MCP server
MCP Trading Tools — MCP server setup for AI agents
Configure the SEIGYO MCP server so AI agents can evaluate trades, check session health, and enforce discipline rules as callable tools.
Who this page is for
AI developers using Model Context Protocol to build trading agents that need real-time discipline evaluation as a callable tool.
Core problem
MCP-compatible agents need tools they can call to evaluate trades. Without a discipline tool, the agent has no way to check whether a trade violates behavioral rules.
Why this matters
Why this page exists
The page should answer the exact query before asking the user to convert.
MCP is the standard protocol for AI agents to call external tools. SEIGYO's MCP server exposes discipline as a tool.
Any MCP-compatible agent (Claude, GPT, custom LLMs) can call evaluate_trade before executing an order.
The agent gets human-readable explanations of why a trade was blocked, not just a boolean.
What to do first
Start with the smallest useful workflow
A specific first step keeps the page practical and reduces decision fatigue.
Add the SEIGYO MCP server to your agent's tool configuration with your API key.
Give the agent access to evaluate_trade, check_session, get_rule_types, and interpret_verdict.
Let the agent use check_session proactively to assess whether it should keep trading.
What to measure
Look for signals that change behavior
Useful review starts with a small number of repeatable measurements.
tool call latency, blocked trades per session, and agent decision quality after warnings
Agent tool call frequency and verdict distribution
Whether the agent respects blocked verdicts without override attempts
How it helps
Where SEIGYO fits
Move from the query into a workflow users can try with demo data, CSV history, or a setup path.
Four tools cover the full discipline loop: evaluate, check, discover rules, and interpret results.
The MCP server runs locally via stdio — no additional network infrastructure required.
Works with Claude Desktop, Claude Code, and any MCP-compatible AI framework.