> ## Documentation Index > Fetch the complete documentation index at: https://docs.bigdata.com/llms.txt > Use this file to discover all available pages before exploring further. # From Screen to Signal: Building a Global Robotics Watchlist with the Bigdata MCP > Screen 13 markets for robotics leaders, save them as a watchlist, compare them in one portfolio grid and search every company at once, using four Bigdata MCP tools. October 21, 2026 MCP, Watchlists, Thematic Research / 6 minutes read Robotics is no longer one industry. It runs from warehouse shuttles and factory arms to surgical robots, self-driving trucks and humanoids, and the companies behind it are listed in New York, Tokyo, Seoul, Shenzhen and across Europe. Building a coverage list for that theme usually means a screener, a spreadsheet and a lot of copy and paste. This post walks through the same job with four tools from the [Bigdata MCP](/mcp-reference/introduction). We go from a cross-market screen to a saved watchlist, a portfolio grid with charts, and one search that covers all 49 companies at once. Then we go deeper on a single name.
Step Tool What it does
1 [`bigdata_screen_companies`](/mcp-reference/tools/bigdata-screen-companies) Finds listed companies by country, industry and market cap
2 [`bigdata_create_watchlist`](/mcp-reference/tools/bigdata-create-watchlist) Saves the selected companies as a reusable watchlist
3 [`bigdata_portfolio_tearsheet`](/mcp-reference/tools/bigdata-portfolio-tearsheet) Returns price, EPS, analyst targets and market cap for every company in one grid
4 `bigdata_watchlist_search` Runs one query across the whole watchlist, with results grouped by company
+ [`bigdata_search`](/mcp-reference/tools/bigdata-search) Goes deeper on a single company
## Step 1: Screen 13 markets for robotics companies The theme covers five areas: **warehouse**, **factory**, **medical**, **self-driving** and **humanoid** robots, plus the chip and software **platforms** they run on. Aerospace and defense are out of scope. There is no "Robotics" industry in the screener, so we map the theme to eight industries: | Industry | Robotics area | | :- | :- | | Industrial - Machinery | Warehouse, factory | | Electrical Equipment & Parts | Warehouse, factory | | Medical - Instruments & Supplies | Medical | | Medical - Devices | Medical | | Auto - Parts | Self-driving | | Auto - Manufacturers | Self-driving, humanoid | | Consumer Electronics | Humanoid | | Semiconductors | Platforms | We screen 13 countries: the US, Germany, France, the Netherlands, Spain, the UK, Switzerland, Sweden, Israel, Japan, South Korea, China and Hong Kong. Market cap is filtered in each listing's own currency, so the threshold of about \$5 billion is set per currency: USD 5bn, EUR 4.3bn, GBP 3.7bn, CHF 4bn, SEK 47bn, JPY 750bn, KRW 7tn, CNY 36bn, HKD 39bn and ILS 18bn. Copy this prompt into your agent: ```text theme={null} Using Bigdata, screen listed companies with a market cap above about $5 billion, converting the threshold to each listing's local currency, in the US, Germany, France, the Netherlands, Spain, the UK, Switzerland, Sweden, Israel, Japan, South Korea, China and Hong Kong. Use these industries: Industrial - Machinery, Electrical Equipment & Parts, Medical - Instruments & Supplies, Medical - Devices, Auto - Parts, Auto - Manufacturers, Consumer Electronics and Semiconductors. Include only actively trading companies, with no ETFs or funds. Then keep only the companies with clear robotics exposure in warehouse, factory, medical, self-driving or humanoid robots, or the chip and software platforms behind them. Leave out aerospace and defense. Keep fewer than 60 companies and tag each company with its area. ``` The agent runs [`bigdata_screen_companies`](/mcp-reference/tools/bigdata-screen-companies) once per country and industry. Across all of them the screen returns 391 companies. Most of them build pumps, HVAC systems or memory chips, so we keep the 49 with clear robotics exposure: | Area | Companies | | :- | :- | | Warehouse | Symbotic, Daifuku, KION (Dematic) | | Factory | Teradyne (Universal Robots, MiR), Rockwell Automation, Siemens, Schneider Electric, ABB, Fanuc, Yaskawa, Omron, Nidec, SMC, Mitsubishi Electric, Denso, HD Hyundai, RoboTechnik, Inovance | | Medical | Intuitive Surgical, Stryker (Mako), Zimmer Biomet (ROSA), Globus Medical (ExcelsiusGPS), Smith & Nephew (CORI) | | Self-driving | Mobileye, Aptiv, Continental, Hyundai Mobis, AB Volvo, Daimler Truck, Mercedes-Benz, Desay SV, Toyota | | Humanoid | Tesla (Optimus), XPeng (Iron), Hyundai Motor (Boston Dynamics), Rainbow Robotics, Samsung Electronics, LG Electronics, Xiaomi, Unitree, Leader Harmonious Drive, Sanhua, Ningbo Tuopu | | Platforms | NVIDIA, Qualcomm, Arm, NXP, Renesas, Infineon | > [!TIP] > > The country filter matches where a company is based, not where it is listed. Each result also carries the company's Bigdata entity ID, which the agent uses in the next steps. ## Step 2: Save the companies as a watchlist In the same conversation, ask the agent to save the list: ```text theme={null} Create a Bigdata watchlist called "Global Robotics" with these companies. Description: "Large-cap robotics companies across warehouse, factory, medical, self-driving, humanoid and platform segments in the US, Europe, Israel, Japan, Korea and China." ``` The agent calls [`bigdata_create_watchlist`](/mcp-reference/tools/bigdata-create-watchlist) and confirms the new watchlist with its ID: ![Agent reply confirming that the Global Robotics watchlist was created with 49 companies](https://mintcdn.com/ravenpackinternational/x4qAIX1kx_M9_rRB/images/blog/global-robotics-watchlist/watchlist-created.png?fit=max\&auto=format\&n=x4qAIX1kx_M9_rRB\&q=85\&s=856ab4c61c6eeb44dfcde0d7d1352122) The watchlist also appears in the [Bigdata app under Watchlists](https://app.bigdata.com/watchlists), with live prices and daily, weekly and monthly moves for all 49 companies: ![The Global Robotics watchlist in the Bigdata app, showing Stryker, Globus Medical, Intuitive Surgical and other companies with their latest price and percentage changes](https://mintcdn.com/ravenpackinternational/x4qAIX1kx_M9_rRB/images/blog/global-robotics-watchlist/global-robotics-watchlist.png?fit=max\&auto=format\&n=x4qAIX1kx_M9_rRB\&q=85\&s=e11a81ea61e73f51f58476639c7597e2) ## Step 3: Compare the companies in one grid Ask for a portfolio view and the two charts: ```text theme={null} Show the portfolio tearsheet for my Global Robotics watchlist with price, EPS, EPS estimate, EPS surprise, price target and market cap. Then chart the consensus EPS estimate, with one chart per reporting currency, and chart how far the consensus price target is above the current price. ``` The agent calls [`bigdata_portfolio_tearsheet`](/mcp-reference/tools/bigdata-portfolio-tearsheet), which returns one row per company with the metrics you ask for. ### Consensus EPS for the last reported quarter EPS is reported in each company's own currency, so we compare companies within one currency at a time. **USD** ![Consensus EPS in USD for 16 robotics companies, from NXP at \$3.52 to Mobileye at \$0.06](https://mintcdn.com/ravenpackinternational/x4qAIX1kx_M9_rRB/images/blog/robotics-watchlist/consensus_eps_usd.svg?fit=max\&auto=format\&n=x4qAIX1kx_M9_rRB\&q=85\&s=bad6fa86ddf9be576e75a09238ab28b1) **JPY** ![Consensus EPS in JPY for 9 Japanese robotics companies, led by SMC at ¥666](https://mintcdn.com/ravenpackinternational/x4qAIX1kx_M9_rRB/images/blog/robotics-watchlist/consensus_eps_jpy.svg?fit=max\&auto=format\&n=x4qAIX1kx_M9_rRB\&q=85\&s=2b6cc970214be4d8fe6eac6e5ec06509) **KRW** ![Consensus EPS in KRW for 5 Korean companies, led by Hyundai Mobis](https://mintcdn.com/ravenpackinternational/x4qAIX1kx_M9_rRB/images/blog/robotics-watchlist/consensus_eps_krw.svg?fit=max\&auto=format\&n=x4qAIX1kx_M9_rRB\&q=85\&s=ace3c6f08347b281c8f03a004b56d86a) **CNY** ![Consensus EPS in CNY for 8 Chinese companies, with XPeng expected to report a loss](https://mintcdn.com/ravenpackinternational/x4qAIX1kx_M9_rRB/images/blog/robotics-watchlist/consensus_eps_cny.svg?fit=max\&auto=format\&n=x4qAIX1kx_M9_rRB\&q=85\&s=b9e2073311f419320261a0ef68316b55) **EUR** ![Consensus EPS in EUR for 6 European companies, led by Siemens at €2.55](https://mintcdn.com/ravenpackinternational/x4qAIX1kx_M9_rRB/images/blog/robotics-watchlist/consensus_eps_eur.svg?fit=max\&auto=format\&n=x4qAIX1kx_M9_rRB\&q=85\&s=624bda63777af1733783f016c35d28f9) **SEK** ![Consensus EPS in SEK for AB Volvo at 5.22 kronor](https://mintcdn.com/ravenpackinternational/x4qAIX1kx_M9_rRB/images/blog/robotics-watchlist/consensus_eps_sek.svg?fit=max\&auto=format\&n=x4qAIX1kx_M9_rRB\&q=85\&s=17b5e0a3eb70ed0db415ae4356291845) ### Consensus price target compared with today's price For the companies with analyst price targets, the gap between the consensus target and the current price shows where analysts see the most room to rise. Arm, NVIDIA and Mobileye lead the list. ![Upside from current price to consensus price target, from Arm at +65% to Zimmer Biomet at +9%](https://mintcdn.com/ravenpackinternational/x4qAIX1kx_M9_rRB/images/blog/robotics-watchlist/price_target_upside.svg?fit=max\&auto=format\&n=x4qAIX1kx_M9_rRB\&q=85\&s=580644f6f507243f0c5756300da57837) ## Step 4: Search every company at once `bigdata_watchlist_search` runs one query across the whole list and returns results grouped by company. Every company gets its own share of the results, so the most covered names cannot crowd out the rest. Ask one question per prompt. The first covers patents: ```text theme={null} Search my Global Robotics watchlist for patents each company has filed or been granted for robotics technology. Return 3 results per company, using only content originally published in English. ``` The second covers products: ```text theme={null} Search my Global Robotics watchlist for products each company sells that solve a specific customer problem. Return 3 results per company, using only content originally published in English. ``` Both searches return results for 45 of the 49 companies. A few highlights: **Patents** | Company | What the search found | | :- | :- | | Tesla | Filing for a printed tactile "skin" for robot fingertips, palms and grippers ([Robotics and Automation News](https://app.bigdata.com/documents/EDAE0A1D7FE14EDE90BA3FDDC01CAD0C?cnum=2)) | | Samsung Electronics | US patents for a humanoid hip joint (2024) and a vision-guided robot hand (2026) ([Tech Times](https://app.bigdata.com/documents/14DE26FBD07E79B1307B00F207702D29?cnum=7)) | | Intuitive Surgical | Key da Vinci patents expired in 2017; the annual report describes how it protects its patent portfolio ([Quartr](https://app.bigdata.com/documents/BED070314C97EA8155BBEE1703D547C4?cnum=128)) | | Hyundai Mobis | 1,015 future-mobility patent applications in 2022, including robotics ([Sustainability report](https://app.bigdata.com/documents/B47266222BC4A27D61CCB41D70B79D10?cnum=174)) | **Products** | Company | Product and the problem it solves | | :- | :- | | FANUC | Food-grade robots for packaging lines and mobile robots for warehouse fulfillment ([Benzinga](https://app.bigdata.com/documents/029F3B7D173CF7059BBE1573C7B890AC?cnum=4)) | | KION | Autonomous truck with AI human detection for loading trailers in busy warehouses ([PubT](https://app.bigdata.com/documents/228F41CC8D34F2C7B50F58ABBD92BA11?cnum=1)) | | Symbotic | Handling for frozen and perishable goods, built at Walmart's request ([Quartr](https://app.bigdata.com/documents/915E1757F4743067E3E19AA6EDA3D67E?cnum=50\&cnum=52)) | | Omron | Sensors, controllers and robots that resolve issues on factory floors ([PubT](https://app.bigdata.com/documents/3050C94584FD4AD55302DC346A66BB3A?cnum=98)) | | Intuitive Surgical | Repeatable, easy-to-learn surgical systems for high-volume ambulatory surgery centers ([Quartr](https://app.bigdata.com/documents/375D84CE4479C4DE6062A697ACB2425B?cnum=44)) | ## Going deeper: Symbotic The watchlist search gives a line per company. When one name stands out, [`bigdata_search`](/mcp-reference/tools/bigdata-search) goes deeper into its filings, transcripts and news. Again, one question per prompt: ```text theme={null} Using Bigdata search, find Symbotic's robotics products and the customer problem they solve. ``` ```text theme={null} Using Bigdata search, find the patents Symbotic has filed or been granted for robotics technology. ``` The two searches give a clear picture: * **The problem.** Manual warehouse work is becoming unsustainable as labor shifts, wages rise and e-commerce adds complexity, and older automation cannot keep up ([10-Q](https://app.bigdata.com/documents/5D01BE6DCA0352725C56F964633027B1?cnum=112)). * **The product.** An AI-powered robotic system that moves, stores and sorts cases and individual items in high-density warehouses for Walmart, C\&S Wholesale Grocers and Exol, its warehouse-as-a-service joint venture ([Q3 FY2026 report](https://app.bigdata.com/documents/216D66BA1BCFD153FCCE6889A0551918?cnum=138)). * **What's new.** The acquisition of cellumation adds the celluveyor, a surface of independently controlled cells that sorts products without conveyor belts, for more throughput in less space ([press release](https://app.bigdata.com/documents/C738BEFBEFA77CCAA73DB103B61390CB?cnum=4\&cnum=1)). * **The patents.** About 1,100 issued or pending patents, more than 650 of them issued, backed by more than \$1 billion of cumulative R\&D ([10-Q](https://app.bigdata.com/documents/5D01BE6DCA0352725C56F964633027B1?cnum=112), [8-K](https://app.bigdata.com/documents/54489C0B57A329C39E7B22E1E270C2BF?cnum=45)). * **The scale.** A backlog of about \$22.5 billion and Q3 FY2026 revenue up 21.7% year on year to \$720.8 million ([Nasdaq](https://app.bigdata.com/documents/B2788AF72D2D8D9D63CD87A096414FE8?cnum=7)). ## Try it yourself The whole workflow runs from any MCP client connected to Bigdata, such as Claude. Ask it to screen, save, compare and search in plain language, and it chains the tools for you. > **[Connect the Bigdata MCP](/mcp-reference/introduction)** > > Set up the Bigdata MCP in your AI client. > **[Screen companies](/mcp-reference/tools/bigdata-screen-companies)** > > See every filter the screener accepts. *** ![Oscar Sanchez Iglesias](https://mintcdn.com/ravenpackinternational/Sf9MtziD0iLKyb1C/images/blog/authors/oscar_sanchez_iglesias.png?fit=max\&auto=format\&n=Sf9MtziD0iLKyb1C\&q=85\&s=c9ee6739dce63b6d6b6f2e5aa36e8442) Oscar Sanchez IglesiasSenior Product Manager This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.