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https://github.com/dhyansraj/mcp-mesh

Enterprise-grade distributed AI agent framework | Develop → Deploy → Observe | K8s-native | Dynamic DI | Auto-failover | Multi-LLM | Python + Java + TypeScript
https://github.com/dhyansraj/mcp-mesh

agentic-ai ai-agents ai-agents-framework distributed-ai java kubernetes mcp mcp-mesh modelcontextprotocol python typescript

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

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README 

          
#  MCP Mesh



[![Release](https://github.com/dhyansraj/mcp-mesh/actions/workflows/release.yml/badge.svg?event=release)](https://github.com/dhyansraj/mcp-mesh/actions/workflows/release.yml)

[![Python Version](https://img.shields.io/badge/python-3.11+-blue.svg)](https://python.org)

[![Java Version](https://img.shields.io/badge/java-17+-orange.svg)](https://openjdk.org)

[![TypeScript](https://img.shields.io/badge/typescript-5.0+-blue.svg)](https://www.typescriptlang.org)

[![Go Version](https://img.shields.io/badge/go-1.23+-blue.svg)](https://golang.org)

[![Rust](https://img.shields.io/badge/rust-stable-orange.svg)](https://www.rust-lang.org)

[![PyPI](https://img.shields.io/pypi/v/mcp-mesh?color=blue&logo=pypi&logoColor=white)](https://pypi.org/project/mcp-mesh/)

[![npm](https://img.shields.io/npm/v/@mcpmesh/cli?color=red&logo=npm&logoColor=white)](https://www.npmjs.com/package/@mcpmesh/cli)

[![Maven Central](https://img.shields.io/maven-central/v/io.mcp-mesh/mcp-mesh-spring-boot-starter?color=orange&logo=apachemaven&logoColor=white)](https://central.sonatype.com/artifact/io.mcp-mesh/mcp-mesh-spring-boot-starter)

[![Docker](https://img.shields.io/badge/docker-hub-blue.svg?logo=docker&logoColor=white)](https://hub.docker.com/u/mcpmesh)

[![Helm](https://img.shields.io/badge/helm-charts-blue.svg?logo=helm&logoColor=white)](https://github.com/dhyansraj/mcp-mesh/pkgs/container/mcp-mesh%2Fmcp-mesh-core)

[![Discord](https://img.shields.io/discord/1386739813083779112?color=7289DA&label=Discord&logo=discord&logoColor=white)](https://discord.gg/KDFDREphWn)

[![YouTube](https://img.shields.io/badge/YouTube-MCPMesh-red?logo=youtube&logoColor=white)](https://www.youtube.com/@MCPMesh)

[![License](https://img.shields.io/badge/license-Open%20Source-blue.svg)](#license)



> **The future of AI is not one large model, but many specialized agents working together.**





  📚 Documentation ·

  🚀 Quick Start ·

  🎬 YouTube ·

  💬 Discord




---



## ⚡ Getting Started



```bash

# Install the CLI

npm install -g @mcpmesh/cli



# Explore commands

meshctl --help



# Built-in documentation

meshctl man

```



**[Python Quick Start →](https://mcp-mesh.ai/python/getting-started/)** | **[Java Quick Start →](https://mcp-mesh.ai/java/getting-started/)** | **[TypeScript Quick Start →](https://mcp-mesh.ai/typescript/getting-started/)**



---



## 🎯 Why MCP Mesh?



You write the agent logic. The mesh discovers, connects, heals, and traces — across languages, machines, and clouds.



---



### **For Developers 👩‍💻**



**Stop fighting infrastructure. Start building intelligence.**



- **Zero Boilerplate**: Simple decorators/functions replace hundreds of lines of networking code

- **Python, Java & TypeScript**: Write MCP servers as simple functions in your preferred language - no manual client/server setup

- **Web Framework Integration**: Inject MCP agents directly into FastAPI (Python), Spring Boot (Java), or Express (TypeScript) APIs seamlessly

- **LLM as Dependencies**: Inject LLMs just like MCP agents - dynamic prompts with Jinja2 (Python), FreeMarker (Java), or Handlebars (TypeScript)

- **Seamless Development Flow**: Code locally, test with Docker Compose, deploy to Kubernetes - same code, zero changes

- **kubectl-like Management**: `meshctl` - a familiar command-line tool to run, monitor, and manage your entire agent network



```python

# MCP Agent

@app.tool()

@mesh.tool(dependencies=["weather_service"])

def plan_trip(weather_service=None):

    # Just write business logic - mesh handles the rest



# FastAPI Route with MCP DI

@api.post("/trip-planning")

@mesh.route(dependencies=["plan_trip"])

async def create_trip(trip_data: dict, plan_trip=None):

    # Use MCP agents directly in your web API

    return plan_trip(trip_data)

```



---



### **For Solution Architects 🏗️**



**Design intelligent systems, not complex integrations.**



- **Agent-Centric Architecture**: Design specialized agents with clear capabilities and dependencies, not monolithic systems

- **Dynamic Intelligence**: Agents get smarter automatically when new capabilities come online - no reconfiguration needed

- **Domain-Driven Design**: Solve business problems with ecosystems of focused agents that can be designed and developed independently

- **Composable Solutions**: Mix and match agents to create new business capabilities without custom integration code



**Example**: Deploy a financial analysis agent that automatically discovers and uses risk assessment, market data, and compliance agents as they become available.



---



### **For DevOps & Platform Teams ⚙️**



**AI infrastructure out of the box.**



- **Kubernetes-Native**: Deploy with Helm charts - horizontal scaling, health checks, and service discovery included

- **Enterprise Observability**: Built-in Grafana dashboards, distributed tracing, and centralized logging for complete system visibility

- **Zero-Touch Operations**: Agents self-register, auto-discover dependencies, and gracefully handle failures without network restarts

- **Standards-Based**: Leverage existing Kubernetes patterns - RBAC, network policies, service mesh integration, and security policies



**Scale from 2 agents to 200+ with the same operational complexity.**



---



### **For Support & Operations 🛠️**



**Complete visibility and zero-downtime operations.**



- **Real-Time Network Monitoring**: See every agent, dependency, and health status in live dashboards

- **Intelligent Scaling**: Agents scale independently based on demand - no cascading performance issues

- **Graceful Failure Handling**: Agents degrade gracefully when dependencies are unavailable, automatically reconnect when services return

- **One-Click Diagnostics**: `meshctl status` provides instant network health assessment with actionable insights



---



### **For Engineering Leadership 📈**



**Transform AI experiments into production revenue.**



- **Accelerated Time-to-Market**: Move from PoC to production deployment in weeks, not months

- **Cross-Team Collaboration**: Enable different departments to build agents that automatically enhance each other's capabilities

- **Risk Mitigation**: Proven patterns help ensure reliable AI deployments that scale with your business

- **Future-Proof Architecture**: Add new AI capabilities without disrupting existing systems



**Turn your AI strategy from "promising experiments" to "competitive advantage in production."**



---



## Architecture Overview



![MCP Mesh Architecture](images/mcp-mesh_arch.png)



**MCP Mesh handles the complexity so you don't have to:**



- **Zero Boilerplate**: Just add `@mesh.tool()` - networking handled automatically

- **Dynamic Everything**: Add/remove/upgrade services without touching other code

- **Complex Apps Made Simple**: Financial services example shows 6+ interconnected agents

- **Production Ready**: Built-in resilience, distributed observability, and scaling



**The Magic**: Write simple functions in Python, Java, or TypeScript, get distributed systems.



---



## Key Features



### **Dynamic Dependency Injection & Service Discovery**



- **Pull-based discovery** with runtime function injection - no networking code required

- **Automatic agent discovery** without configuration

- **Smart dependency resolution** with version constraints and tags

- **Load balancing** across multiple service providers

- **LLM dependency injection** - treat LLMs as first-class dependencies with automatic tool discovery and dynamic prompts



### **Resilience**



- **Registry as facilitator** - agents communicate directly with fault tolerance

- **Self-healing architecture** - automatic reconnection when services return

- **Graceful degradation** - agents work standalone when dependencies unavailable

- **Background orchestration** - mesh coordinates without blocking business logic



### **Observability**



- **Complete observability stack** - Grafana dashboards, Tempo tracing, Redis session management

- **Distributed tracing** with OTLP export and cross-agent context propagation

- **Real-time trace streaming** for multi-agent workflow monitoring

- **Advanced session management** with Redis-backed stickiness across pod replicas



### **Developer Experience & Operations**



- **Near-complete MCP protocol support** for distributed networks

- **Enhanced proxy system** with kwargs-driven auto-configuration for timeouts, retries, streaming

- **meshctl CLI** for lifecycle management and network insights

- **Kubernetes native** with scaling, health checks, and comprehensive observability



---



## MCP Mesh vs Other AI Agent Frameworks



| Feature                                      | Other Frameworks  | MCP Mesh               |

| -------------------------------------------- | ----------------- | ---------------------- |

| **Zero-config Dependency Injection**         | ❌                | ✅                     |

| **Dynamic Agent Discovery & Hot Join/Leave** | ❌                | ✅                     |

| **Cross-language Support**                   | ❌                | ✅ Python + Java + TypeScript |

| **Same Code: Local → Docker → K8s**          | ❌ Rewrite needed | ✅                     |

| **Developer CLI (scaffold, trace, status)**  | ❌                | ✅ `meshctl`           |

| **Kubernetes-native (Helm)**                 | ❌ DIY            | ✅                     |

| **Distributed Tracing (OpenTelemetry)**      | ❌ DIY            | ✅ Grafana/Tempo       |

| **Auto-failover & Graceful Degradation**     | ❌                | ✅                     |

| **LLM as Dependency (Discovery + Failover)** | ❌                | ✅                     |

| **Zero-config Testing (Topology Mocking)**   | ❌                | ✅                     |

| **Standard Protocol**                        | ❌ Custom         | ✅ MCP                 |

| **Framework Lock-in**                        | High (classes)    | Low (decorators)       |

| **Lines of Code per Agent**                  | ~50+              | ~10                    |



**[See full comparison →](https://mcp-mesh.ai/comparison/)**



---



## Contributing



We welcome contributions from the community! MCP Mesh is designed to be a collaborative effort to advance the state of distributed MCP applications.



### How to Contribute



1. **[Check the Issues](https://github.com/dhyansraj/mcp-mesh/issues)** - Find good first issues or suggest new features

2. **[Join Discussions](https://github.com/dhyansraj/mcp-mesh/discussions)** - Share ideas and get help from the community

3. **[Submit Pull Requests](https://github.com/dhyansraj/mcp-mesh/pulls)** - Contribute code, documentation, or examples

4. **Follow our development guidelines** - See project structure and coding standards below



---



## Community & Support



- **[Discord](https://discord.gg/KDFDREphWn)** - Real-time help and discussions

- **[GitHub Discussions](https://github.com/dhyansraj/mcp-mesh/discussions)** - Share ideas and ask questions

- **[Issues](https://github.com/dhyansraj/mcp-mesh/issues)** - Report bugs or request features

- **[Examples](examples/)** - Working code examples and deployment patterns



---



## License



This project is open source. License details will be provided in the LICENSE file.



---



## Acknowledgments



- **[Anthropic](https://anthropic.com)** for creating the MCP protocol that inspired this project

- **[FastMCP](https://github.com/jlowin/fastmcp)** for providing excellent MCP server foundations

- **[Kubernetes](https://kubernetes.io)** community for building the infrastructure platform that makes this possible

- All the **contributors** who help make MCP Mesh better



---



## 📚 Learn More



1. **[📚 Full Documentation](https://mcp-mesh.ai/)** - Complete guides and reference

2. **[⚡ Quick Tutorial](https://mcp-mesh.ai/01-getting-started/)** - Build your first distributed MCP agent

3. **[💬 Join Discord](https://discord.gg/KDFDREphWn)** - Connect with the community

4. **[🔧 Contribute](https://mcp-mesh.ai/contributing/)** - Help build the future of AI orchestration



**Star the repo** if MCP Mesh helps you build better AI systems! ⭐