MCP Tools | Model Context Protocol Server Directory

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The GetBirthChart MCP server exposes the GetBirthChart API to any MCP-compatible client, letting you compute whole-natal charts, planetary positions, Big Three, Moon/Rising signs, aspects, and synastry reports on demand. It's useful for astrological web apps, research notebooks, or CLI tools that need structured astrological data without hosting ephemeris math yourself. After adding the server (npm install @getbirthchart/mcp or clone the GitHub repo) and configuring it in your MCP client, you call the exposed tools with birth data (date, time, location) and receive JSON results ready for rendering or analysis. Compared to building the calculations from scratch, this saves weeks of astronomy and astrological programming while staying current with the underlying service's updates.

Trooth Network introduces a specialized MCP server designed to bridge the gap between AI reasoning and real-world corporate accountability. For developers building agentic workflows or research-heavy applications, this tool provides a standardized way to query a live, read-only repository of company trust metrics. Instead of relying on outdated training data or hallucinations regarding corporate ethics, your LLM can pull verified, timestamped data on identity verification, security protocols, privacy policies, and AI governance. Because it operates as a no-auth MCP server, integration is frictionless: you simply plug it into your existing IDE or agent environment to enable real-time fact-checking. Unlike general search tools that return noisy web results, Trooth delivers structured, source-backed insights specifically curated for risk assessment and due diligence. It transforms your AI from a creative assistant into a tool capable of performing objective third-party audits during complex decision-making processes.

The blooketsimulator-mcp server provides a specialized interface for interacting with Blooket Simulator mechanics through the Model Context Protocol. For developers building gaming assistants or data-driven simulation tools, this MCP server bridges the gap between LLM reasoning and real-time game state data. Instead of manually parsing game outputs, you can integrate this tool to allow your AI agent to programmatically simulate unboxing sequences, audit drop rate probabilities, and query specific item metadata. It is particularly useful for developers creating automated testing environments or statistical analysis bots. Unlike standard web scrapers, this implementation follows the MCP standard, making it easy to plug into existing IDE-based AI agents or custom orchestration layers. It shifts the workflow from manual simulation to intent-based querying, where the AI handles the complexity of the simulator's internal logic.

The Wu Wei Cards MCP Server provides a specialized interface for integrating workshop facilitation tools directly into your AI-driven development or planning workflows. Instead of manually managing deck selections or workshop logic, this server allows LLMs to programmatically access Wu Wei card sets to drive structured brainstorming, creative problem-solving, or team-building exercises. For developers, this means you can build autonomous agents capable of facilitating complex human-centric workshops or integrate meditative, non-striving principles into interactive training modules. Unlike generic prompt-based card games, this MCP implementation offers a standardized way to fetch, interpret, and apply specific card contexts within an agentic framework. It is particularly useful for teams building collaborative AI tools where structured spontaneity is required to break cognitive biases or spark new design directions.

WaveMaster AI is an MCP server that delivers real-time surf forecasts through the Model Context Protocol. It pulls current conditions, weekly rankings, and optimal session times for surf spots worldwide, so you can integrate surf data directly into your AI workflows or applications. Since it follows the MCP standard, you can use it with any MCP-compatible client (like Claude Desktop, custom agents, or development tools) without building a separate API integration layer. The server exposes structured endpoints for spot conditions, day-of-week rankings, and global spot discovery, making it easy to chain surf data with other tools or logic in your own code. For developers building travel apps, surf communities, or just curious about how to enrich AI conversations with live environmental data, this is a practical example of bridging niche APIs with the extensibility MCP enables. It’s community-maintained and available on GitHub, so contributions and feedback are welcome.

LVL LTD Skill Market is a decentralized marketplace for AI agent skills built on the x402 protocol. Developers can publish, discover, and integrate reusable agent capabilities as sealed skill packs priced in USDC on Base. Each transaction is recorded on a public proof ledger, giving buyers verifiable usage rights and creators transparent monetization. The platform exposes a Model Context Protocol (MCP) and Agent-to-Agent (A2A) interface, so skills can be wired directly into existing agent frameworks without custom glue code. Instead of building every tool from scratch, you grab a skill that fits, pay per use, and compose more capable agents faster. Think of it as a package registry but for live, billable AI functions with cryptographic proof of execution. Integration is straightforward: import the MCP client, query the ledger for available skills, and call them like local functions. It competes with centralized API marketplaces by removing platform take-rates and giving you on-chain ownership of your skill IP. If you're building autonomous agents and tired of rebuilding common utilities, this lets you focus on novel logic while still getting paid when others reuse your work.

HireMe MCP bridges the gap between autonomous AI agents and human professional services by providing a standardized interface for talent acquisition. Unlike traditional job boards designed for human browsing, this MCP server allows LLM-based agents to programmatically query a real engineer's technical profile, review shipped product repositories, and evaluate pricing structures. For developers building agentic workflows, this tool enables a seamless transition from 'planning' to 'execution' by letting agents outsource complex tasks to verified human experts. Instead of a developer manually copy-pasting briefs, an agent can use HireMe to submit project requirements and negotiate terms directly through the protocol. It effectively treats human expertise as a discoverable, callable resource within an agent's toolset, turning the concept of 'AI hiring humans' into a functional technical implementation.

The Wildberries MCP Server exposes the full Wildberries Seller API through the Model Context Protocol, giving agents direct access to 202 endpoints across product management, pricing, orders, supplies, advertising, reviews, finance, and analytics. Instead of juggling multiple REST calls or building a custom wrapper, developers can integrate once via MCP and let their agents query or update seller data conversationally. It supports multi-account workflows, so you can manage several Wildberries seller accounts from a single session, which is useful for agencies or large merchants. The server is community-maintained, written for easy deployment alongside existing MCP hosts, and maps cleanly onto Wildberries' official API structure without hiding the underlying semantics. Compared to hitting the REST API directly, you trade a bit of raw control for simpler authentication handling, automatic schema discovery, and reusable tool calls that agents can chain together. It's most valuable when you're building agentic workflows like auto-repricing based on analytics, order-to-supply automation, or review monitoring, where reducing boilerplate and keeping context in conversation matters more than micro-optimizing HTTP requests.

The Ozon MCP Server connects your development environment directly to Ozon's Seller and Performance APIs through 151 purpose-built tools. It's designed for developers managing multiple Ozon seller accounts programmatically, offering streamlined access to pricing, promotions, advertising, orders, returns, finance, and analytics data without wrestling with API authentication and pagination. Instead of building custom integrations for each endpoint, you can query or update information using natural language prompts within your existing MCP-compatible client. This is particularly useful for automating repricing strategies, syncing inventory across accounts, pulling performance reports, or building dashboards that aggregate data from multiple Ozon entities. Compared to direct API integration, it reduces boilerplate code and handles request throttling automatically. The server acts as a middleware layer, so you get consistent JSON responses and can chain operations easily. Since it's community-maintained, it evolves with Ozon's API changes, and being open-source means you can inspect or extend the toolset as needed. It's not a replacement for the official API but a practical abstraction for developers who want results over setup.