We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/IBM/ibmi-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from agno.models.anthropic import Claude
from agno.tools.mcp import MCPTools
from dotenv import load_dotenv
import os
load_dotenv(override=True)
env = {
"MCP_AUTH_TOKEN": os.getenv("MCP_AUTH_TOKEN"),
"MCP_SERVER_CATALOG_URLS": f"http://localhost:4444/servers/{os.getenv('MCP_SERVICE_ID')}",
"MCP_TOOL_CALL_TIMEOUT": "120",
}
async def main():
async with MCPTools(command="python -m mcpgateway.wrapper", env=env) as tools:
# Print available tools for debugging
result = await tools.session.list_tools()
tools_list = result.tools # Extract the tools list from the result
print("=== ALL TOOLS ===")
for tool in tools_list:
print(f"- {tool.name}: {tool.description}")
# Create agent with all tools but instruct it to prefer security tools
agent = Agent(
model=OpenAIChat(),
tools=[tools], # Use original tools but with specific instructions
name="agno-agent",
description=f"An agent that specializes in IBM i system analysis.",
show_tool_calls=True,
debug_mode=True,
debug_level=2,
markdown=True,
)
await agent.aprint_response(
"what is my system status?", stream=False
)
if __name__ == "__main__":
import asyncio
asyncio.run(main())