"A quantitative trading system" matching MCP servers:

Provides real-time stock data, technical indicators, and market analysis via MCP protocol to enable AI-driven quantitative trading.

AI-powered cryptocurrency trading assistant for OKX exchange, featuring a multi-agent analysis system, real-time market data, and autonomous trading capabilities.

Helps founders and teams review business workflows, identify AI opportunities, assess trust/control risks, and recommend a safe first AI-human workflow.

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

Provides a safe trading toolkit for AI agents with market data, indicators, paper trading, and guarded broker integration.

MCP server offering 252 AI skills as 12 MCP tools for tasks like MBTI analysis, contract review, and quantitative trading.

Enables self-hosted AI gateway and agent control plane with governed MCP tools, virtual-key budgets, caching, and audit, supporting OpenAI, Anthropic, Gemini, MCP, and A2A protocols. It provides deterministic prompt enhancement and governed execution with a zero-credential first run.

Provides AI agents with tools for paper trading stocks, options, ETFs, and bonds, including advanced options strategies and risk analysis, using real market data without financial risk.

MCP server for hybrid medical consultation integrating Western and Traditional Chinese Medicine, enabling symptom analysis, diagnosis, and treatment suggestions through two specialized models.

A local, fully vectorized computational engine for stock market analysis that enables AI to perform factor calculation, strategy backtesting, IC analysis, and GPU-based multi-dimensional visualization using local DuckDB data.

Multi-agent system for long-term fund investment decision support, integrating analysis, risk control, and MCP tools to assist with fund trading decisions.

Enables MCP-capable AI clients to read and write structured, project-scoped memory through a Cloudflare Worker backed by D1 and R2.

Dynamic multi-agent debate MCP server for structured argumentation and reasoning among AI agents.

Provides AI assistants with real-time web search, reasoning, and research capabilities through Perplexity's Agent API and Search API, enabling tools for search, conversational Q&A, deep research, and advanced reasoning.

Provides local, deterministic scoring and detailed auditing of text for AI-writing patterns via two read-only tools, with no network calls or language models.

Enables AI agents to access Cloudflare Workers AI for serverless LLM chat completions, text embeddings, and image generation via MCP tools.

Enables agents to make calibrated decisions via six MCP tools for classification, relevance ranking, claim verification, action gating, next-step control, and model listing, using Jev's System One model without generating text.

Provides tools to retrieve the GodPrompt universal system prompt and its components (core skill, protocols, gates, anti-patterns) for AI software development, plus task classification. Designed for progressive context usage.

Predicts the outcome of Dutch court cases dismissed, partly granted, or granted using a model trained on 609,715 rulings, with the outcome leakage measured and removed: 92% of Dutch judgment texts state the outcome verbatim, 0.1% remains after the cut, giving 78.2% accuracy against a 43.7% majority baseline. The lekkage_check tool exposes that same measurement so anyone can test a datase

Seven-layer agent memory over MCP. zenbrain_store routes each memory itself: steps to a procedure, emotional weight to an episode, high confidence to a pinned core memory, the rest to a semantic fact. zenbrain_recall returns each result with its id and layer; zenbrain_forget deletes one memory by both; zenbrain_consolidate runs one sleep-like pass. Local SQLite file, no account, no network call.