"A tool or guide for creating a memory card game" matching MCP servers:

Enables AI coding agents to request a second opinion from a different frontier model via a single tool call, with PII scrubbed before transit, live web search, and support for Claude, ChatGPT, Cursor, and Gemini.

Enables AI agents to request an independent second opinion from a different frontier model, with PII scrubbing before transit, live web search grounding, caching, and multi-provider failover.

Enables AI agents to control a Playwright-driven browser through natural-language instructions, including page interaction and live browser task execution.

Production-ready MCP server providing RAG, hierarchical memory, and 8+ tools for AI agents via the Model Context Protocol.

Starter kit for small businesses: A2A agent card, MCP server card, minimal example MCP server (tools: leistungen, anfrage_anlegen) and validator. Python standard library only, MIT, docs in English and German.

Lets AI agents register, post job specs to matching specialist bots, authorize PayPal escrow funds, and capture payment only for units that pass acceptance checks. Covers the full job lifecycle — bidding, hashed contracts, funding, delivery verification, payouts, dispute mediation and long-polled events.

MCP router that fronts your other MCP servers behind a few small generic tools, so their tool definitions stay out of the context window and are discovered on demand.

Graph-based tool retrieval for LLM agents. Builds a tool graph from OpenAPI/MCP specs and retrieves multi-step workflows via hybrid search (BM25 + graph traversal + embedding), recovering accuracy from 12% to 82% with 79% fewer tokens. Also works as an MCP Proxy to aggregate multiple servers behind 3 meta-tools.

Enables centralized proxy and orchestration of MCP servers, providing unified tool discovery, authentication, and secure request routing. It adds a human-in-the-loop approval gate for high-risk actions and audit logging.

Enables creation and management of structured game worlds for text adventures and RPGs with character creation, world generation, and natural language interaction through AI integration.

MCP server that routes natural language requests to structured tool calls using a LoRA-tuned small language model, with built-in validation, retry, and fallback recovery.

Enables agents to send only the handful of tool definitions relevant to each question, ranking a large catalog by keywords and optional embeddings to cut context cost and wrong-tool picks. It can also run in front of any mcpServers config as a proxy that exposes just search_tools and call_tool instead of the whole catalog.

Orchestrates AI agents through structured markdown documents, enabling multi-agent workflows with automatic context injection and workflow management.

A configurable MCP gateway that runs multiple Streamable HTTP MCP servers and exposes all their tools through a single endpoint, enabling tool aggregation and routing for MCP clients.

A framework for building hot-loadable MCP tools that feature conversational negotiation, graduated permissions, and zero-downtime updates. It enables persistent state continuity across server restarts and provides a hypothetical evaluation system for tool actions.

Discover and connect your agents with other agents via A2A protocol. Share resources for free or fee.

An MCP proxy that embeds tool definitions and returns only the top-k semantically relevant tools per query, reducing context usage and routing calls to upstream MCP servers.

Enables agents to accomplish multi-step work by writing a single sandboxed JavaScript program that drives shell, filesystem, HTTP, and every tool of any configured MCP server, returning only a small summary instead of raw JSON. This collapses dozens of advertised tool schemas into one tool, cutting per-request context by roughly 26× while keeping disabled upstream servers reachable.

Enables coding agents to consult other coding-agent CLIs for independent opinions on proposals, receiving per-agent responses that can be verified and recorded without sharing conversation history.

Central registry for AI tools with vector search and knowledge graph, enabling intelligent tool discovery, chaining, and execution via MCP.

A single MCP server that provides dynamic access to thousands of APIs through discovery and proxy, eliminating the need to install and configure multiple separate MCP servers.

An advanced contextual memory server for agent orchestration providing chronological history, semantic vector search via Redis Stack, and temporary scratchpad storage. It also enables context compression through history rollups and facilitates inter-agent communication using a Redis-based Pub/Sub system.

Enables ZCode to control a real Chrome browser, including tabs, navigation, page content, clicks, form filling, keyboard input, scrolling, screenshots, and JavaScript evaluation through a local MCP bridge.

Wraps a dependency-free memory lifecycle engine as six read-only MCP tools, letting any agent extract facts with pure regex, score signals, compute Ebbinghaus decay and archival judgments, and simulate a full five-stage dream cycle for long-term memory growth. Runs over stdio or streamable HTTP with no API key, storing no caller data.

Enables declaring a catalog of tools for LLMs, filtering them by role, validating arguments, guarding sensitive calls with server-side confirmations, and recording an audit log.

Publishes AAIF Agent Cards and bridges A2A and OASF to AAIF, with built-in EU AI Act compliance.

Enables OpenAI-compatible clients to access external tools, APIs, repositories, and data sources through MCP with allowlisting, approval, and argument validation, deployable as a FastAPI service or Python library.

A shared memory and coordination server for multiple AI coding agents, built on the Model Context Protocol (MCP).

Routes external MCP tools behind a small on-demand discovery interface for Codex agents, using Jev to select relevant tools and providing fallback to the full inventory when confidence is low.

Enables locally configured MCP servers to be called over stdio and mixed with xAI server-side tools, without relying on hosted xAI MCP.