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Careerproof

Career and workforce intelligence built on a deep HR ontology โ€” skill taxonomies, role definitions and responsibilities, compensation and incentive structures, learning and development pathways, sourcing strategies, and role/skill evolution mapping. This structured foundation, combined with a RAG knowledge base curated from 50+ premium sources (HBR, McKinsey, BCG, Gartner, Forrester) and updated 3x daily with live web research, powers 6 guided skills and 42 MCP tools for two audiences: working professionals getting personalized career intelligence (CV optimization, salary benchmarking, career strategy), and HR/TA teams running structured talent evaluation, candidate shortlisting, compensation analysis, and consulting-grade workforce research reports. Example Use Cases (for HR/TA teams): 1. Custom Evaluation Models โ€” Train CareerProof on your organization's existing assessment rubrics, scorecards, and evaluation criteria to build custom eval models that evaluate candidates through your specific lens. Upload your competency frameworks and historical assessments, then run inference on new candidates โ€” scored and ranked exactly how your team would, at scale. 2. Candidate Evaluation & Shortlisting โ€” Set up a hiring context with company profile and job description, upload candidate CVs, then batch-rank them with GEM competency scoring and JD-FIT matching. Apply your custom eval models for organization-specific scoring, or deep-dive any candidate with a 360-degree evaluation including tailored interview questions derived from skill taxonomy analysis. 3. Workforce Research Reports โ€” Generate consulting-grade PDF reports across 16 types (salary benchmarking, skills gap analysis, org design, DEI assessment, succession planning, sourcing strategy, and more). Each report is grounded in real-time market data from premium sources and structured around HR ontology โ€” role definitions, compensation structures, L&D pathways, and skill evolution mapping. 4. Compensation & Incentive Benchmarking โ€” Get market-calibrated salary and total compensation intelligence for any role, location, and industry. Analysis is structured around compensation and incentive frameworks from the HR ontology, enriched with live web research and curated knowledge base data covering base salary, equity, bonuses, and benefits. Example Use Cases (for the working professional or career coach): 1. Career Intelligence Chat (Hyper-Personalized) โ€” Ask career strategy questions and get hyper-personalized responses that fuse your CV context with deep insights from the career and workforce RAG knowledge base. Salary benchmarks calibrated to your function and location, industry disruption analysis mapped to your skill profile, and career pivot recommendations grounded in role evolution data โ€” not surface-level answers, but intelligence drawn from the same sources that inform executive strategy. 2. CV Optimization (Hyper-Personalized) โ€” Upload your CV and receive a hyper-personalized positioning pipeline that combines your actual experience with deep insights from our career and workforce RAG knowledge base. Market analysis calibrated to your industry and seniority, career opportunity identification grounded in role/skill evolution data, and targeted edits with trade-off analysis โ€” not generic advice, but intelligence shaped by 50+ premium research sources and your unique career trajectory.

MCP-MESSENGER

**SlashMCP** is a production-grade AI workspace that connects LLMs to real-world data and tools through an intuitive chat interface. Built on the Model Context Protocol (MCP), it enables seamless interaction with multiple AI providers (OpenAI, Claude, Gemini) while providing powerful capabilities for document analysis, financial data queries, web scraping, and multi-agent workflow orchestration. ### Key Features: - **Multi-LLM Support**: Switch between GPT-4, Claude, and Gemini at runtimeโ€”no restart needed - **Smart Command Autocomplete**: Type `/` to discover and execute MCP server commands instantly - **Document Intelligence**: Drag-and-drop documents with automatic OCR extraction and vision analysis - **Financial Data Integration**: Real-time stock quotes, charts, and prediction market data via Alpha Vantage and Polymarket - **Browser Automation**: Web scraping and navigation using Playwright MCP - **Multi-Agent Orchestration**: Intelligent routing with specialized agents for command discovery, tool execution, and response synthesis - **Dynamic MCP Registry**: Add and use any MCP server on the fly without code changes - **Voice Interaction**: Browser-based transcription and text-to-speech support ### Use Cases: - Research and analysis workflows - Document processing and extraction - Financial market monitoring - Web data collection and comparison - Multi-step task automation **Live Demo:** [ slashmcp.vercel.app ]( https://slashmcp.vercel.app ) **GitHub:** [ github.com/mcpmessenger/slashmcp ]( https://github.com/mcpmessenger/slashmcp ) **Website:** [ slashmcp.com](https://slashmcp.com )

Scholar_mcp_server

ๅญฆๆœฏ่ฎบๆ–‡ๆฃ€็ดข่šๅˆ MCP ๆœๅŠก ๅŸบไบŽ Go ่ฏญ่จ€ๅฎž็Žฐ็š„ๅญฆๆœฏ่ฎบๆ–‡ๆฃ€็ดข่šๅˆ MCP (Model Context Protocol) ๆœๅŠก๏ผŒ้€š่ฟ‡็ปŸไธ€ๆŽฅๅฃๅŒๆ—ถ่ฐƒ็”จๅคšไธชๅญฆๆœฏๆ•ฐๆฎๅบ“๏ผŒๆไพ›ๆ™บ่ƒฝๅŽป้‡ใ€ๅˆๅนถๅ’ŒๆŽ’ๅบ็š„ๆœ็ดข็ป“ๆžœใ€‚ ๅŠŸ่ƒฝ็‰นๆ€ง ๐Ÿ” ๅคšๆบ่šๅˆๆœ็ดข: ๅŒๆ—ถ่ฐƒ็”จ6ไธชไธป่ฆๅญฆๆœฏๆ•ฐๆฎๅบ“ ๐Ÿง  ๆ™บ่ƒฝๅŽป้‡ๅˆๅนถ: ๅŸบไบŽDOIๅ’Œๆ ‡้ข˜็š„ๆ™บ่ƒฝ้‡ๅคๆฃ€ๆต‹ ๐Ÿ“Š ็ปŸไธ€ๆ•ฐๆฎๆ ผๅผ: ๆ ‡ๅ‡†ๅŒ–็š„่ฎบๆ–‡ๅ…ƒๆ•ฐๆฎ็ป“ๆž„ ๐Ÿš€ ๅนถๅ‘้ซ˜ๆ€ง่ƒฝ: ๅผ‚ๆญฅๅนถ่กŒ่ฐƒ็”จๆ‰€ๆœ‰ๆ•ฐๆฎๆบ ๐ŸŽฏ ็ฒพ็กฎ็ป“ๆžœ: ๆ™บ่ƒฝๆŽ’ๅบๅ’Œ็›ธๅ…ณๆ€ง่ฏ„ๅˆ† ๐ŸŒ MCP ๅ่ฎฎๆ”ฏๆŒ: ๅฎŒๆ•ด็š„MCPๅทฅๅ…ทๆŽฅๅฃ ๐Ÿ“ ่ฏฆ็ป†็Šถๆ€ๆŠฅๅ‘Š: ๅฎžๆ—ถๆ•ฐๆฎๆบ็Šถๆ€ๅ’Œๆ€ง่ƒฝ็›‘ๆŽง ๆ”ฏๆŒ็š„ๆ•ฐๆฎๆบ arXiv: ็‰ฉ็†ๅญฆใ€ๆ•ฐๅญฆใ€่ฎก็ฎ—ๆœบ็ง‘ๅญฆ้ข„ๅฐๆœฌ (ๅ…่ดน) Semantic Scholar: AI้ฉฑๅŠจ็š„ๅญฆๆœฏๆœ็ดขๅผ•ๆ“Ž (ๅ…่ดน) Crossref: ๅ…จ็ƒๆœ€ๅคง็š„DOIๆณจๅ†Œๆœบๆž„ (ๅ…่ดน) Scopus: Elsevierๅญฆๆœฏๆ•ฐๆฎๅบ“ (้œ€่ฆAPIๅฏ†้’ฅ) ADSABS: NASAๅคฉไฝ“็‰ฉ็†ๅญฆๆ•ฐๆฎ็ณป็ปŸ (้œ€่ฆAPIๅฏ†้’ฅ) Sci-Hub: ๅญฆๆœฏ่ฎบๆ–‡PDF่Žทๅ– (ๅ…่ดน๏ผŒไฝ†้œ€ๆณจๆ„ๆณ•ๅพ‹้ฃŽ้™ฉ)