"A server for finding quant systems" matching MCP servers:

Provides systems thinking models as composable analysis lenses for architecture, infrastructure, DevOps, incident analysis, and technical decision-making.

Provides retrieval and analysis tools for a quantitative-finance research library, enabling whole-passage answers with verifiable citations, citation checking, entity graph exploration, and corpus inspection.

Enables AI agents to perform market analysis through typed access to deterministic market data, technical indicators, backtesting, and position sizing via the Model Context Protocol.

An MCP server exposing a registry of paper-backed quantitative trading methods plus a deterministic, no-LLM decision helper for reproducible trading research.

MCP server enabling Claude Code to capture screenshots of Windows applications through WSL2, allowing AI to diagnose UI errors and verify layouts.

Enables MCP clients like Claude to query Chinese A-share market data, including K-line charts with forward/backward adjustment, limit-up and limit-down pools, per-stock fund flows, index quotes, and stock news, with automatic symbol normalization and retry handling for throttled data sources.

Provides A-share (Chinese stock market) quantitative analysis through tools for stock screening, northbound capital flow tracking, dragon-tiger list analysis, margin trading, sector analysis, technical indicators, IPO info, and limit-up/down statistics using akshare data.

Enables running quantitative finance coding tasks through MCP, where an agent writes, executes, and repairs Python code using discovered library functions and returns structured results along with saved artifacts.

Institutional-grade quantitative stock analysis and research signals for AI agents via the Model Context Protocol (MCP).

An MCP server that enables AI agents to pause and request human approval or information via Slack, Telegram, or macOS dialogs before proceeding with actions.

An MCP server for searching and downloading books from Library Genesis, supporting EPUB, MOBI, PDF, and more through natural language queries.

AI-native quantitative trading signal engine for crypto and TradFi perpetuals. Multi-factor composite BUY/SELL/HOLD signals, cross-venue funding rate arbitrage scanning, and market regime detection powered by Hyperliquid data.

Read-only MySQL MCP server that lets AI agents list tables, describe schemas, and run SELECT/SHOW/EXPLAIN queries with a row cap, bound to a single database for safety.

Provides a local MCP server for AI-powered web crawling on Windows, enabling agents to directly crawl and extract web content without requiring WSL.

Quant tools for AI agents on Kalshi & Polymarket. 34 tools, 27 free with no key: EV, Kelly sizing, Bayes updates, odds conversion, base-rate gaps, combo grading, Fed odds, NFL and NHL models, 2026 Senate race odds, Kalshi weather board and Kalshi 15-minute markets + perps (live board + liquidation estimates). Pro adds commodity + NFL edge models, mispricing scanner and alerts.

Enables coding agents to add a bounded semantic-judgment layer for routing, ranking, extraction, verification, and escalation, returning typed signals and review recommendations.

Enables agents to compute exact Uniswap v3 Q64.96 tick math, quotes, and liquidity fees, simulate MEV sandwich vulnerability, model multi-hop flashloan arbitrage profits, and project Base L2 blob gas costs. Tools are metered per call in USDC via an x402 HTTP 402 challenge settled on Base L2, so an agent can verify net profitability before executing a trade.

Enables Codex to consult Claude Code for a second opinion through a local stdio MCP server, exposing the ask_claude tool for text-only reviews and recommendations using existing Claude Code authentication. Codex can request findings and tradeoff analysis without allowing Claude to edit files or run commands.

MCP server for Quant Data, providing measured market statistics for index futures and equities, including day-type probabilities, Weis volume-price waves, options max pain, and dealer gamma exposure. Includes free keyless access and emphasizes honest reporting of model limitations.

Enables AI agents to perform local video, audio, and file operations inside an isolated workspace, including cutting/concat videos, extracting audio, transcribing, and managing files, with typed responses and background job support.