"A guide to PostgreSQL architecture and internals" matching MCP servers:

Enables a browser agent to inspect, rank, preview, evaluate, and validate transformer layer pruning proposals, while ensuring only a person can commit removals.

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

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

Enables MCP clients to interact with A2A agents through four ordinary tools, translating agent discovery, messaging, task reading, and cancellation between the A2A and MCP protocols, with support for the tasks extension.

An MCP server that turns a one-sentence idea into working, tested code using a pipeline of six AI agents, with optional deployment.

MCP server that lets you drive Claude Code sessions hands-free by voice from any MCP client, enabling remote models to send prompts, monitor progress, and get results read back.

Enables Claude to use Google Gemini as a secondary AI through MCP for large-scale codebase analysis and complex reasoning tasks. Supports both Gemini Flash and Pro models with specialized functions for general queries and comprehensive code analysis.

MCP server that routes Claude Desktop chat into Claude Code, enabling headless execution and terminal handoff with session continuity.

Converts any REST API into MCP-compatible tools instantly by providing an OpenAPI/Swagger spec, enabling seamless integration with AI agents.

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

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

Acts as a bridge between standard REST/OpenAPI web APIs and the Model Context Protocol, dynamically converting REST endpoints into MCP tools for LLM clients like Cursor, Claude Desktop, and n8n.

A Model Context Protocol (MCP) server that automates generating LinkedIn post drafts from YouTube videos. This server provides high-quality, editable content drafts based on YouTube video transcripts.

Provides a set of MCP tools (file, database, GitHub, Slack, browser, calendar, email, vector search, Python execution) with safety constraints and OpenAI integration for enterprise architecture automation.

Automatically converts OpenAPI/Swagger documents into MCP servers, enabling AI agents to call third-party REST APIs via the MCP protocol.

Acts as a proxy between a local Stdio connection and a remote Model Context Protocol server running over Server-Sent Events. It specifically enables Stdio-based MCP clients to connect to the SwiftZilla remote SSE endpoint.

Bridges Agent Communication Protocol (ACP) agents with Model Context Protocol (MCP) applications, allowing MCP clients such as Claude Desktop to discover and invoke ACP agents as tools and resources.

Enables AI agents to discover and execute tools via a secure MCP server with JWT authentication, RBAC, rate limiting, and audit logging.

Enables multi-agent design sessions with a structured workflow for defining voice, generating directions, creating UI elements, and exporting artifacts.

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