An MCP server that exposes an AI project portfolio as queryable tools, allowing users to ask about projects, search by technology, or get details via natural language.
MCP server for semantic code search and explanation. Allows AI agents to search, ask questions, and manage memory about a codebase with local embeddings and LLM integration.
MCP server that exposes a resume as callable tools and resources, enabling AI agents to query experience, skills, projects, and contact information via natural language.
Turns a developer's portfolio into a queryable MCP server, enabling AI assistants to interrogate career data (experience, projects, skills) with grounded citations.
Local MCP server that provides semantic search (RAG) over code repositories, enabling AI clients like Claude and Gemini to access project context without manual re-upload.
A Dockerized MCP server that fetches your GitHub repositories, indexes them into a local vector database, and exposes semantic code search tools to LLM clients for tailored technical mock interviews grounded in your actual code.