# People Data Labs MCP > People Data Labs MCP provides access to millions of B2B records for lead generation, identity resolution, and market intelligence. Use your AI client to enrich company profiles with metadata or search massive datasets using natural language queries. ## Overview - **Category:** data-analytics - **Price:** Free - **Tags:** b2b-data, data-enrichment, identity-resolution, prospecting, market-intelligence, api-integration ## Description This MCP lets you tap into one of the biggest B2B datasets available today. Stop manually cross-referencing contacts in five different tabs. You can tell your agent to find a person's full professional profile just from an email address, getting details like their work history or education. Need company background? It pulls detailed metadata, including industry classification and stock tickers. If you have a list of 100 leads, the MCP handles bulk enrichment so you don't lose momentum. When building complex data pipelines using Vinkius, this MCP lets you query records directly with SQL or Elasticsearch DSL through plain conversation. You can also clean up messy data points—standardizing addresses or school names—before feeding them into your CRM. ## Tools ### pdl_autocomplete Gets suggestions for values you use in search API queries. ### pdl_bulk_enrich_company Enriches data for up to 100 companies at once. ### pdl_bulk_enrich_person Enriches data for up to 100 people at once. ### pdl_clean_company Cleans and standardizes messy raw company names or identifiers. ### pdl_clean_location Standardizes raw location data like addresses into a consistent format. ### pdl_clean_school Cleans and standardizes names of schools or universities. ### pdl_enrich_company Enriches a single company profile using available attributes. ### pdl_enrich_ip Provides detailed information by enriching an IP address. ### pdl_enrich_job_title Expands a job title to find similar roles and associated skills. ### pdl_enrich_person Enriches an individual's profile using multiple attributes like name or email. ### pdl_identify_person Compares a set of inputs to identify and score the best matching person profiles. ### pdl_search_company Searches the entire company dataset using either an Elasticsearch DSL query or SQL. ### pdl_search_job_posting Searches both active and historical job postings for keywords or criteria. ### pdl_search_person Searches the entire person dataset using either an Elasticsearch DSL query or SQL. ## Prompt Examples **Prompt:** ``` Enrich the person profile for the email 'sean@peopledatalabs.com'. ``` **Response:** ``` I've found the profile for Sean Thorne. He is the Co-Founder and CEO at People Data Labs, based in San Francisco. Would you like to see his full work history or education details? ``` **Prompt:** ``` Search for companies in the 'Financial Services' industry with more than 1000 employees using SQL. ``` **Response:** ``` I've executed the SQL search. I found several companies matching your criteria, including 'Stripe', 'Plaid', and 'Brex'. Which one would you like to explore in detail? ``` **Prompt:** ``` Identify potential profiles for 'John Doe' who works at 'Google'. ``` **Response:** ``` I've identified 3 possible profiles for 'John Doe' at Google. One is a Software Engineer in Mountain View, another is a Product Manager in New York. Should I enrich the Software Engineer profile for you? ``` ## Capabilities ### Enriching Profiles Retrieve comprehensive professional details for people and companies using limited identifiers like email, phone number, or job title. ### Advanced Data Searching Query the massive person or company datasets directly via SQL or an Elasticsearch DSL query through your AI client. ### Identifying People Cross-reference a set of attributes to find and score multiple potential profiles for one individual, ensuring you get the best match. ### Standardizing Data Fields Clean and normalize raw data points like company names, location addresses, or school affiliations so they fit standard formats. ### Processing Large Batches Process up to 100 records—either people or companies—in a single request for high-volume lead list building. ## Use Cases ### Validating Contact Info for Outbound Campaigns A marketing manager has 500 emails from a recent trade show. Instead of individually checking each one, they ask their agent to use `pdl_bulk_enrich_person`. The MCP processes the list and returns only verified profiles with company metadata. ### Finding a Candidate's Full History A recruiter hears about a great candidate but only has their name and current employer. They ask their agent to use `pdl_identify_person`. The MCP returns three possible profiles, allowing the recruiter to select the best match for deeper review. ### Market Research on Competitors A data analyst needs to compare industry trends. They ask their agent to run an SQL query using `pdl_search_company` targeting 'Financial Services' and filtering by employee size, pulling a list of direct competitors. ### Cleaning CRM Data Before Reporting A data engineer receives 10,000 records with inconsistent addresses. They use `pdl_clean_location` to standardize every address field across the entire dataset before running any reports on it. ## Benefits - Stop guessing who a lead is. Use `pdl_identify_person` to cross-reference an email address and find multiple potential profiles associated with that single person. - Build huge prospect lists without manual effort. The MCP lets you use `pdl_bulk_enrich_company` or `pdl_bulk_enrich_person` to process up to 100 records in one go. - When your data is messy, fix it first. Use the dedicated cleaning tools like `pdl_clean_location` or `pdl_clean_school` before running any reports on your end. - Need a specific company detail? You can run deep queries using either an SQL or Elasticsearch DSL through the MCP's search functionality, such as `pdl_search_company`. - Get more than just names. Run `pdl_enrich_job_title` to automatically surface relevant skills and related job roles for a candidate profile. ## How It Works The bottom line is that instead of writing complex API calls, you just talk to your agent about the data you need. 1. Subscribe to the People Data Labs MCP and enter your API key into Vinkius. 2. Your AI client accesses the connector, allowing you to issue natural language commands for data enrichment or queries. 3. The MCP runs the necessary lookups against the B2B dataset and returns structured, accurate profiles directly into your conversation. ## Frequently Asked Questions **How do I find multiple profiles for one person using People Data Labs MCP?** Use the `pdl_identify_person` tool. It compares a set of attributes—like name, company, and city—and returns several possible records along with a confidence score to help you pick the best match. **Can I enrich my CRM data in bulk using People Data Labs MCP?** Yes. Use `pdl_bulk_enrich_person` or `pdl_bulk_enrich_company`. These tools allow you to process up to 100 records in a single request, which is perfect for large-scale list building. **What kind of queries can I run with People Data Labs MCP?** You can use both SQL and Elasticsearch DSL. This gives you flexibility; if you're used to writing structured database code, either query type will work for searching the company or person datasets. **Does People Data Labs MCP help standardize my data?** Absolutely. If your records have messy fields, use cleaning tools like `pdl_clean_location` to normalize addresses or `pdl_clean_school` to standardize university names before you run any analysis. **Is People Data Labs MCP only for finding emails?** No. While it handles email enrichment, the tool set is much broader. You can also enrich based on job titles (`pdl_enrich_job_title`) or IP addresses (`pdl_enrich_ip`).