"A GitHub server implementing the Model Context Protocol (MCP)" matching MCP servers:

Enables AI assistants to interact with Square's Connect API through the Model Context Protocol standard, allowing for operations like managing customers, processing payments, and handling inventory.

Autonomous DeFi yield for AI agents on Base. Query APY rates, agent status, payment splits, and referral stats. 4 read-only tools + 1 resource.

Enables Claude to access and manage GitHub repositories dynamically at runtime, including private repos, with tools for browsing files, searching code, and viewing commits, pull requests, and issues.

Universal HTTP 402 Micropayment Protocol & Autonomous Economic Settlement Engine for AI Agents on Base L2.

An MCP server that enables AI models to retrieve information from Ragie's knowledge base through a simple 'retrieve' tool.

This server facilitates the invocation of AI models from providers like Anthropic, OpenAI, and Groq, enabling users to manage and configure large language model interactions seamlessly.

An MCP server that seats multiple LLMs as a council, letting your assistant query them in parallel or in sequence, relay answers for cross-critique, and merge conclusions within one conversation.

MCP server for managing i18n translation files — gives your AI agent full control over your app's translations without dumping entire locale files into context.

Deterministic dependency + CVE context for AI coding tools, over the Model Context Protocol. A ~0.85 MB pure-Rust MCP server.

MCP server that pings 130+ free coding LLM models across 17 providers in real-time, ranks them by latency, and helps AI agents pick the fastest available model.

Discovers local model runtimes such as Ollama, LM Studio, and LocalAI, and exposes their endpoint metadata to MCP clients like Copilot.

Trust infrastructure for the agent economy.

An MCP server that provides AI trading agents with persistent, outcome-weighted memory to learn from historical performance and detect behavioral biases. It enables agents to automatically adjust strategies and optimize position sizing based on context-aware recall of past trade outcomes.

Enables AI coding agents to offload large file reads and boilerplate code generation to cheaper or local worker models through MCP, reducing token consumption and keeping context clean.

GitHub MCP server for Claude Code, Cursor, Cline, Windsurf, and any MCP-compatible client. Exposes GitHub tools (issues, pull requests, code search, file content) to your LLM via the Model Context Protocol.

Security-enforcing MCP proxy that sits between an AI agent and any number of downstream MCP servers, intercepting every tool call through a capability-token policy gateway that can allow, deny, or escalate to human approval before the call reaches any real tool. It also exposes built-in operator tools for approval workflows, audit trail queries, token management, voice/HUD output, and hierarchical

AIFeed Open Standard. AIFeed Protocol to the building tools section. AIFeed enables web publishers to provide verified, token-efficient content feeds for AI agents.

Connects to wetlab protocol resources such as protocols.io, enabling users to access and manage experimental protocols via natural language.

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

Enables running a project's agent definitions from .github/agents/ against a model the user explicitly names, instead of inheriting whatever model the IDE session happens to use. It reads the agent file as the system prompt, executes a bounded tool loop against a configurable inference gateway, enforces a tiered model allow-list, and reports which model actually ran.