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tadas-github/a2asearch-mcp

by Various

MCP server for searching AI agents, MCP servers, CLI tools and agent skills via A2ASearch

T

MCP

tadas-github/a2asearch-mcp

Added 1 June 2026

#a2asearch #ai-agents #claude #cursor #mcp #mcp-server #model-context-protocol

Overview

This MCP server enables AI assistants to search for AI agents, MCP servers, CLI tools, and agent skills through the A2ASearch platform. Built in JavaScript, it integrates as a tool for querying a directory of developer resources via the Model Context Protocol.

Best for

Best for
Developers building agentic workflows who need a searchable directory of tools and agents

Use cases

  • Searching for available AI agents through an AI assistant
  • Discovering MCP servers for integration into workflows
  • Finding CLI tools or agent skills via conversational queries

Notes

This MCP server enables AI assistants to search for AI agents, MCP servers, CLI tools, and agent skills through the A2ASearch platform. Built in JavaScript, it integrates as a tool for querying a directory of developer resources via the Model Context Protocol.

14 stars on GitHub. Last updated 2026-03-30. Licensed MIT.

Use cases

  • Searching for available AI agents through an AI assistant
  • Discovering MCP servers for integration into workflows
  • Finding CLI tools or agent skills via conversational queries

Pros

  • Lightweight JavaScript implementation for easy integration
  • Works with any MCP-compatible client like Claude
  • Searches multiple categories (agents, servers, tools, skills) in one request

Cons

  • Small community surrounding the project (14 stars on GitHub)
  • Depends on the coverage and accuracy of the A2ASearch index
  • Requires an MCP-compatible client to function

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

Pros

  • Lightweight JavaScript implementation for easy integration
  • Works with any MCP-compatible client like Claude
  • Searches multiple categories (agents, servers, tools, skills) in one request

Cons

  • Small community surrounding the project (14 stars on GitHub)
  • Depends on the coverage and accuracy of the A2ASearch index
  • Requires an MCP-compatible client to function