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valado/pantheon-mcp

by Various

A collection of AI agents

V

MCP

valado/pantheon-mcp

Added 1 June 2026

Overview

A collection of AI agents implemented in TypeScript. The repository provides multiple agent implementations that can be used together or individually. It is designed for building multi-agent systems using the Model Context Protocol.

Best for

Best for
Developers exploring multi-agent architectures with TypeScript

Use cases

  • Building multi-agent workflows with pre-built agents
  • Integrating AI agents into existing TypeScript projects
  • Experimenting with agent orchestration and communication

How to use

Install

npx pantheon-mcp

Example client config

{\n  "mcpServers": {\n    "pantheon-mcp": {\n      "type": "stdio",\n      "command": "npx",\n      "args": ["-y", "pantheon-mcp"],\n      "env": {}\n    }\n  }\n}

Notes

A collection of AI agents implemented in TypeScript. The repository provides multiple agent implementations that can be used together or individually. It is designed for building multi-agent systems using the Model Context Protocol.

8 stars on GitHub. Last updated 2025-09-27. Licensed MIT.

Use cases

  • Building multi-agent workflows with pre-built agents
  • Integrating AI agents into existing TypeScript projects
  • Experimenting with agent orchestration and communication

Pros

  • Written in TypeScript for type safety and developer experience
  • Open source with a modular structure for selective use
  • Provides a starting point for multi-agent experimentation

Cons

  • Low star count indicates limited community adoption
  • Documentation and examples may be sparse
  • Project may lack active maintenance or frequent updates

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.

Pros

  • Written in TypeScript for type safety and developer experience
  • Open source with a modular structure for selective use
  • Provides a starting point for multi-agent experimentation

Cons

  • Low star count indicates limited community adoption
  • Documentation and examples may be sparse
  • Project may lack active maintenance or frequent updates
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