🧠 LangFlow MCP High ATS Resume Creator (ATS-Aware)

This repository contains a LangFlow-exported .json file representing a custom multi-agent flow, designed to act as an MCP server. This flow can be used with Claude Desktop or any MCP-compatible client.

Its core functionality is to generate a high ATS (Applicant Tracking System) score resume based on a LinkedIn job post URL and a user's existing resume. The system parses both sources, summarizes relevant content, and produces a tailored, ATS-friendly resume in multiple formats.

📜 Architectural Decision Records (ADRs)

ADR 001 – Why LangFlow?

LangFlow allows for modular low-code orchestration of agentic LLM pipelines, making it ideal for our goal of chaining multiple agents with custom components and data parsers.

ADR 002 – Why MCP Server?

By exposing this flow as an MCP server:

• It becomes interoperable with Claude Desktop and other MCP clients.
• Users can interact via chat interfaces and benefit from stateful agent behavior.
• Encourages reuse and composability across different workflows.

ADR 003 – Agent Design and Flow

🎯 Agent 1: Resume Summarizer

• Input: User's current resume (raw text or document)
• Output: Summary of professional experience, total years, key skills, responsibilities, and education.
• ✅ Focused extraction using resume-aware prompt logic.

🎯 Agent 2: Job Description Summarizer

• Input: LinkedIn job post URL via chat.
• Output: Structured summary of required qualifications.
• 🛠️ Powered by a custom LangFlow component that parses HTML directly from the URL input.

🔄 Data Parsing and Conversion

• Each agent's output passes through a Message-to-Data Converter, followed by a combined parser to normalize structure and prepare inputs for resume generation.

🎯 Agent 3: Resume Generator

• Input: Parsed summaries from Agent 1 & Agent 2.
• Output: ATS-optimized resume in LaTeX format matching job criteria with user's skills.
• 🧠 Tailored resume structure focused on score improvement.

🛠️ Custom LangFlow Component: Format Converter

• Converts LaTeX output to:
  • ✅ PDF
  • ✅ DOCX
  • ✅ TXT
• Makes the resume instantly downloadable and shareable.

🎯 Agent 4: ATS Score Evaluator

• Input: Generated resume and job summary.
• Output: Final ATS score (out of 100) indicating how well the resume matches the job.
• ✅ Helps users iterate on improvements.

🔀 ADR 004 – Data Pipeline

flowchart TD
    FileUpload[File Upload] --> Agent1[Agent 1: Resume Summary]
    ChatInput[Chat Input URL] --> MCPCustomcomponent[URL HTML Fetcher]
    MCPCustomcomponent --> Agent2[Agent 2: Job Summary]
    Agent1 --> MsgToData1[Message to Data 1]
    Agent2 --> MsgToData2[Message to Data 2]
    MsgToData1 --> Merge1[Merge Resume + Job Summary]
    MsgToData2 --> Merge1
    Merge1 --> Parse1[Parser for Resume]
    Parse1 --> Agent3[Agent 3: Resume Generator in latex]
    Agent3 --> MsgToData3[Message to Data 3]
    MsgToData3 --> Parse2[Parser for LaTeX]
    Parse2 --> LatexToPDF[Convert LaTeX to PDF/DOCX/TXT]
    LatexToPDF --> ResumeOut[Output Resume]
    LatexToPDF --> MsgToData4[Message to Data 4]
    Agent2 --> MsgToData5[Message to Data 5]
    MsgToData4 --> Merge2[Merge Resume + Job Summary for Scoring]
    MsgToData5 --> Merge2
    Merge2 --> Parse3[Parser for Score Input]
    Parse3 --> Agent4[Agent 4: ATS Scoring]
    Agent4 --> ScoreOut[Output Score]

🔗 Compatibility

✅ Works with:

• Claude Desktop (as MCP Client)
• Any custom MCP-compatible chat client

📦 LangFlow Version: v1.4+

🧪 Example Use Case

Prompt:
"Please generate an tailored resume for [LinkedIn Job URL]"

Result:

• Tailored resume (PDF, DOCX, TXT)
• ATS match score out of 100
• Explanation of missing or weak areas

🚀 Get Started

1. Clone this repo
2. Import the .json into LangFlow
3. Connect with MCP client (e.g., Claude Desktop)
4. Start chatting!

🧩 Contributing

Have ideas for new agents or better format converters?
We welcome contributions via PR or feedback.

📄 License

MIT License
Copyright © 2025