mcp-ts-template and mcp-streamable-http

The TypeScript template provides a comprehensive framework for building MCP servers, while the Streamable HTTP project offers a specific example of implementing MCP's streamable HTTP capabilities, making them ecosystem siblings where the latter could be used as a reference or component within the former.

mcp-ts-template
62
Established
mcp-streamable-http
40
Emerging
Maintenance 10/25
Adoption 10/25
Maturity 25/25
Community 17/25
Maintenance 2/25
Adoption 10/25
Maturity 7/25
Community 21/25
Stars: 119
Forks: 20
Downloads:
Commits (30d): 0
Language: TypeScript
License: Apache-2.0
Stars: 127
Forks: 33
Downloads:
Commits (30d): 0
Language: TypeScript
License:
No risk flags
No License Stale 6m 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 mcp-streamable-http

invariantlabs-ai/mcp-streamable-http

Example implementation of MCP Streamable HTTP client/server in Python and TypeScript.

This project provides example implementations for developers to build real-time, interactive chat applications using the Model Context Protocol (MCP) Streamable HTTP. It takes user input as chat messages and returns responses, demonstrating how to handle streaming data between a client and server. Developers building AI-powered chat interfaces or similar streaming data applications would use this.

API-development real-time-chat AI-integration client-server-architecture streaming-data

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