Mcp Mesh

Name: Mcp Mesh
Author: dhyansraj

@mcpmesh/cli · by dhyansraj

34 643/wk 0 tools GitHub npm

No known CVEs

MIT license

Actively maintained

Last commit 15d ago

Works with most clients

Transport: stdio, sse, http

0 tools

Grade F

Edit this pageView history

AI / ML DevOps

Step 1

Install in your client

Config is the same across clients — only the file and path differ.

Supported in Claude Desktopstdio, sse, http · Node 18+

Paste into ~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "mcp-mesh": {
      "args": [
        "-y",
        "@mcpmesh/cli"
      ],
      "command": "npx"
    }
  }
}

Are you the author?

Add this badge to your README to show your security score and help users find safe servers.

Embed in your READMEAbout badges →

[![MCPpedia Score](https://mcppedia.org/api/badge/mcp-mesh)](https://mcppedia.org/s/mcp-mesh)

Read me

What Mcp Mesh does

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

Test This Server

This server supports HTTP transport. Be the first to test it — help the community know if it works.

Loading README…

Scored, not listed

Why this score

Five weighted categories — click any category to see the underlying evidence.

Score breakdown

61/100across 5 weighted dimensions

How we score →

0255075100

−39

Security

Maintenance

Efficiency

Documentation

Compatibility

Categoriesclick a row to see evidence

Security

OSV.dev

No known CVEs.

Checked @mcpmesh/cli against OSV.dev.

Community

Reviews

Be the first to review

Have you used this server?

Share your experience — it helps other developers decide.

How easy was setup?Did it work reliably?How was the documentation?

Frequently Asked Questions

Is Mcp Mesh safe to use?: Mcp Mesh has no known CVEs as of the latest MCPpedia security scan. It does not require authentication, so any local process can connect — keep this in mind in shared environments. Licensed under MIT.
How do I install Mcp Mesh?: Mcp Mesh supports copy-paste install configs on its MCPpedia page for Claude Desktop, Cursor, and Claude Code. Scroll to the Quick Install section and select your client.
What AI clients work with Mcp Mesh?: Mcp Mesh is compatible with claude-desktop, cursor, claude-code. It uses stdio and sse and http transport.
Is Mcp Mesh actively maintained?: Mcp Mesh is actively maintained — last commit was 15 days ago. It has 34 GitHub stars.

Similar servers

Others in ai-ml / devops

View all →

Memory MCP Server98

Persistent memory using a knowledge graph

86.4k 5

Sequential Thinking MCP Server98

Dynamic problem-solving through sequential thought chains

86.4k 1

Mcp Gitlab96

MCP server for using the GitLab API

1.6k 12

Antigravity Workspace Template96

Workspace template + MCP server for Claude Code, Codex CLI, Cursor & Windsurf. Multi-agent knowledge engine (ag-refresh / ag-ask) that turns any codebase into a queryable AI assistant.

1.2k 2

MCP Security Weekly

Get CVE alerts and security updates for Mcp Mesh and similar servers.

Community

Discussion

Start a conversation

Ask a question, share a tip, or report an issue.

Has anyone used this with Cursor?How do you handle auth?Any alternatives?

🎯 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

from fastmcp import FastMCP import mesh app = FastMCP("TripPlanner") @app.tool() @mesh.tool( capability="plan_trip", dependencies=[ {"capability": "weather", "tags": ["+claude"]}, {"capability": "hotels", "tags": ["+gpt"]}, {"capability": "flights"}, {"capability": "budget", ... [View full README on GitHub](https://github.com/dhyansraj/mcp-mesh#readme)

Frequently Asked Questions

Is Mcp Mesh safe to use?

Mcp Mesh has no known CVEs as of the latest MCPpedia security scan. It does not require authentication, so any local process can connect — keep this in mind in shared environments. Licensed under MIT.

How do I install Mcp Mesh?

Mcp Mesh supports copy-paste install configs on its MCPpedia page for Claude Desktop, Cursor, and Claude Code. Scroll to the Quick Install section and select your client.

What AI clients work with Mcp Mesh?

Mcp Mesh is compatible with claude-desktop, cursor, claude-code. It uses stdio and sse and http transport.

Is Mcp Mesh actively maintained?

Mcp Mesh is actively maintained — last commit was 15 days ago. It has 34 GitHub stars.

MCP Mesh

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

📚 Documentation · 🚀 Quick Start · 🎬 YouTube · 💬 Discord

⚡ Getting Started

# Install the CLI
npm install -g @mcpmesh/cli

# Explore commands
meshctl --help

# Built-in documentation
meshctl man

Python Quick Start → | Java Quick Start → | TypeScript Quick Start →

🎯 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

from fastmcp import FastMCP
import mesh

app = FastMCP("TripPlanner")

@app.tool()
@mesh.tool(
    capability="plan_trip",
    dependencies=[
        {"capability": "weather", "tags": ["+claude"]},
        {"capability": "hotels",  "tags": ["+gpt"]},
        {"capability": "flights"},
        {"capability": "budget", 

... [View full README on GitHub](https://github.com/dhyansraj/mcp-mesh#readme)