Just wondering what MCP servers you guys integrated and feel like has dramatically changed your success. Also, what other methodologies do you work with to achieve good results? Conversely what has been a disappointment and you've decided not to work with anymore?

This was a game changer for me - let Claude Code review with zen MCP before and after every a meaningful update to the code. Gemini is being the adult in the room, looking over Claude Code's shoulder.

It results with meaningfully better code. It finds bugs (real ones), focusing not only on the code itself but what's around it, how it's being used, etc.

They're just better together, Claude and Gemini (I'm not impressed by zen + o3 abilities - it feels like o3 is trying too hard (to impress?) by recommending over-engineered changes), and it made me think - if LLMs behave in similar ways to our brains, perhaps they are meant to work together on other high-value tasks? I know it's not a new concept but the positive impact is very clear to me now.

Thoughts?

Meet Zen MCP: One Context, Many Minds.

https://github.com/BeehiveInnovations/zen-mcp-server

This started off as an experiment two days ago with just Claude Code working with Gemini: https://www.reddit.com/r/ClaudeAI/comments/1l73a1x/claude_code_gemini_pro_two_ai_coders_working_as/

But then it exploded into something bigger. You can now use this MCP server to make Claude Code reach out to Gemini Pro / Flash / O3 / O3-Mini and collaboratively solve problems. This has now effectively become Claude Code _for_ Claude Code.

1. Multi-Model Collaboration with Continuity / Context Awareness

2. Automatic model selection

3. Extended context windows beyond Claude's limits

4. Smart file handling

5. Effective bypass of MCP's 25K limit but intelligently sharing large prompts as files with the MCP instead

6. Claude Code can use the same tools with any model and cross-talk and continue with the same thread of communication to find solutions and solve problems.

Features true AI orchestration with conversations that continue across tasks - Give Claude a complex task and let it orchestrate between models automatically. Claude stays in control, performs the actual work, but gets perspectives from the best AI for each subtask. Claude can switch between different tools and models mid-conversation, with context carrying forward seamlessly.

Example Workflow:

1. Claude uses Gemini Pro to deeply analyze the code in question

2. Switches to O3 to continue discussion about its findings

3. Uses Flash to validate formatting suggestions from O3

4. Performs the actual work after taking in feedback from all three

5. Returns to Pro for a thorough precommit review

All within a single conversation thread! Gemini Pro in step 5 knows what was recommended by O3 in step 2! Taking that context and review into consideration to aid with its pre-commit review.

So I think all know how useful zen-mcp-server was, but for some reason it just stops sending request back to claude and basically useless.

So I decided to review forks to see if someone tried to fix that and found this guy: https://github.com/FallDownTheSystem/zen-mcp-server

Checked commits and found this gold:

Just wanted to share, that is just LMAO