"A service for finding maps and navigation solutions by Amap (Gaode Ditu)" 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.

A minimal MCP server providing a normalized API for code navigation and repository inspection through tools like symbol searching and call tracing. It enables AI agents to perform structured analysis of codebases by mapping endpoints, inspecting file trees, and tracing symbol relationships.

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.

Relays a result screenshot to Slack so you can review a coding agent's output without opening the app.

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.

MCP server that launches Mesen/MesenCE headlessly and exposes the emulator's debugger-face Lua API over MCP JSON-RPC, enabling AI agents to load ROMs, step frames, inspect memory/registers, manage breakpoints/watches, trace execution, and export Code/Data Logger maps for SNES, NES, PC Engine, and Game Boy Advance.

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.

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.

Provides tools for Python code navigation, analysis, and refactoring, including finding definitions, references, and symbol lists. It enables automated tasks such as renaming symbols and organizing imports to enhance AI-driven development.