How to Use the Bybit MCP in Pydantic AI

Use the Bybit MCP Server with Pydantic AI to validate every market data point before it hits your agent's logic.

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Connect Bybit MCP to Pydantic AI

Create your Vinkius account to connect Bybit to Pydantic AI and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Bybit with Pydantic AI

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Type-safe market analysis with Pydantic AI

Every response from `get_tickers` or `get_recent_trades` is validated against your Pydantic models. If the exchange returns malformed data, your agent catches it immediately. This prevents silent errors during data ingestion. Your agent logic only runs on verified, structured data structures.

Rigorous data validation for Pydantic AI

Use `get_orderbook` to retrieve market depth and map the results to strict schemas. Your agent won't hallucinate price levels because the data is checked at runtime. You'll know exactly what the market looks like before the agent makes a move. This is the standard for building reliable, production-grade agents.

Robust instrument tracking in Pydantic AI

Query `get_instruments` to populate your agent's trading list. The server's output is parsed into your defined types, ensuring total consistency across your system. Your agent maintains a clean state by relying on these validated records. It's the most reliable way to handle incoming market configurations.

Setup guide

Set up Bybit MCP in Pydantic AI

Prerequisites

Python 3.10+ installed
pydantic-ai-slim[fastmcp] package
Active Vinkius subscription with a valid endpoint token

1

Install Pydantic AI with FastMCP
Run pip install "pydantic-ai-slim[fastmcp]". The FastMCP toolset replaces the deprecated MCPServerHTTP class with full protocol support.
2

Configure the FastMCPToolset
Pass a JSON-style config dict to FastMCPToolset with your Vinkius URL. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com. Supports Streamable HTTP, SSE, and Stdio transports.
3

Create and run your agent
Pass the toolset to Agent(toolsets=[toolset]) and call agent.run(). Swap openai:gpt-4o for any supported model — Anthropic, Google, Mistral, or Groq.

agent.py

from pydantic_ai import Agent
from pydantic_ai.toolsets.fastmcp import FastMCPToolset

toolset = FastMCPToolset({
    "mcpServers": {
        "bybit-mcp": {
            "url": "https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
        }
    }
})

agent = Agent(
    "openai:gpt-4o",
    toolsets=[toolset],
    system_prompt="You have access to Bybit tools.",
)

result = await agent.run("List recent Bybit transactions")
print(result.output)

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Common questions about Bybit MCP in Pydantic AI

The framework checks the raw JSON from the server against your Pydantic schemas. If the data doesn't match your expected types, the agent fails safely.

You just add the MCPToolset to your agent's config. The server runs externally and communicates via SSE or HTTP.

Because you use Pydantic models, you get guaranteed type safety. This eliminates the risk of unexpected API changes breaking your agent's logic.

Errors are treated as validation failures. Your agent can catch these exceptions and handle them according to your custom error-handling flow.

All communication is authenticated via your Vinkius token. The server is strictly scoped to market data, ensuring your sensitive logic remains isolated.

Use it with your favorite AI tools

Connect this server to Cursor, Claude, VS Code, and more.

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