#chm

Mirror of

Goku is an HTTP load testing application written in Rust

A Model Context Protocol server for enriching data from multiple security products

Connect Claude to your Lunch Money personal finance data for conversational money management. Ask natural language questions about spending, manage budgets and categories, create transactions, and get financial insights through chat. Supports full CRUD operations including transaction queries, budget management, category organization, and asset tracking. Perfect for AI-powered personal finance analysis without leaving your conversation with Claude.

Model Context Protocol (MCP) server implementation for Aytch4K applications. The MCP server provides an interface for Large Language Models (LLMs) to interact with Aytch4K applications.

An MCP (Model Context Protocol) server that exposes Interzoid's AI-powered data quality, matching, enrichment, and standardization APIs to AI agents and LLM applications. This MCP server makes 29 Interzoid APIs discoverable and callable by any MCP-compatible client including Claude Desktop, Claude Code, Cursor, Windsurf, and other AI tools. AI agents can discover the available data quality tools and invoke them as needed during conversations and workflows. More info at interzoid.com

A Model Context Protocol (MCP) server for security data enrichment

The evaluation benchmark on MCP servers

chm to markdown

Career and workforce intelligence built on a deep HR ontology — 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 — 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 — scored and ranked exactly how your team would, at scale. 2. Candidate Evaluation & Shortlisting — 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 — 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 — role definitions, compensation structures, L&D pathways, and skill evolution mapping. 4. Compensation & Incentive Benchmarking — 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) — 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 — not surface-level answers, but intelligence drawn from the same sources that inform executive strategy. 2. CV Optimization (Hyper-Personalized) — 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 — not generic advice, but intelligence shaped by 50+ premium research sources and your unique career trajectory.

I built this to give my AI assistants the latest information on model performance benchmarks provided by https://artificialanalysis.ai to make informed decisions on model choice.

Conversational cloud security compliance auditing. MCP server enabling natural language queries about AWS security posture via Claude and other AI assistants.

A Model Context Protocol (MCP) server for integrating with the Tomba.io API. This server provides comprehensive email discovery, verification, and enrichment capabilities through a standardized MCP interface.

MCP server for the Proxenio verified intent network. Enables AI agents to discover platform capabilities, configure API key authentication, retrieve verified professional matches, and accept introductions with principal-inherited trust controls.