Miro describes itself as an AI innovation workspace for teamwork; the company offers a collaborative workflow platform for software application developers to get into the “flow” and push code through from concept to delivery in working producton. Now working to connect its technologies to the most pertinent integration streams and channels possible, the company has announced its Model Context Protocol (MCP) server. But then, so has every other enterprise technology vendor worth its salt, so what makes this one different?
Bidirectional integration
Built in collaboration with Anthropic, AWS, GitHub, Google and Windsurf (a company known for its AI-native integrated development environment (IDE) that acts as a collaborative agentic coding partner), the MCP server creates bidirectional integration between Miro’s AI innovation workspace technology and AI coding environments.
The aim is to help teams build the right things faster.
Jeff Chow, chief product & technology officer at Miro reminds us that organisations understand that AI can help them move faster, but uncertainty remains around how to ground it in real workflows and decisions so that it’s not just fast, but also accurate. As we know, without “shared context” in place, AI outputs remain fragmented, hard to trust and costly to validate – particularly for teams outside of engineering, such as IT, security and operations.
“When product, design and engineering align visually on intent and decisions, that shared context can flow into agentic coding systems and back into cross-functional discussions as work evolves. By making this context accessible through MCP, we’re helping organisations realise the full value of their AI investment,” said Chow.
Get real, AI, I mean, really
Miro’s MCP server connects the shared visual context that teams already create in Miro with AI agents across an organisation. This means that teams may be able to gain greater confidence that AI outputs are grounded in real architectures, real decisions and real cross-functional understanding.
“Millions of developers use GitHub Copilot for software development and they are increasingly using agentic workflows, of which MCP servers are incredibly valuable in keeping developers in the flow by giving access to context and tools across systems,” said Simina Pasat, VP of product at GitHub. “Closer connection with Miro through its MCP integration means engineering teams using GitHub Copilot can better access architectural diagrams, user stories and design decisions without having to leave their workflow, powering a smarter, faster and more secure development experience.”
With this release, Miro enables what it calls two “foundational use cases” for product development workflows, with more to be announced:
- Automated Code Visualisation – Teams can generate system architecture diagrams and detailed documents directly from codebases within AI coding tools, revealing component relationships and dependencies without manual reverse-engineering. This empowers engineering and product teams to understand existing codebases when onboarding onto new projects or new team members.
- Context-Aware Code Generation – Context-driven AI development brings cross-functional team members directly into the development workflow. Product Requirements Documents (PRDs), design specs, user research and existing codebase architecture – created on the Miro canvas become input for agentic coding development. The result is more context-aware code that understands an existing system and meets the mark with fewer revisions.
Tighter feedback loops
“Miro’s MCP server unlocks a powerful new workflow to go from ideas to apps using Replit,” said Jeff Burke, head of partnerships at Replit. “By seamlessly passing context from Miro to Replit, teams can reduce friction and move from concept to execution faster. We’re excited to see how Replit builders use Miro’s MCP server to create tighter feedback loops between thinking and making – and ship products faster as a result.”
Miro’s MCP server includes existing Miro enterprise security controls and governance policies. The full list of AI coding platforms that Miro’s MCP connects with is: Claude Code, AWS Kiro, GitHub Copilot, Gemini CLI, Windsurf, Cursor, Lovable, Replit, OpenAI Codex, VS Code and Devin.
What appears most original (let’s not say unique or special) about this technology is its AI-nativeness, its core alignment to codebase command-line-level technologies that grassroots software application development engineers will be familiar with every day and perhaps also its ability to have integrated with the big names that operate at the agentic platform level as an admittedly smaller operation.