Quickstart

This sections showcases a few ways to get started using our remote MCP server.

The Katoshi MCP server is currently in Beta - Please report any issues or feedback in our Telegram Group

---

Connection Types

Katoshi's MCP server is available via stream for persistent connexion for high-volume data flow.

https://server.katoshi.ai/x2/mcp/A17mXBLw/mcp/stream

---

Authentication

Authentication is required to connect to the MCP server. 2 auth options are available:

1) API Key in URL

• Pass your Katoshi API Key directly in the URL

https://server.katoshi.ai/x2/mcp/A17mXBLw/KATOSHI_API_KEY/stream

2) Bearer Token

• Pass your Katoshi API Key in headers as a bearer token

https://server.katoshi.ai/x2/mcp/A17mXBLw/mcp/stream

"Authorization": "Bearer KATOSHI_API_KEY"

---

The new MCP server below is experimental and still in BETA, use at your own risk. For better reliability use the one above. More updates coming soon.

MCP Endpoint

Katoshi's MCP server is available via stream for persistent connexion for high-volume data flow.

• Pass your USER_ID in the id query parameter

https://mcp.katoshi.ai?id=USER_ID

You can find your MCP endpoint and user id in the app's settings page.

---

Authentication

Authentication is required to connect to the MCP server. We provide 2 ways to auth:

1) Bearer Token

• Pass your Katoshi API Key in headers as a bearer token

"Authorization": "Bearer KATOSHI_API_KEY"

2) URL Query Parameter

• Pass your Katoshi API Key to the api_key query parameter

https://mcp.katoshi.ai?id=USER_ID&api_key=API_KEY

---

Client Integrations

Katoshi

The easiest way to use our MCP is by creating an AI Agent directly in the Katoshi app.

• Our native AI agents are already connected to our MCP and have even more tools that allows agents to read charts, run technical analysis, and more.

• Katoshi Agents are also API-ready out-of-the-box, so you can send commands to your agents via simple POST requests. See the Agent API section for more info.

Continue reading below if you prefer to use and setup your own Agentic framework or AI tools

Cursor

Clients like Cursor will require you to add MCP servers in the mcp.json file.

{
  "mcpServers": {
    "katoshi": {
      "command": "npx",
      "args": [
        "mcp-remote",
        "https://mcp.katoshi.ai?id=USER_ID&api_key=API_KEY"
      ]
    }
  }
}

• Replace USER_ID with your user id and API_KEY with your Katoshi API Key

The mcp-remote package requires Node.js 22 or higher.

Agentic Frameworks

Agentic frameworks like LangChain, CrewAI, AutoGen, Agno, while slightly different will connect to MCP tools in a similar way. Here's a simple example using the Agno framework that will create a fully functional Agent with memory and full trading capacity due to our MCP tools:

import os
from dotenv import load_dotenv
from agno.agent import Agent
from agno.db.sqlite import SqliteDb
from agno.models.openrouter import OpenRouter
from agno.os import AgentOS
from agno.tools.mcp import MCPTools, StreamableHTTPClientParams

# Load environment variables from .env file
load_dotenv()

# ************* Create Agent *************
# See: https://docs.agno.com/concepts/tools/mcp/overview
agno_agent = Agent(
    name="Agno Agent",
    model=OpenRouter(id="anthropic/claude-3.5-sonnet"),
    db=SqliteDb(db_file="agno.db"),
    enable_agentic_memory=True,
    tools=[
        MCPTools(
            transport="streamable-http",
            server_params=StreamableHTTPClientParams(
                url=f"https://mcp.katoshi.ai/?id={os.getenv('USER_ID', '')}",
                headers={
                    "Authorization": f"Bearer {os.getenv('KATOSHI_API_KEY', '')}"
                },
            ),
        )
    ],
    add_history_to_context=True,
    markdown=True,
)

# ************* Create AgentOS *************
agent_os = AgentOS(agents=[agno_agent])
app = agent_os.get_app()

# ************* Run AgentOS *************
if __name__ == "__main__":
    agent_os.serve(app="agno_agent:app", reload=False)

n8n Integration

You can connect the Katoshi MCP to n8n agents using this tutorial:

n8n