Migration from Docker to Standalone Python Server (#73)

* Migration from docker to standalone server
Migration handling
Fixed tests
Use simpler in-memory storage
Support for concurrent logging to disk
Simplified direct connections to localhost

* Migration from docker / redis to standalone script
Updated tests
Updated run script
Fixed requirements
Use dotenv
Ask if user would like to install MCP in Claude Desktop once
Updated docs

* More cleanup and references to docker removed

* Cleanup

* Comments

* Fixed tests

* Fix GitHub Actions workflow for standalone Python architecture

- Install requirements-dev.txt for pytest and testing dependencies
- Remove Docker setup from simulation tests (now standalone)
- Simplify linting job to use requirements-dev.txt
- Update simulation tests to run directly without Docker

Fixes unit test failures in CI due to missing pytest dependency.

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

* Remove simulation tests from GitHub Actions

- Removed simulation-tests job that makes real API calls
- Keep only unit tests (mocked, no API costs) and linting
- Simulation tests should be run manually with real API keys
- Reduces CI costs and complexity

GitHub Actions now only runs:
- Unit tests (569 tests, all mocked)
- Code quality checks (ruff, black)

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

* Fixed tests

* Fixed tests

---------

Co-authored-by: Claude <noreply@anthropic.com>

docs/ai-collaboration.md

@@ -12,7 +12,7 @@ This server enables **true AI collaboration** between Claude and multiple AI mod
 - **Cross-tool continuation** - Start with one tool (e.g., `analyze`) and continue with another (e.g., `codereview`) using the same conversation thread
 - **Both AIs coordinate their approaches** - questioning assumptions, validating solutions, and building on each other's insights
 - Each conversation maintains full context while only sending incremental updates
-- Conversations are automatically managed with Redis for persistence
+- Conversations are automatically managed in memory for the session duration
 
 ## Example: Multi-Model AI Coordination
 
@@ -52,7 +52,7 @@ This server enables **true AI collaboration** between Claude and multiple AI mod
 **Conversation Management:**
 - Up to 10 exchanges per conversation (configurable via `MAX_CONVERSATION_TURNS`)
 - 3-hour expiry (configurable via `CONVERSATION_TIMEOUT_HOURS`)
-- Thread-safe with Redis persistence across all tools
+- Thread-safe with in-memory persistence across all tools
 - **Image context preservation** - Images and visual references are maintained across conversation turns and tool switches
 
 ## Cross-Tool & Cross-Model Continuation Example