Discover Awesome MCP Servers

Travel City Planner MCP

Converts natural language travel requests into customizable multi-city itineraries, with tools for planning, editing, and exporting trips across 69 global destinations.

MCP Link - Convert Any OpenAPI V3 API to MCP Server

Okay, I can help you understand how to convert an OpenAPI V3 API definition to an MCP (presumably referring to a **Microservice Control Plane**) server. However, the process isn't a direct, one-step conversion. It involves several steps and considerations. Here's a breakdown of the general approach and key concepts: **Understanding the Goal** * **OpenAPI V3:** This describes your API's structure, endpoints, data models, authentication, etc. It's a *specification*. * **MCP (Microservice Control Plane):** This is an infrastructure layer that manages and orchestrates your microservices. It typically handles things like: * Service discovery * Traffic management (routing, load balancing) * Security (authentication, authorization) * Observability (metrics, logging, tracing) * Deployment and scaling The goal is to use the OpenAPI definition to *configure* your MCP to properly handle requests to your API. You're not "converting" the OpenAPI file into an MCP server itself. You're using it as a blueprint to tell the MCP how to manage your API. **General Steps** 1. **Choose an MCP:** The first step is to select a Microservice Control Plane. Popular options include: * **Istio:** A very popular and powerful open-source service mesh. * **Linkerd:** Another open-source service mesh, known for its simplicity. * **Kong:** An API gateway and service mesh. * **Envoy:** A high-performance proxy often used as a building block for service meshes. * **Commercial Solutions:** Many cloud providers (AWS, Azure, GCP) offer managed service mesh or API gateway solutions. The choice depends on your requirements (scale, complexity, existing infrastructure, budget, etc.). 2. **Deploy Your API (Microservice):** You need to have your actual API implementation running as a microservice. This is the code that handles the requests defined in your OpenAPI specification. This microservice needs to be deployed in an environment that the MCP can manage (e.g., Kubernetes). 3. **Configure the MCP using the OpenAPI Definition:** This is the core of the process. You'll use the OpenAPI definition to configure the MCP to: * **Route traffic:** Tell the MCP how to route incoming requests to the correct microservice based on the URL path, HTTP method, and other criteria defined in the OpenAPI spec. * **Apply security policies:** Configure authentication and authorization based on the security schemes defined in the OpenAPI spec (e.g., API keys, OAuth 2.0, JWT). * **Implement rate limiting:** Set limits on the number of requests allowed per client or API endpoint. * **Transform requests/responses (if needed):** The MCP can sometimes be used to transform requests or responses to match the expected format. * **Enable observability:** Configure the MCP to collect metrics, logs, and traces for your API. 4. **Specific MCP Configuration Methods:** The exact way you configure the MCP depends on the chosen MCP. Here are some common approaches: * **Istio:** * **Virtual Services:** Define how traffic is routed to your microservices. You can use the OpenAPI spec to help define the routing rules. * **Gateway:** Configures the entry point for external traffic into your service mesh. * **AuthorizationPolicy:** Defines access control rules. * **RequestAuthentication:** Configures how to authenticate requests. * **Istio API Definitions:** Istio has its own API definitions (CRDs - Custom Resource Definitions) that you use to configure its behavior. You'll need to translate the information from your OpenAPI spec into these Istio API definitions. * **Kong:** * **Plugins:** Kong uses plugins to add functionality like authentication, rate limiting, and request transformation. You can configure these plugins using the Kong Admin API or declarative configuration files. The OpenAPI spec can guide you in configuring these plugins. * **Services and Routes:** Define the upstream services and the routes that map to them. * **Other MCPs:** Each MCP will have its own configuration mechanisms. Consult the documentation for your chosen MCP. **Example (Conceptual - Istio)** Let's say your OpenAPI spec defines an endpoint: ```yaml paths: /users/{userId}: get: summary: Get a user by ID parameters: - name: userId in: path required: true schema: type: integer responses: '200': description: Successful operation content: application/json: schema: type: object properties: id: type: integer name: type: string ``` In Istio, you might create a `VirtualService` like this (simplified): ```yaml apiVersion: networking.istio.io/v1alpha3 kind: VirtualService metadata: name: user-service spec: hosts: - "user-service.example.com" # Or the hostname of your service gateways: - my-gateway http: - match: - uri: prefix: /users/ route: - destination: host: user-service # The Kubernetes service name of your microservice port: number: 8080 # The port your microservice is listening on ``` This `VirtualService` tells Istio to route any requests to `/users/*` to the `user-service` microservice. You would then configure other Istio resources (e.g., `AuthorizationPolicy`) to handle authentication and authorization for this endpoint, based on the security schemes defined in your OpenAPI spec. **Tools and Automation** * **OpenAPI to MCP Configuration Generators:** Some tools can help automate the process of generating MCP configuration from OpenAPI definitions. These tools are often specific to a particular MCP. Search for tools like "OpenAPI to Istio configuration generator" or "OpenAPI to Kong configuration generator." * **Scripting:** You can write scripts (e.g., using Python and the Istio or Kong API) to programmatically generate the MCP configuration based on your OpenAPI spec. * **Configuration Management Tools:** Tools like Terraform or Ansible can be used to manage the deployment and configuration of your MCP. **Important Considerations** * **Complexity:** Configuring an MCP can be complex, especially for large and complex APIs. * **Security:** Pay close attention to security when configuring your MCP. Make sure you properly authenticate and authorize requests. * **Testing:** Thoroughly test your API after configuring the MCP to ensure that everything is working as expected. * **Evolution:** As your API evolves, you'll need to update your OpenAPI definition and reconfigure your MCP. **In summary, there's no single "convert" button. You need to:** 1. **Choose an MCP.** 2. **Deploy your API as a microservice.** 3. **Use your OpenAPI definition as a blueprint to configure the MCP to manage traffic, security, and observability for your API.** 4. **Use tools and scripting to automate the configuration process where possible.** To give you more specific guidance, please tell me: * **Which MCP are you using (or considering)?** * **What is your deployment environment (e.g., Kubernetes, AWS, Azure)?** * **What are your key requirements (e.g., security, rate limiting, observability)?** Then I can provide more tailored advice.

MCP NanoBanana

Enables AI image generation and editing using Google's Nano Banana model via the AceDataCloud API. It supports creating images from text prompts, virtual try-ons, and product placement directly within MCP-compatible clients.

code-auditor-mcp

Enables AI assistants to search, analyze, and understand multi-language codebases by providing indexed code intelligence via MCP.

Weather MCP Server

Provides weather information for cities through a protected MCP interface with Nevermined payment integration. Demonstrates both high-level and low-level MCP server implementations with paywall protection for tools, resources, and prompts.

Serverless VPC Access MCP Server

An auto-generated MCP server for Google's Serverless VPC Access API, enabling communication with Google Cloud VPC networks through natural language interactions.

Microsoft Planner MCP

Enables interaction with Microsoft Planner tasks through natural language using Azure CLI authentication. Supports listing plans, creating/updating/deleting tasks, managing buckets, and integrating GitHub links without complex OAuth setup.

Turnale

Tournament software for tennis, padel, pickleball and more: fair draws, live standings, scores and dropout handling.

BOSSCORE MCP PACK

Modular MCP capabilities package for the BOSS ecosystem, enabling WordPress site management, file reading, and cPanel deployment with 63 tools across three profiles (wordpress, files, full) and two transport modes (stdio and HTTP/SSE).

db-mcp

A secure MCP server for connecting AI assistants to MySQL, Redis, and MongoDB with preconfigured connections, runtime protections, and graded security modes.

PAELLADOC

A Model Context Protocol (MCP) server that implements AI-First Development framework principles, allowing LLMs to interact with context-first documentation tools and workflows for preserving knowledge and intent alongside code.

mcp-gitlab-workflow

An MCP server for issue-driven GitLab development, automating requirement analysis, issue creation, branching, coding, merge requests, and issue updates.

mcp-fc

MCP server exposing the financecentre MongoDB (stocks, prices, SEC financials, insider trades, 13F funds, congressional trades, macro series, news) to AI agents.

playwright-react-debug-mcp

Enables AI-assisted debugging of React applications by providing browser control, DOM inspection, network monitoring, React DevTools, and error analysis through natural language conversation.

token-scout

Discovers LLM models in real time from cloud providers and local Ollama instances, returning compatibility profiles and live pricing so AI agents can route tasks to the cheapest viable model without breaking tool calls or context clipping.

Gmail MCP Server

A high-performance MCP server that enables AI assistants to interact with Gmail securely via OAuth 2.0, supporting smart email retrieval and thread-aware drafting.

Fuse

A local .NET MCP server for coding agents, providing persistent semantic indexing, typed-graph DI wiring resolution, reduced context, and compiler-backed verification for .NET projects.

Zaifer-MCP

Enables LLM assistants like Claude to interact with Zaif cryptocurrency exchange through natural language, supporting market information retrieval, chart data, trading, and account management for BTC/JPY, ETH/JPY, and XYM/JPY pairs.

Code Mode Bridge

An MCP server that aggregates multiple upstream MCP tools into a single 'codemode' tool for unified orchestration and execution. It enables agents to run generated code in an isolated sandbox to interact with various connected services through a single interface.

Almanac MCP Server

Self-hosted fitness tracking MCP server that gives AI assistants access to your nutrition, training, weight, sleep, and accomplishment data via 77 tools and 5 resources. Enables natural-language logging and querying of personal health metrics through Claude or ChatGPT.

MCP Data Analyst

Enables natural language querying of SQL databases using AI, supporting multiple database types and automatic schema discovery.

Artsy Analytics MCP Server

A Model Context Protocol server that provides Artsy partner analytics tools for Claude Desktop, allowing users to query gallery metrics, sales data, audience insights, and content performance through natural language.

Remote Jobs MCP Server

Official Model Context Protocol (MCP) server to search, filter, and retrieve live remote job listings from the Jobicy database in real-time. Works with Claude Code, Cursor, Cline, and custom AI agents.

MCP Server SearXNG

MCP server for SearXNG meta search engine with enhanced error handling and parameter validation for AI agents. Enables privacy-focused web searches with structured JSON results and advanced filtering.

godot-docs-mcp

Query Godot Engine documentation with full-text search across classes, methods, properties, and inheritance.

root-ext-cad

CAD-engineering MCP tool server for parametric modeling, DFM validation, mechanical calculations, and more. Enables code-CAD builds (build123d/CadQuery), model inspection, meshing, and mechanical calculators via MCP stdio.

ask-user-questions

Enables AI models to ask users questions through a local web interface, supporting batch questions, multi-select, and free text for human-in-the-loop interactions.

MCP Server Builder

Provides searchable access to official MCP protocol specification and FastMCP framework documentation, helping developers build correct MCP servers by querying live documentation with BM25 full-text search.

Aedifion MCP Server

Enables AI assistants to interact with the aedifion cloud platform for building performance optimization and IoT data management. It provides over 95 tools for monitoring timeseries data, managing project components, and executing building analytics or controls.

Apple Health MCP Server

An MCP server that allows users to query and analyze their Apple Health data using SQL and natural language, utilizing DuckDB for fast and efficient health data analysis.