alpha-forge-mcp
OfficialRelated Servers
Alternatives to alpha-forge-mcp
No user-submitted related servers found.
Related Servers
- AlicenseAqualityCmaintenanceMCP server for the Pyon trading platform that lets AI agents search markets, generate research, build and edit node-graph strategies, run backtests, diagnose problems, and optimize parameters with 2-D sweeps.1310 npm4MIT
- AlicenseNot gradedqualityDmaintenanceMCP server that provides AI agents with financial tools including real-time quotes, backtesting, technical analysis, and multi-exchange data via a simple CLI interface.1MIT
- FlicenseNot gradedqualityDmaintenanceEnables quant research, strategy generation, backtesting, and paper trading from natural language prompts, integrating with AI agents via an MCP server.63-
- AlicenseBqualityAmaintenanceMCP server that lets AI agents directly control and interact with the TradingView desktop app via 88 chart-control tools, enabling automated chart reading, Pine Script compilation, strategy optimization, and replay control.113332 npm41MIT
- AlicenseNot gradedqualityBmaintenanceLocal-first MCP server for building and running reproducible Backtrader strategies offline, with tools to inspect datasets, manage drafts, and execute backtests via controlled subprocess runs. It supports multiple hosts including Claude, Codex, OpenCode, and OpenClaw through stdio.1MIT

flox-mcpofficial
AlicenseAqualityAmaintenanceMCP server for the FLOX trading framework. About 30 tools to run backtests, scaffold strategies, validate for lookahead bias, compute indicators, place orders, and query PnL from Claude/Cursor.38224MIT
TDQS
Scored across 17 tools
Most tools have distinct purposes. run_optimize and run_walk_forward both optimize but are differentiated by description (single vs. walk-forward). get_result, get_strategy, and get_journal serve different retrieval needs. Minor overlap but clear descriptions guide selection.
Tools predominantly follow verb_noun pattern with underscores (e.g., run_backtest, get_strategy). One tool, exploration_status, uses noun_noun, breaking the pattern slightly. Overall consistent and readable.
17 tools are well-scoped for a quantitative backtesting platform, covering data fetching, strategy management, backtesting, optimization, Monte Carlo, walk-forward, and results. Each tool has a clear role without bloat.
The tool surface covers the full lifecycle from data fetch to strategy registration, backtesting, optimization, and result analysis. Minor gaps like missing delete/update tools for strategies or results, but core workflows are intact.