"How to create the most intelligent agent" matching MCP servers:

A Multi-Agent Conversation Protocol server that provides access to the New York Times Most Popular API, allowing agents to interact with NYT's most viewed, shared, and emailed content.

A dynamic service that creates and manages Model Context Protocol (MCP) servers, allowing users to spawn, customize, and control multiple MCP servers as child processes.

MCP server for qualifying and responding to inbound leads in seconds using a multi-agent AI pipeline.

Converts AI Skills (following Claude Skills format) into MCP server resources, enabling LLM applications to discover, access, and utilize self-contained skill directories through the Model Context Protocol. Provides tools to list available skills, retrieve skill details and content, and read supporting files with security protections.

MCP server for controlling satellite ground station operations in the Trench simulation, including pass management, downlink control, and antenna pointing.

A Model Context Protocol server that converts Markdown documents to plain text with flexible options and dual protocol support.

Enables LLMs to query documents using semantic search, supporting PDFs, Word, Excel, and more. Organizes documents by topics from folder structure and provides advanced search features like phrase matching and date filtering.

Enables existing Express routers to be exposed as MCP tools, dispatching tool calls through the Express middleware stack in-process without a network hop.

Auto-generates MCP tools from your OpenAPI spec, allowing natural language interaction with any API via configurable headers and serverless deployment.

A standalone proxy that transforms any OpenAPI or Swagger-described REST API into an MCP server by mapping API operations to executable MCP tools. It enables AI clients to interact with existing web services through automated HTTP requests based on their official documentation.

Turns GitHub repository history into a cited maintainer skill for coding agents, providing tools to collect evidence, query the knowledge graph, and inspect bundles.

Provides MCP tools that let an agent retrieve customer account, product usage, interaction, and support summaries, and create follow-up tasks after user approval.

Agent Ready is an AI agent readability scanner — point it at any public URL and get back a 0–100 score plus per-check remediation hints for every failing check. This package wraps the same engine that powers agent-ready.dev as an MCP server, so Claude Desktop, Claude Code, Cursor, Cline, VS Code, and Windsurf can run scans inline and explain the results.

A self-improving knowledge agent that provides local retrieval, web research, and structured answer synthesis for Claude Code and VS Code Copilot via MCP. It enables AI tools to manage a project-specific knowledge lifecycle through automated research and indexing.

Converts natural language queries into valid GraphQL queries and executes them against GraphQL APIs. Includes schema introspection, query validation, execution with authentication, and query history tracking.

Shared knowledge graph for AI coding agents. Search, create, and link verified technical knowledge across 12 node types with trust scoring, demand signals, and auto-provisioning. Install: npx agent-hive-mcp

An MCP server that enables AI agents to retrieve detailed GitHub Pull Request information using git commit hashes, branch names, or PR numbers. It automatically detects repositories and extracts comprehensive PR data including descriptions, labels, and reviews via the GitHub CLI.

One-pass agentic inbox triage as an MCP server: fetch unread Gmail → classify (action_needed/fyi/newsletter/noise) → summarize → extract tasks → draft replies as Gmail DRAFTS (never sends) → flag calendar → write a triage report. Four stdio tools (fetch_emails, save_gmail_draft, append_tasks, write_report); the host is the LLM, so it runs keyless in Claude Code. Gmail scopes: readonly + compose

Converts JSON data to TOON (Token-Oriented Object Notation) format and back, reducing token usage by 30-60% for more efficient LLM applications.

An MCP server that enables AI agents to instantly convert Markdown into beautiful, ready-to-deliver Word, PDF, HTML with sidebars, and Slideshow documents, bridging the "last mile" of AI content generation.