"Discovering and Using Alternative Map Servers" matching MCP servers:

MAP (Maraventano Agent Protocol). One MCP server with three subtractive parts — Merchant Key (read any product URL into one CleanRead), Atlas (publish your own catalog by reading yourself), Provisions (wallet curriculum), Teacher, not butler: never signs, pays, or holds keys.

Remote MCP server for geographic data. Free and x402 paid packs all normalized for cross domain joins. Start with get_catalog, then get_pack for details.

Provides a framework for running multiple MCP servers using FastAPI, stdio, and streamable-http transports, with an echo tool for testing and integration with MCP Inspector.

Provides a structured map of 120 practical AI prompts across 6 business domains, enabling users to quickly generate complete prompts for specific tasks using slash commands or tools.

A Model Context Protocol server that provides a dynamic map interface with tools to add raster/vector layers, control map view, and modify paint properties.

MCP服务器，为LLM提供高德和百度地图的地理编码、POI搜索、路径规划、天气查询等功能。

Finds the cheapest gas stations along a travel route in Korea using Kakao Navigation and Opinet APIs.

Provides location-based place recommendations in South Korea using the Kakao Map API, optimized for Korean language queries. Supports recommending various places like restaurants, shops, public facilities, and tourist attractions based on user queries.

Automatically generates mind map images from text content using Coze API workflow. Returns accessible image links that can be used in MCP-compatible tools like CodeBuddy, Cursor, and Qoder.

A workspace of six MCP servers—grounded-cv (hybrid RAG with citations), repo-intel (GitHub repo intelligence), web-research (safe web search/extraction), ats-jobs (unified ATS job boards), outcome-ledger (durable task ledger), and coding-workflows (code review & planning)—purpose-built for agentic hiring evaluations.

An experimental MCP server that explores neuroscience-inspired approaches to software development analysis, featuring associative memory, context-aware caching, and cross-language API detection.

Two self-hosted MCP servers: manage a local model machine (Ollama pull/switch, LoRA training) and bridge to local Ollama/vLLM for pure language processing tasks (writing, summarizing, classifying, extraction) without giving the calling agent tools or file access.

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

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

Enables mapping JavaScript error stack traces back to original source code, extracting context information to help developers locate and fix issues.

Provides seamless access to the Protein Data Bank in Europe (PDBe) API and search capabilities, enabling AI clients to query protein structures, perform advanced searches, and retrieve structural biology data.

Enables discovery and summarization of French education data, including school directories, geocoded establishments, IPS, Parcoursup, and exam datasets.

MCP servers for quantitative trading: live trading signals, market data, NAV history, portfolio management with dual-track (AUTO/MANUAL) performance comparison. Supports both stdio and Streamable HTTP transport.

Enables AI assistants to self-host MCP connectors for managing Meta platforms such as Facebook Pages, Instagram, Threads, Ads Manager, and Commerce, with tools for publishing, engagement, analytics, ad campaigns, and competitor research.

Enables async-first working practices by providing tools to draft decision docs, convert meetings to async artifacts, score status updates, and triage sync vs async tasks. It also offers reference tools for the Open and Async book's principles and coaching prompts.