"A service for finding people by their usernames" matching MCP servers:

Provides over 1,000 creative ways to decline requests across four categories (polite, humorous, professional, and creative). The MCP server wraps a REST API to help users craft professional rejections through natural language interactions.

This project builds a read-only MCP server. For full read, write, update, delete, and action capabilities and a simplified setup, check out our free CData MCP Server for Oracle Service Cloud (beta): https://www.cdata.com/download/download.aspx?sku=KOZK-V&type=beta

A minimal Model Context Protocol (MCP) service for integration with external platforms. Provides CRUD operations, reference data fetching, and authentication capabilities.

A Model Context Protocol (MCP) service for integration with external platforms, providing CRUD operations for 23 entity types through a standardized MCP interface.

A production-ready generic FastMCP server template with SQLAlchemy async CRUD, enabling rapid bootstrapping of MCP data-management services. It provides registry-driven CRUD, FK resolution, conflict versioning, and multiple transports.

A reusable MCP HTTP server with OAuth 2.1 that turns any JSON-RPC handler into a production-ready endpoint with dynamic client registration, PKCE, refresh tokens, and OpenAPI docs.

Enables agents to read, create, and modify invitations for calendar events through a deny-by-default broker that validates OAuth bearer tokens and intersects server-owned per-subject, per-calendar grants with token scopes. Access is limited to a narrow, data-minimized calendar surface with idempotent writes and fail-closed authorization, rather than arbitrary service or network execution.

A unified HTTP/HTTPS service that exposes Model Context Protocol (MCP) functionality over HTTP endpoints, allowing clients to list available tools and call them through a standardized API.

Provides GPU-accelerated gradient boosting model training and inference through a cloud service. Enables AI agents to train models on NVIDIA A10G GPUs and get fast cached predictions with portable model artifacts.

Independent MCP service module for Poco, providing analytics and management tools such as daily usage analysis and service introspection.

An MCP (Multi-Agent Conversation Protocol) server that enables interaction with Google's Managed Service for Microsoft Active Directory through its OpenAPI, allowing users to manage identity resources through natural language.

Enables coding agents to add a bounded semantic-judgment layer for routing, ranking, extraction, verification, and escalation, returning typed signals and review recommendations.

A Model Context Protocol server that helps programmers understand code by providing explanations, tech stack analysis, and best practice suggestions through prompt templates.

A validation layer for AI coding assistants that enforces explicit LLM evaluations on plans, code diffs, and tests to ensure safer and higher-quality code.

Enables users to annotate individual sentences or selected passages of Claude's responses in an inline interface and send all their replies and questions back in a single message. Claude then answers each point in turn.

Enables generation of API and integration documentation, English/French translation, and quality linting for technical docs.

Thin Host Protocol Adapter between an MCP host and the Drama Plugin, exposing plugin tools via MCP with automatic discovery and secure routing.

Turns a codebase into a persistent knowledge graph so AI coding agents can answer structural questions about functions, call chains, routes, and cross-service links through graph queries instead of reading files one by one.

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.

An MCP server that enables Claude to execute SQL queries on MySQL databases with automatic connection management and error handling.

Enables agents to refactor source code and extract structured code summaries, plus generate interview questions and query 5G NWDAF analytics through MCP tools.

Stdio MCP server for managing recommended.by lists from agents like OpenClaw, Codex, Claude Desktop, etc. It exposes tools to create, read, update, delete lists and items via the recommended.by REST API.

Lets a coding agent hand a plain-language app idea to a hosted AI software team that shapes, designs, builds, tests and deploys it, returning a one-time link into the full build workspace. Also lists your apps with their stage, pending approvals and live addresses after a standard OAuth sign-in.

An MCP server that provides access to Google's API Discovery Service, allowing agents to discover and interact with Google APIs through natural language commands.

An MCP Server that enables interaction with Google's Service Usage API, allowing management and control of which Google Cloud Platform APIs and services are enabled for a project.

Enables Codex to consult Claude Code for a second opinion through a local stdio MCP server, exposing the ask_claude tool for text-only reviews and recommendations using existing Claude Code authentication. Codex can request findings and tradeoff analysis without allowing Claude to edit files or run commands.

Enables multiple AI agents to hand off verified work packages—such as skills, lemmas, datasets, and patches—by publishing, searching, pulling, and locally re-verifying them without sharing context.

Use Codex as a subagent inside Claude Code: async dispatch into a long-lived codex app-server, results pushed back into the Claude session automatically, steer/interrupt mid-task, and Codex's built-in code review.

Odds are, most of what you want to build is already open source. Tell your AI agent what you're making, and it finds it: which repos to use as they are, which to adapt, and what's left for you to write. Every repo it names is real, licensed for your use or flagged, and checked live.

Enables AI coding agents to discover and verify current open-source libraries and models using live GitHub activity, PyPI adoption, license checks, and hardware VRAM estimates before generating code.