The Model Context Protocol is rapidly evolving. This page outlines our current thinking on key priorities and direction for approximately the next six months, though these may change significantly as the project develops. To see what’s changed recently, check out the specification changelog.

We value community participation! Each section links to relevant discussions where you can learn more and contribute your thoughts.

For a technical view of our standardization process, visit the Standards Track on GitHub, which tracks how proposals progress toward inclusion in the official MCP specification.

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Validation

To foster a robust developer ecosystem, we plan to invest in:

• Reference Client Implementations: demonstrating protocol features with high-quality AI applications
• Compliance Test Suites: automated verification that clients, servers, and SDKs properly implement the specification

These tools will help developers confidently implement MCP while ensuring consistent behavior across the ecosystem.

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Registry

For MCP to reach its full potential, we need streamlined ways to distribute and discover MCP servers.

We plan to develop an MCP Registry that will enable centralized server discovery and metadata. This registry will primarily function as an API layer that third-party marketplaces and discovery services can build upon.

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Agents

As MCP increasingly becomes part of agentic workflows, we’re exploring improvements such as:

• Agent Graphs: enabling complex agent topologies through namespacing and graph-aware communication patterns
• Interactive Workflows: improving human-in-the-loop experiences with granular permissioning, standardized interaction patterns, and ways to directly communicate with the end user

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Multimodality

Supporting the full spectrum of AI capabilities in MCP, including:

• Additional Modalities: video and other media types
• Streaming: multipart, chunked messages, and bidirectional communication for interactive experiences

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Governance

We’re implementing governance structures that prioritize:

• Community-Led Development: fostering a collaborative ecosystem where community members and AI developers can all participate in MCP’s evolution, ensuring it serves diverse applications and use cases
• Transparent Standardization: establishing clear processes for contributing to the specification, while exploring formal standardization via industry bodies

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Get Involved

We welcome your contributions to MCP’s future! Join our GitHub Discussions to share ideas, provide feedback, or participate in the development process.