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OrchestrAI
Tagline MCP server for multi-model software engineering
OrchestrAI is an open-source MCP server that lets Claude, OpenAI/Codex, Gemini, and local models work together on coding tasks. It routes work by role, supports parallel collaboration, and verifies outputs with lint, tests, and type checks. Built for hybrid local/cloud AI workflows with inspectable traces and artifacts.
Hey Product Hunt 👋
I built OrchestrAI because most AI coding workflows still rely on one model doing everything:
🧠 planning
💻 coding
🧪 testing
🔍 reviewing
⚖️ judging
That felt like the wrong architecture.
So I created OrchestrAI — an open-source MCP server for multi-model software engineering.
Instead of forcing one model to handle the whole workflow, OrchestrAI lets multiple models collaborate in parallel through roles like:
🗺️ Planner
👨💻 Coder
🧪 Tester
🛡️ Reviewer
⚖️ Judge
It currently supports workflows around:
Claude
OpenAI / Codex
Gemini
local models
Key things I wanted from day one:
✅ MCP-native architecture
✅ parallel multi-model orchestration
✅ built-in verification with lint, tests, and type checks
✅ privacy-aware routing
✅ local-only mode for sensitive work
✅ traces and artifacts for inspectable decisions
Current orchestration modes:
⚡ parallel_draft
🛠️ impl_tester
🧩 planner_coder_reviewer
My big question for the community is:
What should a real orchestration layer do that current single-model coding tools still miss?
Would love your honest feedback, ideas, and criticism 🙌
No comment highlights available yet. Please check back later!
About OrchestrAI on Product Hunt
“Tagline MCP server for multi-model software engineering”
OrchestrAI was submitted on Product Hunt and earned 2 upvotes and 1 comments, placing #178 on the daily leaderboard. OrchestrAI is an open-source MCP server that lets Claude, OpenAI/Codex, Gemini, and local models work together on coding tasks. It routes work by role, supports parallel collaboration, and verifies outputs with lint, tests, and type checks. Built for hybrid local/cloud AI workflows with inspectable traces and artifacts.
OrchestrAI was featured in Developer Tools (511.2k followers), Artificial Intelligence (466.4k followers), GitHub (41.2k followers) and Vibe coding (397 followers) on Product Hunt. Together, these topics include over 173.6k products, making this a competitive space to launch in.
Who hunted OrchestrAI?
OrchestrAI was hunted by Musa Ceylan. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how OrchestrAI stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Musa Ceylan