Build effective agents using Model Context Protocol and simple workflow patterns.
By leveraging Python SDK / OpenAI API, the application isolates runtime dependencies while maintaining low-latency execution traces across multi-step LLM operations.
Clone lastmile-ai/mcp-agent from GitHub
Install dependencies with pip install -r requirements.txt (or uv sync)
Copy .env.example to .env and add your API keys
Run the skill server and connect your AI client via stdio or HTTP
Anthropic's official Claude Skills for working with document formats — fill, merge, and extract data from PDFs, Word files, PowerPoint decks, and Excel spreadsheets inside agent workflows.
Turn any codebase, with its docs, SQL schemas, configs, and PDFs, into a queryable knowledge graph. A /graphify skill for Claude Code, Cursor, Codex, and Gemini CLI: local deterministic AST parsing, every edge explained, no vector store.
The AI SEO Audit Team is an autonomous, multi-agent workflow built with Google ADK. It takes a webpage URL, crawls the live page, researches real-time SERP competition, and produces a polished, prioritized SEO optimization report.
MCP AI AgentsThis example demonstrates how to connect an ADK agent to a filesystem MCP server using the MCPToolset. The agent can perform file operations like reading, writing, and listing files through the Model Context Protocol.
MCP AI AgentsWelcome to the Firecrawl MCP Agent! This powerful agent demonstrates how to integrate Firecrawl's advanced web scraping capabilities with Google ADK through the Model Context Protocol (MCP).
