mcp-ts-core and mcp-farmer

The TypeScript template (`cyanheads/mcp-ts-core`) and the CLI tool (`boldare/mcp-farmer`) are complements, as the CLI tool is designed to scaffold, test, extend, and analyze MCP servers, which can then be built using the provided TypeScript template.

mcp-ts-core
65
Established
mcp-farmer
48
Emerging
Maintenance 13/25
Adoption 10/25
Maturity 25/25
Community 17/25
Maintenance 10/25
Adoption 4/25
Maturity 22/25
Community 12/25
Stars: 119
Forks: 20
Downloads:
Commits (30d): 0
Language: TypeScript
License: Apache-2.0
Stars: 5
Forks: 1
Downloads:
Commits (30d): 0
Language: TypeScript
License: MIT
No risk flags
No risk flags

About mcp-ts-core

cyanheads/mcp-ts-core

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 is a framework for developers to quickly build and deploy specialized AI agent servers that perform specific tasks. It takes declarative definitions of 'tools' and 'resources' (like searching a database or greeting a user) and produces a ready-to-use server, handling common backend complexities like authentication, storage, and logging. Developers who need to create custom, task-specific AI agents without building server infrastructure from scratch would use this.

AI-agent-development backend-development developer-tools cloud-native-applications server-side-logic

About mcp-farmer

boldare/mcp-farmer

A CLI tool for scaffolding, testing, extending and analyzing MCP (Model Context Protocol) servers

Provides automated vetting, documentation generation, and AI-assisted tool creation for MCP servers through multiple transport methods (HTTP with Streamable/SSE fallback and stdio). Integrates with popular coding agents (OpenCode, Claude Code, Gemini CLI) via the Agent Client Protocol (ACP) for intelligent tool generation from OpenAPI/GraphQL specs and automated probe testing with LLM-generated inputs. Auto-discovers servers from client configs (Cursor, VS Code, Claude Desktop) and generates shareable HTML/JSON/Markdown audit reports and documentation.

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