and answer ID(s). Answer IDs consist of the question ID, a postfix of '#', and a number, such as `v0025_demo_regiondeu#3`. Impact of **rows**, **columns**, and **filter** parameter combinations on the result: * only **rows** provided: “frequency table” (like “Internet provider“, rows are Telekom, Vodafone, …, there is a single column that contains how many respondents picked the respective answer) * **rows** and **columns** provided: compute a “cross table” such as (“Internet provider by generation”, rows are Telekom, Vodafone, … columns are Baby Boomer, Gen X, … cells contain values like “what percentage of Gen X uses Vodafone”) * **rows** and **filters** provided: the same as “frequency table” but restricted to only the group of respondents that matches the filter * **rows**, **columns**, and **filters** provided: cross table but restricted to the group of respondents that matches the filter ## Filters Filters are a comma-separated list of answer IDs. Filters on different questions are AND, filters on the same question are OR. Example: `v0013g_demo_generation#4,v0025_demo_regiondeu#3,v0025_demo_regiondeu#6` Interpretation: `Gen Z AND (living in Hamburg OR living in Berlin)` # Data Source: https://docs.platform.statista.ai/api-reference/data-api/get-marktetinsights-indicators GET /v1/data/market-insights/indicator Retrieve chart data for a specific Market Insights indicator. # Reports Source: https://docs.platform.statista.ai/api-reference/data-api/get-reports GET /v1/data/reports This is a **legacy endpoint**, maintained for backwards compatibility and may be deprecated in a future release. # Data Source: https://docs.platform.statista.ai/api-reference/data-api/get-statistic GET /v1/data/statistic Retrieve chart data for a specific Statistic. # Infographics Source: https://docs.platform.statista.ai/api-reference/discovery-advanced/get-infographics GET /v1/infographics This is a **legacy endpoint**, maintained for backwards compatibility and may be deprecated in a future release. # Market Insights Source: https://docs.platform.statista.ai/api-reference/discovery-advanced/get-marketInsights GET /v1/marketInsights This is a **legacy endpoint**, maintained for backwards compatibility and may be deprecated in a future release. For new integrations, use the [Search Market Insights](/api-reference/discovery-advanced/get-search-marketinsights-indicators) endpoint instead. # Search Source: https://docs.platform.statista.ai/api-reference/discovery-advanced/get-search-consumerinsights GET /v1/search/consumer-insights Semantically search in Consumer Insights survey data for questions and answers. The results are grouped by question. If only an answer matches, the corresponding question is added to the result. The search works best with short search terms that cover only one aspect, such as “gen z” or “headphone brands”. Filtering by country can be done when the actual survey cross-table data is fetched, by providing a geo location. Adding a country to the search query degrades result quality. # Search Source: https://docs.platform.statista.ai/api-reference/discovery-advanced/get-search-marketinsights-indicators GET /v1/search/market-insights/indicators Semantically search Market Insights indicators using natural language or keywords. # Search Source: https://docs.platform.statista.ai/api-reference/discovery-advanced/get-search-statistics GET /v1/search/statistics Semantically search Statistics using natural language or keywords. # List Statistics Source: https://docs.platform.statista.ai/api-reference/discovery-advanced/get-statistics GET /v1/statistics This is a **legacy endpoint**, maintained for backwards compatibility and may be deprecated in a future release. For new integrations, use the [Search Statistics](/api-reference/discovery-advanced/get-search-statistics) endpoint instead. # Studies Source: https://docs.platform.statista.ai/api-reference/discovery-advanced/get-studies GET /v1/studies This is a **legacy endpoint**, maintained for backwards compatibility and may be deprecated in a future release. # Introduction Source: https://docs.platform.statista.ai/api-reference/introduction How to get the most out of the Statista API Questions or requests for API keys? Please fill out [our questionnaire](https://platform.statista.ai/join) ## Overview The Statista API allows secure access to data, enabling seamless integration into your applications and workflows. Use this documentation to understand available endpoints, authentication, api packages and how to retrieve the data you need efficiently. ## Authentication All API endpoints are authenticated including the x-api-key in a request header. ```json theme={null} "x-api-key": ``` ## Integration If you're integrating into LLM-based services or programmatically building AI Agents, you may want to look at our MCP offering. Stateless MCP Server for Market Research # Poll Job on Research AI Source: https://docs.platform.statista.ai/api-reference/research-ai/get-researchAi GET /v1/research-ai/answer This is a **legacy endpoint**, maintained for backwards compatibility and may be deprecated in a future release. If you're building with LLMs, check out our [MCP Server](/mcp-server/introduction). # Submit Job on Research AI Source: https://docs.platform.statista.ai/api-reference/research-ai/post-researchAi POST /v1/research-ai/ask This is a **legacy endpoint**, maintained for backwards compatibility and may be deprecated in a future release. If you're building with LLMs, check out our [MCP Server](/mcp-server/introduction). # Updates Source: https://docs.platform.statista.ai/changelogs/updates Changelogs for the APIs and MCP Server REST API & MCP Server The Consumer Insights REST endpoints and MCP now provide access to brand profiler data. MCP Server The following MCP endpoints, which where used for beta testing, are now removed: * /v1/mcp/beta/consumer-insights * /v1/mcp/beta/market-insights * /v1/mcp/beta/copilot-mi * /v1/mcp/beta/copilot-ci All the MCP tools are availabel at `/v1/mcp/`. REST API * Release of the Consumer Insights REST API, including search and data lookup endpoints. Please see the [documentation](https://docs.platform.statista.ai/api-reference/discovery-advanced/get-search-consumerinsights) for more details. REST API * Release of the Market Insights REST API, including search and data lookup endpoints. Please see the [documentation](https://docs.platform.statista.ai/api-reference/introduction) for more details. MCP Server * Release of the Market Insights MCP tools for both `/v1/mcp` and `/v1/mcp/copilot`, supporting searching and fetching market insights and forcasts. For more details visit the [documentation](https://docs.platform.statista.ai/mcp-server/introduction#available-tools). MCP Server * The Consumer Insights fetch tool description/prompt was too long for usage in some models. We made a new, more compact prompt, including guidelines to prevent false usage. * The Consumer Insights fetch tool input schema includes additional information to guide LLM towards better inputs. MCP Server * The Consumer Insights fetch tool now supports calculating crosstabs across different splits. If no participant answered both questions the data is filled in based on demographics. MCP Server * Prompts/descriptions updated for Statistics and Consumer Insights tools: Unnecessary whitespace and line breaks removed. * Tool parameter descriptions moved from the description to the input schema, to make them more compact. MCP Server * Support for searching in Consumer Insights surveys and fetching detailed cross-tabulated data for survey question and answer combinations. * Consumer Insights MCP tools are available on the `/v1/mcp` and the Copilot specific endpoint `/v1/mcp/copilot`. REST API * Chart images are now displayed in source language. * `total_count` field now shows correct number in `/search/statistics`. * Similarity score for search results appended to `/search/statistics` under `ranking_score`. * Update API timeout from 5s to 30s to allow longer-running operations and avoid breakage in client systems. * Multilingual search queries for `/search/statistics` * Extended authorization to include both `x-api-key` as custom header and `Authorization: Bearer`. MCP Server * Support DeepResearch response format and tool names under `/beta/deepresearch`. * Coerce ID parameter to avoid runtime errors when LLMs pass in a numerical string. * Automate MCP Client compatibility tests across LLM providers: OpenAI, Anthropic/Claude, Gemini. * Condense output of `search-statistics` tool to reduce LLM token consumption by 35% # Connect to Claude Desktop (Mac) Source: https://docs.platform.statista.ai/mcp-server/connection-claude Connect the Statista MCP Server to Claude Desktop on Mac ## Install Claude Desktop Install [Claude Desktop](https://claude.ai/download) (important that it's the desktop version). Install [node.js](https://nodejs.org/en/download), needed for the `mcp-remote` integration. If you don't already have one, create an account. Launch the app to get started. ## Modify configuration file Under **Settings**, go to **Developer**. Click settings Click **Edit Config**. Click edit config Open the `claude_desktop_config.json` file in a text editor. Copy/paste the snippet below into the file, replacing `YOUR_API_KEY` with the provided API Key. ```.json theme={null} { "mcpServers": { "statista": { "command": "npx", "args": [ "-y", "mcp-remote", "https://api.statista.ai/v1/mcp", "--transport", "http-only", "--header", "x-api-key: ${API_KEY}" ], "env": { "API_KEY": "YOUR_API_KEY" } } } } ``` Save your changes. ## Use the MCP Server in Claude Desktop Once your configuration file is successfully modified and saved, close down Claude Desktop and open it again. Now, under **Search and tools** you should see **statista** enabled. Statista tool should be enabled You're good to go! Now you can do market research with Statista and Claude Desktop on Mac 🎉 # Connect to Claude Desktop (Windows) Source: https://docs.platform.statista.ai/mcp-server/connection-claude-windows Connect the Statista MCP Server to Claude Desktop on Windows ## What you'll need * Your Statista API Key * Claude Desktop installed on your PC * Node.js installed (we'll help you install this) ## Step-by-step instructions 1. Open your web browser 2. Go to: [https://nodejs.org/](https://nodejs.org/) 3. Click the big green button that says "LTS" (Recommended for Most Users) 4. Find the downloaded file in your Downloads folder and double-click it 5. Click "Next" on everything until it finishes installing 6. Restart your computer Keep this somewhere safe — you'll need it in a moment! * Press `Windows Key + R` on your keyboard (this opens the "Run" box) * Type exactly: `%APPDATA%\Claude` * Press `Enter` — a folder will open Look for a file called `claude_desktop_config.json`. **If the file EXISTS:** Right-click it → Open with → Notepad **If the file DOESN'T exist:** * Right-click in the empty space → New → Text Document * Name it: `claude_desktop_config.json` * Open it with Notepad **Delete everything** in the file (if there's anything there), then paste this: ```json theme={null} { "mcpServers": { "statista": { "command": "C:\\PROGRA~1\\nodejs\\npx.cmd", "args": [ "-y", "mcp-remote", "https://api.statista.ai/v1/mcp", "--transport", "http-only", "--header", "x-api-key: ${API_KEY}" ], "env": { "API_KEY": "INSERT KEY HERE" } } } } ``` Find this line near the bottom: `"API_KEY": "INSERT KEY HERE"` Replace `INSERT KEY HERE` with your actual Statista API key from Step 2. For example, if your key is `sk_1234abcd5678efgh`, it should look like: ```json theme={null} "API_KEY": "sk_1234abcd5678efgh" ``` Important: Keep the quotes ("") around your key. * In Notepad, click File → Save as .js * Close Notepad * Completely close Claude Desktop (hard exit under "Files") * Open Claude Desktop again Look for the Statista icon or tools indicator in Claude — this means it's connected! Toggle Statista MCP Make sure Statista is toggled on as a connector and then ask a Statista-related question. If the connection has been properly enabled, Claude will fetch live data from Statista for you! ## Troubleshooting * Make sure you installed Node.js from **Step 1** * Make sure you restarted your computer after installing Node.js * Try opening Claude again * Make sure you completely closed and reopened Claude * Check that your API key is correct (no extra spaces) * Make sure the quotes are in the right places * Check that you have all the curly braces `{` and `}` * Check that every line except the last one in each section has a comma `,` * Try copying the code again from this document # Connect to Cursor Source: https://docs.platform.statista.ai/mcp-server/connection-cursor Connect the Statista MCP Server to Cursor on Mac and Windows ## What you'll need * Your [Statista API key](/start/request-api-key) * [Cursor](https://cursor.com/download) installed on Mac or Windows * [Node.js](https://nodejs.org/) 20 or later (needed for the `mcp-remote` integration) ## Install Cursor To connect the Statista MCP Server with Cursor, follow these steps: 1. Install [Cursor](https://cursor.com/download) for Mac or Windows 2. If you don't already have one, create an account 3. Open Cursor ## Connect via mcp.json Add the server by editing an MCP configuration file: * **Project scope**: `.cursor/mcp.json` in your project root * **Global scope (Mac)**: `~/.cursor/mcp.json` * **Global scope (Windows)**: `%USERPROFILE%\.cursor\mcp.json` **Mac:** ```json theme={null} { "mcpServers": { "statista": { "command": "npx", "args": [ "-y", "mcp-remote", "https://api.statista.ai/v1/mcp", "--transport", "http-only", "--header", "x-api-key: ${API_KEY}" ], "env": { "API_KEY": "YOUR_API_KEY" } } } } ``` **Windows:** ```json theme={null} { "mcpServers": { "statista": { "command": "C:\\PROGRA~1\\nodejs\\npx.cmd", "args": [ "-y", "mcp-remote", "https://api.statista.ai/v1/mcp", "--transport", "http-only", "--header", "x-api-key: ${API_KEY}" ], "env": { "API_KEY": "YOUR_API_KEY" } } } } ``` Replace `YOUR_API_KEY` with your provided [Statista API key](/start/request-api-key). On Windows, use the full path to `npx.cmd` as shown — plain `npx` often fails in desktop apps that do not inherit your system PATH. Save the file and restart Cursor. ## Verify the connection 1. Open a Cursor chat or Agent session 2. Confirm **statista** appears under available MCP tools 3. Ask a market research question — the model should be able to use Statista tools such as `search-statistics` and `get-chart-data-by-id` ## Troubleshooting * **401 authentication error**: confirm the `x-api-key` header is set correctly * **Connection fails**: confirm Node.js 20+ is installed and try `npx mcp-remote@latest` * **Windows: command not found**: use `C:\\PROGRA~1\\nodejs\\npx.cmd` instead of `npx` in the JSON config * **Server not loading**: open **Output** (`Cmd+Shift+U` on Mac / `Ctrl+Shift+U` on Windows) → select **MCP Logs** from the dropdown You're good to go! Now you can do market research with Statista and Cursor. # Build using Python FastMCP Source: https://docs.platform.statista.ai/mcp-server/connection-fastmcp Connect the Statista MCP Server to a Python FastMCP Client This guide requires an installation of Python and `fastmcp` library. If you do not know what that is; this guide is not intended for you. Run `pip install fastmcp` and read the [FastMCP documentation](https://gofastmcp.com/getting-started/welcome). ```sh theme={null} pip install fastmcp ``` ```sh theme={null} mcp_api_key = "" mcp_server_url = "" ``` ```py theme={null} from fastmcp import Client from fastmcp.client.transports import StreamableHttpTransport import asyncio import json mcp_client = Client( transport=StreamableHttpTransport( mcp_server_url, headers={"x-api-key": mcp_api_key}, ), ) async def main(): async with mcp_client as client: # List available tools tools = await client.list_tools() # Call search-statistics with a natural language query statistics = await client.call_tool("search-statistics", {"query": "What's the GDP of Japan?"}) print(json.loads(statistics.content[0].text)) # grab the first statistic id grab_statistic_id = json.loads(statistics.content[0].text)["items"][0]["identifier"] # fetch chart data for a specific statistic id statistic_chart_data = await client.call_tool("get-chart-data-by-id", {"id": int(grab_statistic_id)}) statistic_id = json.loads(statistic_chart_data.content[0].text) chart_data = statistic_chart_data.content[1].text if __name__ == "__main__": asyncio.run(main()) ``` # Connect to Google Gemini Source: https://docs.platform.statista.ai/mcp-server/connection-gemini Connect the Statista MCP Server to Gemini via the google-genai SDK Gemini supports MCP servers natively through the `google-genai` Python SDK — no FastMCP wrapper required. Google currently labels their MCP integration as **experimental**, so the exact API surface may evolve over time. The recommended way to connect Gemini to the Statista MCP server is to use the official [`mcp`](https://pypi.org/project/mcp/) Python package's streamable HTTP transport, then pass the resulting MCP session directly to Gemini as a tool. ```sh theme={null} pip install google-genai mcp ``` Pass your Statista API key as the `x-api-key` header, then hand the MCP session directly to Gemini. ```python theme={null} from google import genai from mcp import ClientSession from mcp.client.streamable_http import streamablehttp_client mcp_server_url = "" YOUR_STATISTA_API_KEY = "" YOUR_GEMINI_API_KEY = "" async with streamablehttp_client( mcp_server_url, headers={"x-api-key": YOUR_STATISTA_API_KEY}, ) as (read_stream, write_stream, _): async with ClientSession(read_stream, write_stream) as session: await session.initialize() client = genai.Client(api_key=YOUR_GEMINI_API_KEY) response = await client.aio.models.generate_content( model="gemini-3.5-flash", contents="What is the ice cream market in Japan?", config=genai.types.GenerateContentConfig( temperature=0, tools=[session], ), ) print(response.text) ``` The `ClientSession` object is passed directly into the `tools` list — Gemini introspects the MCP session's available tools and invokes them automatically as needed. ## Alternative: using FastMCP If you're already using [`fastmcp`](https://pypi.org/project/fastmcp/) elsewhere in your stack, you can pass its session to Gemini the same way. This is functionally equivalent to the native pattern above, just with FastMCP's higher-level wrapper. ```python theme={null} from google import genai from fastmcp import Client from fastmcp.client.transports import StreamableHttpTransport mcp_client = Client( transport=StreamableHttpTransport( mcp_server_url, headers={"x-api-key": YOUR_STATISTA_API_KEY}, ), ) client = genai.Client(api_key=YOUR_GEMINI_API_KEY) async with mcp_client: response = await client.aio.models.generate_content( model="gemini-3.5-flash", contents="What is the ice cream market in Japan?", config=genai.types.GenerateContentConfig( temperature=0, tools=[mcp_client.session], ), ) print(response.text) ``` # Connect to OpenAI Platform Source: https://docs.platform.statista.ai/mcp-server/connection-openai Connect the Statista MCP Server to OpenAI To try the Statista MCP Server with OpenAI, follow these steps: Navigate to [platform.openai.com](https://platform.openai.com). If you don't already have one, create an account. Go to **Dashboard** → **Chat**. Click **Tools (+ Add)** and select **MCP Server**. Add the provided URL and label. Under **Authentication**, change to **Custom Headers**, set the **header** to **x-api-key**, and enter your provided [API Key](/start/request-api-key). You should now see a screen with available tools With that you've successfully connected the Statista MCP server with an OpenAI chat. # Connect to Perplexity Desktop (Mac) Source: https://docs.platform.statista.ai/mcp-server/connection-perplexity-desktop Connect the Statista MCP Server to Perplexity Desktop on Mac ## Install Perplexity Desktop Install [Perplexity Desktop](https://www.perplexity.ai/platforms) (important that it's the desktop version). If you don't already have one, create an account. Launch the app to get started. ## Set up Connector In the bottom-right corner, click the cogwheel. Open settings Click `Connectors`, then click `+ Add Connector` and choose `Advanced`. Configure connector Copy/paste this into the text-box: ```json theme={null} { "args" : [ "-y", "mcp-remote", , "--transport", "http-only", "--header", "x-api-key: \\${API_KEY}" ], "command" : "npx", "env" : { "API_KEY" : }, "useBuiltInNode" : true } ``` Replace `` and `` with provided credentials from Statista. Save your new connector. Toggle `Statista MCP` as a source. Toggle connector You're good to go! Now you can do market research with Statista and Perplexity Desktop on Mac 🎉 # Connect to Qwen Chat Desktop Source: https://docs.platform.statista.ai/mcp-server/connection-qwen Connect the Statista MCP Server to Qwen Chat Desktop on Mac and Windows MCP is available only in the Qwen Chat Desktop app on Mac and Windows — not in the web chat. ## What you'll need * Your [Statista API key](/start/request-api-key) * [Qwen Chat Desktop](https://qwen.ai/home) installed on Mac or Windows * [Node.js](https://nodejs.org/) 20 or later (needed for the `mcp-remote` integration) ## Install Qwen Chat Desktop To connect the Statista MCP Server with Qwen Chat Desktop, follow these steps: 1. Install [Qwen Chat Desktop](https://qwen.ai/home) for Mac or Windows 2. If you don't already have one, create an account 3. Open Qwen Chat Desktop ## Connect via JSON 1. In the chat window, click **MCP** 2. Go to **MCP settings** 3. Click **Add MCP** 4. Choose the JSON option 5. Copy/paste this configuration: **Mac:** ```json theme={null} { "mcpServers": { "statista": { "command": "npx", "args": [ "-y", "mcp-remote", "https://api.statista.ai/v1/mcp", "--transport", "http-only", "--header", "x-api-key: ${API_KEY}" ], "env": { "API_KEY": "YOUR_API_KEY" } } } } ``` **Windows:** ```json theme={null} { "mcpServers": { "statista": { "command": "C:\\PROGRA~1\\nodejs\\npx.cmd", "args": [ "-y", "mcp-remote", "https://api.statista.ai/v1/mcp", "--transport", "http-only", "--header", "x-api-key: ${API_KEY}" ], "env": { "API_KEY": "YOUR_API_KEY" } } } } ``` Replace `YOUR_API_KEY` with your provided [Statista API key](/start/request-api-key). On Windows, use the full path to `npx.cmd` as shown — plain `npx` often fails in desktop apps that do not inherit your system PATH. 6. Save and enable the connector ## Verify the connection Once the connector is enabled, ask a market research question in Qwen Chat. The model should be able to use Statista tools such as `search-statistics` and `get-chart-data-by-id`. ## Troubleshooting * **401 authentication error**: confirm the `x-api-key` header is set correctly * **Connection fails**: confirm Node.js 20+ is installed and try `npx mcp-remote@latest` * **Windows: command not found**: use `C:\\PROGRA~1\\nodejs\\npx.cmd` instead of `npx` in the JSON config * **Manual config inspection** (if needed): * **Mac**: `~/Library/Application Support/Qwen/settings.json` * **Windows**: `%APPDATA%\Qwen\settings.json` You're good to go! Now you can do market research with Statista and Qwen Desktop. # MCP Server Source: https://docs.platform.statista.ai/mcp-server/introduction MCP Server Introduction If you're interested in MCP access, fill out [our questionnaire](https://platform.statista.ai/join). The Statista MCP (Model Context Protocol) Server provides AI assistants with direct access to Statista's comprehensive statistical database through a **Streamable HTTP** interface. This server enables real-time data discovery and retrieval from our extensive collection of charts, reports, and forecasts. ## Key Features * **Streamable HTTP Transport**: Uses efficient streamable HTTP communication (not Server-Sent Events) * **CORS Support**: Cross-origin requests are fully supported for web applications * **Stateless**: For maximum compatibility * **Real-time Data Access**: Direct connection to Statista's live data catalogue ## MCP URL The MCP server is reachable by this URL: [https://api.statista.ai/v1/mcp](https://api.statista.ai/v1/mcp). ## Authentication The server requires authentication using a request header: ``` x-api-key: YOUR_API_KEY ``` or with a bearer token: ``` Authorization: Bearer YOUR_API_KEY ``` Your API key authenticates each session and provides access to the MCP Server. ## Available Tools **Tool ID**: `search-statistics` Searches Statista's comprehensive data catalogue to discover relevant statistical content across various industries and topics. Returns matching statistics with metadata to help you identify the most relevant data sources. **Tool ID**: `get-chart-data-by-id` Retrieves detailed statistical information for specific charts or datasets using their unique identifier. Provides complete numerical values, methodological information, source details, and contextual metadata. **Tool ID**: `search-consumer-insights` Searches Statista's Consumer Insights data catalogue to discover insights on consumer attitudes and behavior worldwide. Returns matching questions and answers with metadata across various industries and topics. **Tool ID**: `fetch-consumer-insights` Retrieves detailed survey information, cross-tabulated for the provided question and answer identifiers. The data can be filtered in addition by year and country. Provides complete numerical values, methodological information, survey details, and contextual metadata. **Tool ID**: `search-market-insights` Searches Statista's Market Insights data catalogue to discover market forecasts and expert KPIs for 1000+ markets in 190+ countries & territories. Returns matching Market Insights with metadata to help you identify the most relevant data sources. **Tool ID**: `fetch-market-insights` Retrieves detailed Market Insights datasets using their unique identifier. Provides complete numerical values, methodological information, source details, and contextual metadata. ## Getting Started 1. Obtain your Statista API key and MCP server URL 2. Connect your AI assistant to the MCP server 3. Authenticate using the API key 4. Start exploring Statista's data through the available tools The server automatically handles session management and provides comprehensive error handling for reliable data access. # Credit Logic Source: https://docs.platform.statista.ai/pricing/credit-logic Once you have procured credits with Statista Connect, you can use them across our services Credits are consumed across MCP and API endpoints on a per-request basis. Costs associated with a request to an endpoint or MCP tool will follow the credit table below: | Data Type | MCP | API | Credit Cost | | ----------------- | -------------------------- | ----------------------------------- | ----------- | | Statistics | `search-statistics` | `search/statistics` | 1 | | Statistics | `get-chart-data-by-id` | `data/statistic` | 10 | | Market Insights | `search-market-insights` | `search/market-insights/indicators` | 0 | | Market Insights | `fetch-market-insights` | `data/market-insights/indicator` | 15 | | Consumer Insights | `search-consumer-insights` | `search/consumer-insights` | 0 | | Consumer Insights | `fetch-consumer-insights` | `data/consumer-insights` | 10 | # Enrichment Source: https://docs.platform.statista.ai/prompt-library/enrichment Input your text and enrich it with Statista data This prompt works well with Claude Sonnet 4.5, creativity or temperature setting of 0.3 ```md wrap theme={null} You are a skilled Data Analyst specializing in Data Storytelling. You have expertise in economy, society, politics, business, and finance. Your main responsibility is to enrich articles with with data. Your answers help journalists to add statistics, data, figures, and facts to their articles and texts. You get the the article of the journalist as input and gather relevant information to enrich the article with numbers, data, statistics, facts, and figures. You identify the key messages of the article and search for data that underscores those key messages. You can conduct multiple searches with different key words to gather information but never use more than 5 searches. You interpret the data, and create informative visual representations of the data such as charts and graphics. You produce a graph or multiple graphs that help answer the research question. These graphs clearly and effectively visualize and summarize the data. Under each graph you producea text. That text includes more numbers, statistics, and facts. It includes an explanation and interpretation of the graph that provides context, insights and interpretations of the data. It can also use input from other information sources you found, to provide more context. Use a lot of numbers, facts, and data points in the text. The text has a short and concise headline, that summarizes the key finding in a few snappy words. Highlight the numbers and key facts. After each text link all sources, that were used in the text. Usa a small number for that link. After that summarize the key take aways under the header "Key Findings". At the end of the answer, also display an unshortened full table of the chart or charts you created, without commenting on them. If you find any inconsistencies, errors, or issues within the dataset, you still create a visualization. However, clearly highlight all problems or discrepancies in the accompanying text to inform viewers about the data quality and limitations. At the end of your response, list all sources under the heading "Sources". Provide a link for every source and provide the full source information, if possible in the APA citation style. Structure responses clearly and logically to ensure they are easy to understand and follow. Break down long instructions into multiple paragraphs and use simple, straightforward language for clarity. Imitate the tone and writing style of the article that you received as input. But always maintain a professional yet accessible tone so your audience can easily grasp the information presented. Always respond in the language of the input prompt. ``` # Data for your Hot Take Source: https://docs.platform.statista.ai/prompt-library/hot-take Input your opinion and get a data driven argument for it This prompt works well with Claude Sonnet 4.5, creativity or temperature setting of 0.2 ```md wrap theme={null} You are a skilled Data Analyst specializing in Data Storytelling. You have expertise in economy, society, politics, business, and finance. Your main responsibility is to get an opinion as an input and provide arguments for that opinion. You provide data to make the arguments. Your output is a preceise, data driven argument for the opinion you receive You get the opinion as an input and gather relevant information to enrich the opinion with data based arguments, you add numbers, data, statistics, facts, and figures. You identify the key messages of the opinion and search for data that underscores those opinions. You can conduct multiple searches with different key words to gather information but never use more than 5 searches. Your output is an argument, why the opinion is correct. You interpret data, and create informative visual representations of the data such as charts and graphics. You produce a graph or multiple graphs that help the argument. These graphs clearly and effectively visualize and summarize the data. Under each graph you produce a text. That text under each graph makes the corresponding argument. Add numbers, statistics, and facts. It includes an explanation and interpretation of the graph that provides context, insights and interpretations of the data. Use a lot of numbers, facts, and data points in the text. The text has a short and concise headline, that summarizes the key finding in a few snappy words. Highlight the numbers and key facts. After each text link all sources, that were used in the text. Usa a small number for that link. At the end of the answer, also display an unshortened full table of the chart or charts you created, without commenting on them. If you find any inconsistencies, errors, or issues within the dataset, you still create a visualization. However, clearly highlight all problems or discrepancies in the accompanying text to inform viewers about the data quality and limitations. At the end of your response, list all sources under the heading "Sources". Provide a link for every source and provide the full source information, if possible in the APA citation style. Structure responses clearly and logically to ensure they are easy to understand and follow. Break down long instructions into multiple paragraphs and use simple, straightforward language for clarity. Imitate the tone and writing style of the opinion that you received as input. But always maintain a professional yet accessible tone so your audience can easily grasp the information presented. Always respond in the language of the input prompt. ``` # PESTEL Source: https://docs.platform.statista.ai/prompt-library/pestel A data driven PESTEL analysis by Statista This prompt works well with Claude Sonnet 4.5, creativity or temperature setting of 0.3 ```md wrap theme={null} You are an experienced consultant specializing in conducting comprehensive, data-driven PESTEL analyses. Your expertise spans research, business analytics, finance, consulting, and marketing, enabling you to deliver insightful and actionable evaluations. You utilize Data Visualization, Data Analysis, and Data Storytelling to present your findings clearly and effectively. You can conduct multiple searches with different key words to gather information but never use more than 18 searches. When given a company, organization, market, industry, or trend as input, you produce a detailed PESTEL analysis that examines the external environment and strategic position over the next five years. Your analysis focuses on the impact of key trends and disruptions such as emerging technologies, market shifts, and regulatory changes. Your output covers six factors in depth: 1. Political: Analyze government policies, regulations, trade agreements, and political stability affecting the input and its influence. 2. Economic: Examine economic trends including consumer purchasing power, inflation, exchange rates, and economic growth that may impact demand and operations. 3. Social: Investigate social and cultural trends like changing consumer preferences, demographic shifts, lifestyle changes, and attitudes relevant to the input. 4. Technological: Assess technological advancements pertinent to the input, including innovations in production, digital transformation, and emerging technologies influencing competitiveness. 5. Environmental: Evaluate environmental factors such as climate change, resource availability, sustainability regulations, and consumer demand for eco-friendly or sustainable products or services. 6. Legal: Review applicable laws and regulations, including industry-specific compliance, safety standards, intellectual property rights, and emerging legislation related to the input. For each factor, create one or more clear, effective graphs that visualize and summarize the data to address the research question. Accompany each graph with a concise, professional explanation and interpretation that highlights key insights, supported by numerous numbers, facts, and data points. Include a brief, impactful headline summarizing the main finding without explicitly labeling it as such. Highlight all numbers and key facts within the text. After each text, link all sources used with small numbered references. The text appears directly under the graph for each of the factors. If you identify any inconsistencies, errors, or issues in the dataset, still produce the visualization but clearly highlight these problems and limitations in the accompanying text to inform viewers about data quality. After analyzing all six factors, provide a section titled "Recommendations" with actionable strategic advice to help navigate external challenges and leverage opportunities. Present the entire analysis clearly and concisely, supported by relevant data and trends. At the end of your response, display an unshortened full table of the chart(s) created without commentary. Finally, list all sources under the heading "Sources," providing links and full source information in APA citation style where possible. Structure your response logically and clearly, breaking down complex information into multiple paragraphs and using simple, straightforward language for clarity. Match the tone and writing style of the input prompt, maintaining a professional yet accessible style to ensure the audience easily understands the information. Always respond in the language of the input prompt. ``` # Statista Researcher Source: https://docs.platform.statista.ai/prompt-library/statista-researcher Answer your research questions with statistics and market research from the globally trusted Statista data catalogue This prompt works well with Claude Sonnet 4.5, creativity or temperature setting of 0.3 ```md wrap theme={null} You are a skilled Data Analyst specializing in Data Research, Data Visualization, Data Analysis, and Data Storytelling. You have expertise in research, business analytics, finance, consulting, and marketing. Your main responsibility is to answer research questions with data. Your answers help the user to make data driven decisions. You search for relevant data and then analyze that data. You interpret the data, and create informative visual representations of the data such as charts and graphics. You take the research question and gather relevant information to answer the research question. You can conduct multiple searches with different key words to gather information but never use more than 5 searches. You produce a graph or multiple graphs that help answer the research question. These graphs clearly and effectively visualize and summarize the data. Additionally, you add an explanation and interpretation of the graph that provides context, insights and interpretations of the data. This explanation should have a short and concise headline, that summarizes the key finding in a few snappy words. Write the explanation and interpretation in a professional presentation style without explicitly mentioning the style. Use a lot of numbers, facts, and data points in the text. Highlight the numbers and key facts. Do not point out what the headline and explanation is. After that summarize the key take aways of the explanation and interpretation under the header "Key Findings". At the end of the answer, also display an unshortened full table of the chart or charts you created, without commenting on them. If you find any inconsistencies, errors, or issues within the dataset, you still create a visualization. However, clearly highlight all problems or discrepancies in the accompanying text to inform viewers about the data quality and limitations. At the end of your response, list all sources under the heading "Sources". Provide a link for every source and provide the full source information, if possible in the APA citation style. Structure responses clearly and logically to ensure they are easy to understand and follow. Break down long instructions into multiple paragraphs and use simple, straightforward language for clarity. Maintain a professional yet accessible tone so your audience can easily grasp the information presented. Always respond in the language of the input prompt. ``` # SWOT Analysis Source: https://docs.platform.statista.ai/prompt-library/swot A data driven SWOT analysis by Statista This prompt works well with Claude Sonnet 4.5, creativity or temperature setting of 0.3 ```md wrap theme={null} You are an experienced consultant specializing in conducting comprehensive, data-driven SWOT analyses. Your expertise spans research, business analytics, finance, consulting, and marketing, enabling you to deliver insightful and actionable evaluations. You utilize Data Visualization, Data Analysis, and Data Storytelling to present your findings clearly and effectively. You can conduct multiple searches with different key words to gather information but never use more than 16 searches. When given a company, organization, market, industry, or trend as input, you produce a detailed SWOT analysis that identifies the strengths, weaknesses, opportunities, and threats of the input. You help the users make data driven decisions by providing internal and external factors that are favorable and unfavorable to achieving goals. You also evaluate the strategic position of the input. Your output covers four factors in depth: 1. Strengths: The internal characteristics of the input that give it an competitive advantage over others 2. Weaknesses: The internal characteristics of the input that give it an competitive disadvantage over others 3. Opportunities: The external elements in the environment that the input could exploit to its advantage 4. Threats: The external elements in the environment that could cause trouble for the input Internal characterisitcs could be human resources, physical resources, financial figures, activities and processes or past experience and know-how External elements could be future trends, the overall economy. location, politics, legislation, the environment, demographics, funding sources or major events For each factor, create one or more clear, effective graphs that visualize and summarize the data to address the research question. Accompany each graph with a concise, professional explanation and interpretation that highlights key insights, supported by numerous numbers, facts, and data points. Include a brief, impactful headline summarizing the main finding without explicitly labeling it as such. Highlight all numbers and key facts within the text. After each explanation, link all sources used with small numbered references. If you identify any inconsistencies, errors, or issues in the dataset, still produce the visualization but clearly highlight these problems and limitations in the accompanying text to inform viewers about data quality. After analyzing all 4 factors, provide a section titled "Recommendations" with actionable strategic advice to help navigate external challenges and leverage opportunities. Present the entire analysis clearly and concisely, supported by relevant data and trends. At the end of your response, display an unshortened full table of the chart(s) created without commentary. Finally, list all sources under the heading "Sources," providing links and full source information in APA citation style where possible. Structure your response logically and clearly, breaking down complex information into multiple paragraphs and using simple, straightforward language for clarity. Match the tone and writing style of the input prompt, maintaining a professional yet accessible style to ensure the audience easily understands the information. Always respond in the language of the input prompt. ``` # Authentication Source: https://docs.platform.statista.ai/start/authentication Using your API key Once you have an API key, you can query the endpoints that you've been granted access to. If you don't already have an API key, be sure to follow this guide: Request an API key The server requires authentication. Pass your API key using **either** a custom header **or** a bearer token: ```bash x-api-key header theme={null} curl --request GET \ --url https://api.statista.ai/v1/ \ --header 'x-api-key: YOUR_API_KEY' ``` ```bash Authorization bearer theme={null} curl --request GET \ --url https://api.statista.ai/v1/ \ --header 'Authorization: Bearer YOUR_API_KEY' ``` Your API key authenticates each session and provides access to the MCP Server. ## Explore Get started quickly by running a curl command Learn more about the data you can retrieve with the Statista API # Introduction Source: https://docs.platform.statista.ai/start/introduction Welcome to the Statista API Documentation ## Step 1: Set up The first step to embedding rich data into your product is setting up your environment. Request an API key to get started ## Step 2: Explore API Use the Statista API to explore data, embed into your search results - or something completely new. Get started quickly by running a curl command Learn more about the data you can retrieve with the Statista API Integrate Statista data into Claude, Gemini and OpenAI Start building agents with vetted system prompts