mcp-mesh and MCP

mcp-mesh
53
Established
MCP
39
Emerging
Maintenance 10/25
Adoption 6/25
Maturity 24/25
Community 13/25
Maintenance 13/25
Adoption 3/25
Maturity 9/25
Community 14/25
Stars: 24
Forks: 4
Downloads: —
Commits (30d): 0
Language: Python
License: MIT
Stars: 4
Forks: 3
Downloads: —
Commits (30d): 0
Language: TypeScript
License: MIT
No risk flags
No Package No Dependents

About mcp-mesh

dhyansraj/mcp-mesh

Enterprise-grade distributed AI agent framework | Develop → Deploy → Observe | K8s-native | Dynamic DI | Auto-failover | Multi-LLM | Python + Java + TypeScript

MCP Mesh helps platform teams and solution architects quickly build and manage complex AI systems made of many specialized AI agents working together. It takes individual agent logic, written in Python, Java, or TypeScript, and connects them into a robust, distributed network. The output is a highly scalable, observable, and resilient AI system ready for enterprise-level deployment.

AI-architecture distributed-systems MLOps AI-deployment intelligent-automation

About MCP

ShunsukeHayashi/MCP

MCP (Model Context Protocol) server implementations for AI agent integration

Monorepo containing 20+ MCP server implementations spanning AI agents, browser automation, external service integrations (GitHub, Slack, Notion, Discord), and file/system operations. Built with TypeScript and Turbo for optimized monorepo builds, servers communicate via stdio transport and integrate with Claude Desktop through JSON configuration. Includes specialized servers for workflow automation (Asana, Google Apps Script), content processing (transcription, RSS), and environment management (Conda).

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mcp-mesh and DeepMCPAgent

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