mcp-ts-template and template-mcp-server

These are ecosystem siblings offering language-specific scaffolding for the same MCP server development task—TypeScript and Python developers would each choose the appropriate template based on their preferred language and framework (FastMCP vs. declarative tools).

mcp-ts-template
62
Established
template-mcp-server
58
Established
Maintenance 10/25
Adoption 10/25
Maturity 25/25
Community 17/25
Maintenance 13/25
Adoption 8/25
Maturity 15/25
Community 22/25
Stars: 119
Forks: 20
Downloads:
Commits (30d): 0
Language: TypeScript
License: Apache-2.0
Stars: 49
Forks: 50
Downloads:
Commits (30d): 0
Language: Python
License: Apache-2.0
No risk flags
No Package No Dependents

About mcp-ts-template

cyanheads/mcp-ts-template

TypeScript template for building Model Context Protocol (MCP) servers. Ships with declarative tools/resources, pluggable auth, multi-backend storage, OpenTelemetry observability, and first-class support for both local and edge (Cloudflare Workers) runtimes.

This project helps developers build specialized backend servers that integrate with AI agents. You provide descriptions of 'tools' that an agent can use, along with their inputs and outputs. The project then generates a fully functional server, handling all the underlying infrastructure like data storage, authentication, and logging. It's designed for developers creating custom AI agent capabilities, rather than end-users interacting with AI directly.

backend-development AI-agent-integration server-framework developer-tools microservices

About template-mcp-server

redhat-data-and-ai/template-mcp-server

Production-ready Python template for building MCP servers with FastMCP, FastAPI, OAuth, and OpenShift deployment.

This is a pre-built foundation for developers to create new Model Context Protocol (MCP) servers quickly and efficiently. It takes a conceptual idea for a server that uses MCP and provides a robust, production-ready backend, complete with examples of tools and deployment readiness. This is for backend developers and MLOps engineers who need to deploy AI models or other services as MCP-compliant servers.

backend-development MLOps API-development cloud-deployment enterprise-IT

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