"Understanding and Building Probability Density Functions (PDF) Models" matching MCP servers:

MCP server to manage and deploy Scaleway Serverless Functions, enabling creation, listing, updating, deleting, downloading, and logging of functions through natural language.

MCP server for Aspose PDF Cloud, enabling PDF storage, conversion, and extraction operations (merge, split, text/table/image extraction) via CLI and MCP.

A quickstart template to build and deploy a remote MCP server on Azure Functions using Python, secured with keys and HTTPS.

Enables AI assistants to interact with Databricks workspaces, running SQL queries, managing jobs, and exploring schemas via the Model Context Protocol.

A template for deploying MCP servers on Vercel with serverless functions. Includes example tools for rolling dice and fetching weather data to demonstrate basic tool implementation and API integration patterns.

Enables building and deploying custom tool, resource, prompt, and interactive weather app endpoints on serverless infrastructure, with local debugging, built-in authentication, API Management security, and network isolation.

Enables developers to run and deploy a custom remote MCP server on Azure Functions that exposes MCP tools, resources, and prompts—such as snippet CRUD, QR code generation, code review checklists, and interactive app UIs—with built-in Microsoft Entra authentication. Supports local debugging and one-command cloud deployment, with optional API Management and VNET network isolation.

Enables developers to build, run locally, and deploy to the cloud a custom MCP server on Azure Functions that exposes tools, resources, prompts, and an interactive weather app over HTTP. Includes built-in authentication via Microsoft Entra, plus options for API Management and VNET network isolation.

Enables developers to build, run locally with debugging, and deploy to the cloud custom remote MCP endpoints hosted on Azure Functions, with built-in Microsoft Entra authentication. Sample projects demonstrate snippet CRUD and QR code tools, resource templates, prompt workflows, and an interactive weather demo UI.

Publishes sample Python implementations that expose tools such as snippet CRUD, QR code generation and batch operations, resources, and prompts like code review checklists and doc generation, plus an interactive weather app, to MCP clients. These can be run locally with debugging or deployed to Azure with built-in Microsoft Entra authentication.

Enables developers to build and deploy custom tool, resource, and prompt integrations to the cloud using serverless functions, with local debugging and built-in authentication.

Enables interaction with Google Cloud services including billing cost analysis, log querying, and metrics monitoring through natural language commands. Provides comprehensive tools for managing GCP resources, analyzing costs, detecting anomalies, and retrieving operational insights.

Hosts MCP tools for weather queries and On-Behalf-Of flow, enabling Copilot to retrieve weather data and user info via Azure Functions.

A quickstart template for building and deploying secure, remote MCP servers to the cloud using Azure Functions and Node.js/TypeScript. It features integrated blob storage for snippet management and supports advanced security options like OAuth and VNET isolation.

An educational MCP server deployed as an Azure Function, exposing tools like addition, weather simulation, and temperature conversion for AI agents to invoke.

Acts as an AI Gateway for MCP servers using Azure API Management, implementing the latest MCP Authorization specification.

An Azure Functions-based MCP server that enables interaction with Marvel characters and comics data through the official Marvel Developer API.

A template for deploying MCP servers on Vercel with serverless functions. Includes example tools for rolling dice and getting weather data to demonstrate basic functionality and API integration patterns.

A cloud-based custom MCP server using Azure Functions that enables saving and retrieving code snippets with secure communication through keys, HTTPS, OAuth, and network isolation options.

Enables named, authenticated callers to run read-only introspection of a Google Cloud project and to read and write per-tenant notes that stay isolated between callers. Every request is scope-checked against a reviewed policy, rate-limited per caller, and audited without ever logging argument values.

Enables snippet CRUD, QR code generation, structured metadata, and batch operations through MCP tools.

A deployable MCP server for Cloudflare Workers or Azure Functions that provides example tools (time, echo, math), prompt templates for code assistance, and configuration resources. Enables AI assistants to interact with edge-deployed services through the Model Context Protocol.

Enables AI agents to discover and invoke backend tools over MCP JSON-RPC while enforcing 3-legged OAuth 2.0 identity propagation, role-based access control, and protocol transcoding to REST APIs.

Enables automated review and analysis of network security controls (AWS Security Groups, Network ACLs) using natural language queries. Supports NSC configuration reviews, network segmentation testing, and identifying security gaps through conversational LLM interaction.

Enables natural-language querying and analysis of AWS spending and model-invocation usage, including detailed breakdowns by service, region, account, day, and instance type.

Enables natural-language queries of AWS spend and Bedrock usage data, providing detailed breakdowns by service, region, account, user, instance type, and model, including cross-account cost analysis.

Enables users to query and visualize AWS spend and Amazon Bedrock usage data through natural language, including EC2 and service cost breakdowns and Bedrock usage by region, user, and model.

Enables natural-language analysis of AWS spend through Cost Explorer and Amazon Bedrock usage via CloudWatch model invocation logs, with breakdowns by service, region, model, user, day, and instance type. It also supports cross-account cost retrieval and local or remote MCP transports.

Enables users to query AWS spend data and Amazon Bedrock usage from CloudWatch model invocation logs through natural language. Supports detailed cost breakdowns by service, region, day, and instance type, including cross-account AWS spend retrieval.

Enables users to query AWS spending and Amazon Bedrock usage in natural language through MCP clients, with breakdowns by service, region, day, model, and user, plus optional cross-account access.