"A server for TradingView - the financial charting and trading platform" matching MCP servers:

Provides a comprehensive suite of 20 tools for cryptocurrency trading and technical analysis across 100+ exchanges like Binance and MEXC via CCXT. It enables users to execute orders, track positions, and scan for market opportunities through Claude Desktop using natural language.

A type-safe MCP server that enables AI agents to control TradingView Desktop via Chrome DevTools Protocol, allowing chart state reading, symbol/timeframe changes, and OHLCV data fetching.

MCP server for The Commons (jointhecommons.space), a persistent, noncommercial space where AI voices from different models post and reply to each other with persistent identities. 48 tools; reading needs no token, writing uses a facilitator-issued token.

Enables structured learning with a verified loop: define goals as observable claims, learn through teach-lab-test-gate per claim, and get independently graded by an adversarial examiner to ensure genuine progress.

Enables AI assistants to interact with IG Trading API for forex, indices, and commodities trading. Provides 21 tools for account management, position trading, order placement, market data analysis, and watchlist management.

Perpetual futures trading API for AI agents. Access 275+ markets (crypto, stocks, commodities, forex) via Hyperliquid. Copy trading, leaderboard, up to 50x leverage. No KYC. 20% referral commissions.

Enables agent-native collaboration network for long-running agents and MCP clients with shared context, tasks, and interactive MCP App widgets.

Enables LLM clients to access A-share market data, run the trading rule engine, and retrieve daily decision reports through 32 MCP tools.

Enables Claude to monitor and execute Binance trading strategies through a bounded MCP tool interface, with risk controls and audit logging.

Enables building and evaluating LangGraph agents over a protocol-level MCP server to measure failure rates across four agent topologies.

Bridges Hermes Agent to the Hermes Intelligence Platform API, enabling tools to read/write learning loop data (context, feedback, signals, memory, etc.) via stdio.

Score your agent's governance (0-100), lint MCP tool definitions, and estimate costs across all major models. Free diagnostic tools with no API key needed. Expert skill files on governance, economics, and system architecture available with free tier.

Transforms AI assistants into autonomous crypto trading agents with real-time market analysis, portfolio management, and trade execution across 17+ blockchains.

An intelligent agent that responds to financial queries about TreePod Glamping directly within Claude Desktop using MCP protocol, providing tools for tariff calculation, occupancy checking, financial analysis, and business reporting.

Enables multi-agent financial research through MCP, combining live or offline market, news, fundamentals, document RAG, and risk tools with critic review, synthesis, and execution tracing.

MCP server for the Sayba AI agent social platform, enabling agents to register, browse, interact, manage goals, trade skills, and exchange items via natural language.

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.

Enables an agent to run a single planning request past seats drawn from multiple AI labs, which ask clarifying questions, propose independently, debate each other's anonymised proposals, and panel-review a draft against yes/no acceptance criteria until it passes or hits the round cap. Each run writes a local folder with the deliverable, the full debate board, a handoff document, per-lab scores, and real token/cost accounting, all driven with your own API keys.

A-MEM is a self-evolving memory system for coding agents that automatically organizes knowledge into a Zettelkasten-style graph with dynamic relationships, enabling semantic and structural search.

Provides a hand-written MCP server integrated with a LangGraph agent to benchmark multiple agent topologies and measure their failure rates.