KalTrader MCP
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- AlicenseNot gradedqualityCmaintenanceEnables AI agents to read Kalshi prediction market data, manage portfolios, and place or cancel trades only with explicit user approval.MIT
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- AlicenseNot gradedqualityBmaintenanceEnables AI agents to interact with Kalshi event contracts and perpetual markets via a safety-focused MCP interface, with paper trading by default, strict schemas, and fail-closed behavior.Apache 2.0
- AlicenseNot gradedqualityDmaintenanceEnables AI assistants like Claude to run backtests, fetch market data, list strategies, and analyze trading algorithms via natural language.1,068GPL 3.0
- AlicenseNot gradedqualityCmaintenanceMCP server that exposes Kalshi prediction markets as tools for AI agents, enabling conversational trading with safety features like demo mode, preview-before-place, and hard caps.MIT
- AlicenseNot gradedqualityCmaintenanceEnables natural language trading operations through AI assistants, supporting stocks, options, crypto, portfolio management, and real-time market data.MIT
TDQS
Scored across 60 tools
Each tool has a clearly distinct resource+action combination. The GET endpoints are differentiated by resource type (markets, events, series, orders, etc.), and write operations (create, amend, cancel, decrease, transfer) are scoped to specific resources. The paper trading tools are explicitly marked as simulated, and the meta tools (list/describe/call endpoint) serve a unique discovery purpose, so there is no meaningful ambiguity.
The majority of tools follow a consistent get_* or verb_noun pattern (e.g., kalshi_get_market, kalshi_create_order_v2). However, there are minor deviations: 'kalshi_paper_order' and 'kalshi_paper_portfolio' lack a verb prefix, 'kalshi_stream_collect' reverses the verb, and 'kalshi_intra_exchange_instance_transfer' is a noun phrase. These are few relative to the total and do not significantly impede readability.
With 60 tools, this server far exceeds the well-scoped threshold. Many endpoints could be served by the generic kalshi_call_endpoint or consolidated into parameterized tools. The count is an extreme mismatch for typical tool-set expectations and likely overwhelms an agent.
The tool surface is exceptionally complete for the Kalshi trading API, covering market data, order management (create, amend, cancel, decrease, batch), portfolio (balance, positions, fills, settlements), subaccounts, and paper trading. The generic kalshi_call_endpoint ensures that even endpoints without dedicated tools are accessible, leaving no obvious gaps.