"Understanding Crypto Execution in Financial Markets" matching MCP servers:

A minimal MCP server that exposes Gemini's web and multimodal understanding (video, audio, document, image) through five dedicated tools.

Enables AI agents to interact with the Execute.run bot API for managing Shell balances, transferring funds, and executing LLM requests. It provides tools for identity verification, transaction tracking, and performing compute tasks through the Execute.run platform.

MCP server for multimodal understanding and object grounding (bounding boxes) across images, videos, and documents, with support for multiple AI providers (Zhipu GLM-V, OpenAI GPT-4o, Anthropic Claude, or any OpenAI-compatible endpoint).

Enables AI agents to maintain persistent, inspectable understanding through typed, revisable updates, and to coordinate multi-agent work via shared graph-based stigmergy.

Saves the user's exact words as immutable, SHA-256-hashed captures before anything else, then derives events, entities, context cards, and causal hypotheses — every fact traceable to its verbatim source. Local-first personal memory for Claude Code, Codex, and any MCP client.

An MCP server that helps AI coordinate sequential tool calls and maintain a comprehensive journal of execution workflows, decisions, and actions.

Enables querying New York Fed markets data—repo and reverse repo auctions, securities lending, SOMA holdings, reference rates, and primary dealer statistics—through MCP tools without an API key.

Provides AI agents with real-time prediction market odds from Polymarket and Kalshi, enabling them to browse active markets, retrieve detailed probabilities and trading data, and discover trending markets via x402 micropayments.

A zero-dependency Node.js playground for debugging how MCP clients authenticate to an MCP server over HTTP.

Enables AI agents to retrieve live Hong Kong monetary data (HKMA Base Rate, HIBOR fixings, USD/HKD peg band) via typed tools, no API key needed.

Provides search, trending, odds, arbitrage, and category browsing for prediction markets (Polymarket & Kalshi) via the Model Context Protocol, enabling AI agents to access live market data without API keys.

An MCP server exposing Indian market and regulatory data from official sources (NSE, NIFTY, AMFI, SEBI), providing tools for end-of-day quotes, index constituents, mutual fund NAVs, and SEBI order searches with a focus on primary sources and no fabricated data.

Enables local video inspection and offline transcription with timestamped JSON and Markdown output, enforced filesystem boundaries, and reproducible content-addressed caching.

Enables AI agents and MCP clients to look up Indian equities, retrieve transparent technical signals and trend regimes, and compare symbols using public Yahoo Finance data without API keys.

Verifies AI agent completion claims by checking that claimed output files exist and are fresh, acting as a lightweight physical telemetry gate.

An MCP server that analyzes local or remote GitHub repositories, providing intelligent code context and structure to AI coding assistants.

Bridges matched Kalshi and Polymarket prediction-market data to AI agents via MCP, enabling market lookup, cross-venue spread analysis, and arbitrage detection.

Enables MCP-aware agents to initiate M-Pesa B2C/B2B payouts, query transaction status, validate phone numbers, and reconcile M-Pesa statements against ledger CSVs to surface discrepancies, plus structured lookups for county public data and KRA tax helpers. It runs in sandbox mode by default, uses idempotency keys for safe retries, and stays read-only for reconciliation and lookups.

Records all MCP tool interactions in a centralized ledger, enabling developers to trace, replay, inspect, and audit AI agent workflows.

A queue-based execution server that monitors a command queue and executes shell commands or Python scripts, moving completed or failed jobs to respective directories.