# HrFlow.ai MCP for AI Agents AI Agent Connect > HrFlow.ai is a talent acquisition API for parsing resumes, matching candidates to jobs, and reasoning about profiles. It helps your AI client automate the heavy lifting of recruitment by scoring candidates against job descriptions and performing semantic searches across large talent pools. ## Overview - **Category:** ai-frontier - **Price:** Free - **Endpoint:** https://edge.vinkius.com/vk_preview_I5AWktYKd6ZBeasEU5l62xtiXMSMlPPEd1gKq98S/ai-agent-connect - **Tags:** resume-parsing, talent-acquisition, semantic-search, candidate-scoring, hiring-automation ## Description This Connector connects your AI client to the HrFlow.ai platform to handle the heavy lifting of talent acquisition. Instead of manually sifting through hundreds of resumes, you can have your agent parse files into structured data and then search through them using natural language. You can ask specific questions about a candidate's career path or have the agent score a list of profiles against a new job description to see who actually fits the bill. It handles the reasoning about candidate fit so you can focus on making the final hiring decisions. Because Vinkius hosts this Connector, you can plug it into your existing workflow and start running these recruitment operations immediately without building your own infrastructure. ## Tools ### search_jobs Find specific jobs using semantic filters instead of just basic keyword matching. This finds the right roles even with slightly different naming. ### unfold_profile Analyze a candidate's career path to see how they moved between different roles and industries. This provides a deeper look at their progression. ### parse_profile Turn a raw resume file into a structured profile that your agent can actually read. This eliminates manual data entry for every new applicant. ### score_profiles Compare a group of candidates against a job description to get a numerical fit score. It helps you prioritize who to contact first. ### search_profiles Look for candidates across your entire database using natural language search queries. It understands the context of your search terms. ### ask_profile Ask a natural language question about a specific profile to see if they have the right experience. This helps you skip the initial screening call for basic requirements. ### list_boards Get a list of all job boards currently available in your HrFlow account. Use this to keep track of your active hiring locations. ### list_jobs See all the jobs you have stored across your various HrFlow boards. This gives you a bird's eye view of your open roles. ### list_profiles Pull a list of all candidate profiles currently saved in your HrFlow system. It's the fastest way to see your total talent pool. ### list_sources View the different sources where your candidate profiles are being pulled from. Use this to audit your talent pipeline. ## Prompt Examples **Prompt:** ``` Can you look at the resume I just uploaded and tell me if this person has experience with project management? ``` **Response:** ``` I've analyzed the resume for you. Here is a summary of their project management experience: * **Lead Project Manager** (TechCorp) | 2020–2023 * Managed a team of 12 engineers. * Oversaw a $2M budget for cloud migration. * **Project Coordinator** (StartupX) | 2018–2020 * Handled timeline scheduling and stakeholder updates. **Verdict:** Yes, they have 5 years of direct experience in both leadership and coordination roles. ``` **Prompt:** ``` I need to find any candidates in our database who have worked in the fintech space in the last three years. ``` **Response:** ``` I've searched our profiles for 'fintech' experience within the last three years. Here are the top matches: | Name | Company | Years in Fintech | | :--- | :--- | :--- | | Sarah Chen | PayPal | 3 | | Marcus Thorne | Revolut | 2 | | Elena Rodriguez | Stripe | 4 | Would you like me to pull the full profiles for these three? ``` **Prompt:** ``` Compare these five candidates against the job description for the Senior Product Manager role and tell me who the best fit is. ``` **Response:** ``` I've scored the 5 candidates against your Senior PM description. Here is the ranking: 1. **David Kim (Score: 94/100)** - Strongest match. Has led 3+ product launches in SaaS. 2. **Aisha Khan (Score: 88/100)** - Very strong. Excellent background in growth. 3. **Jordan Smith (Score: 75/100)** - Good experience, but lacks the required scale. 4. **Lee Wong (Score: 62/100)** - Missing key leadership experience. 5. **Maria Garcia (Score: 55/100)** - More focused on design than product. **Recommendation:** I suggest reaching out to David Kim first. ``` ## Capabilities ### Parse resumes into structured data Turn raw resume files into organized profiles that your AI client can read and analyze. ### Score candidates against jobs Automatically rank a list of candidates based on how well they match a specific job description. ### Perform semantic profile searches Find the right people in your database using natural language instead of just basic keywords. ### Ask questions about profiles Query specific details about a candidate's history or skills using plain English. ### Analyze career paths Have your agent unfold and explain a candidate's professional progression over time. ### Manage job boards and sources List and organize your various job boards and candidate sources in one place. ## Use Cases ### Ranking a high volume of applicants A recruiter has 200 resumes for a dev role. They ask their agent to use parse_profile on all files and then use score_profiles to find the top 10 matches for the engineering role. ### Quickly checking specific experience A hiring manager wants to know about a candidate's leadership. They ask the agent to use ask_profile on a specific candidate key to see if they managed teams in their last two roles. ### Finding niche skills across sources A company needs to find a niche skill across many sources. The user asks the agent to use search_profiles to find anyone with distributed systems experience across all profile sources. ### Auditing talent pipeline sources An HR admin wants to see where their data is coming from. They ask the agent to use list_sources to identify which job boards are providing the most candidate profiles. ## Benefits - Stop manually reading every resume by using parse_profile to turn files into structured data instantly. - Rank applicants faster by using score_profiles to see which candidates actually match your job requirements. - Find the right people with search_profiles which uses semantic filters to understand the intent behind your search. - Get deeper insights into a candidate's history by using unfold_profile to map out their entire career progression. - Save time on repetitive screening by using ask_profile to query specific skills or experience from a profile. - Keep your job listings organized by using list_boards and list_jobs to manage your hiring pipeline in one place. ## How It Works The bottom line is that your AI agent handles the data extraction and matching so you can just pick the best people. 1. Connect your AI client to the HrFlow.ai MCP via Vinkius. 2. Provide the agent with a resume file or a specific job description. 3. Get back structured candidate data, fit scores, or a list of matching jobs. ## Frequently Asked Questions **How does HrFlow.ai help my recruitment team save time?** It automates the manual data entry of reading resumes. Instead of a human typing out details from a PDF, your AI agent parses the file into a structured format instantly, allowing your team to focus on interviewing. **Can I use HrFlow.ai to rank my applicants?** Yes, you can have your AI agent score every candidate against a specific job description. It gives you a clear ranking based on how well their experience actually matches your requirements. **Does HrFlow.ai support natural language searching for candidates?** Yes, it uses semantic search. This means you can ask your agent to find people with specific skills or backgrounds using normal sentences, and it will find the best matches even if they don't use exact keywords. **How does HrFlow.ai handle resume parsing?** It takes raw resume files and turns them into structured profiles. This makes the information searchable and allows your AI agent to reason about a candidate's skills and history much more accurately. **Can I ask specific questions about a candidate's history using HrFlow.ai?** Absolutely. You can ask your AI agent to check for specific things, like whether a candidate managed a team or worked in a specific industry, and it will find that information within their profile for you. **Is HrFlow.ai good for high-volume hiring?** It's ideal for high-volume hiring because it handles the heavy lifting of initial screening. It can process hundreds of resumes and rank them in seconds, so your team only sees the most qualified people. **How do I get HrFlow API credentials?** You can find your X-API-KEY in the HrFlow dashboard under Settings > API. You also need the email address of your account. **Can I parse PDF resumes with this Connector?** Yes, the parse_profile tool allows you to provide a public URL to a resume file for AI parsing. **What is profile asking?** It's an AI feature that lets you ask questions about a candidate's profile in plain English and get intelligent answers based on their data. **Can I parse PDF resumes with this MCP?** Yes, the parse_profile tool allows you to provide a public URL to a resume file for AI parsing.