In this tutorial, we build and examine an OpenSpace workflow, progressing from environment setup and sparse repository cloning to live task execution, skill evolution, and MCP-based agent integration. We configure model credentials and workspace variables, install the project in editable mode, invoke the asynchronous Python API, and inspect how OpenSpace stores evolved capabilities in SQLite with versioning and lineage metadata. We also create a custom SKILL.md, connect host-agent skills, test warm-task reuse, launch the streamable HTTP MCP server, and analyze the showcase evolution database to understand how FIX, DERIVED, and CAPTURED skills support lower-cost, reusable agent behavior.
import os, sys, subprocess, sqlite3, json, textwrap, shutil, time, pathlib
ANTHROPIC_API_KEY = ""
OPENAI_API_KEY = ""
OPENSPACE_MODEL = "anthropic/claude-sonnet-4-5"
