"General Information Request" matching MCP servers:

Enables AI assistants to search and filter Azure platform updates, including previews, general availability, and retirements, through natural language queries.

Enables AI agents to discover, request access to, and query data products in Data Mesh Manager, enforcing governance policies while retrieving business data from platforms like Snowflake and Databricks.

Enables MCP-speaking agents to deploy and operate applications on gagarin by translating every tool call into an authenticated request to the gagarin API, using the caller's own credential.

Enables AI assistants to search and retrieve information about Terraform providers and modules from the public Terraform registry, including detailed documentation, version information, and resource specifications.

Enables AI agents to run BigQuery queries safely under a configurable policy, with parsing, dry-run byte limits, row caps, and audit logging for every request.

Provides direct access to Microsoft Graph API with multi-tenant account management, allowing users to interact with Microsoft 365 services across multiple tenants through a single flexible graph-request tool.

Enables AI agents to manage Stape.io infrastructure, including container management, custom domains, power-ups, request logs, and Stape Store NoSQL database operations.

Implementation of Model Context Protocol (MCP) server that provides tools for accessing Google Cloud's Vertex AI Gemini models, supporting features like web search grounding and direct knowledge answering for coding assistance and general queries.

Helps design, validate, and generate Adobe Experience Manager Assets API request plans for integration work, including upload, folder management, and metadata sync.

Enables interaction with the Fastly REST API through user-scoped authentication, supporting service management, purging, token updates, and full API coverage via a configurable request tool.

An MCP server that enables users to retrieve information from AWS Knowledge Bases using RAG (Retrieval-Augmented Generation) via Bedrock Agent Runtime.

An MCP server that allows searching for and retrieving information about Model Context Protocol servers registered on the MCP Hub.

Enables middleware management, information checking, backups, and node-level operations for the MegaCloud API.

Query and interact with kubernetes environments monitored by Metoro. Look at APM, metrics, traces, profiling information with LLMs.

An MCP server that enables AI models to access user geolocation information through EdgeOne Pages Functions.

A local MCP server that integrates with Claude Desktop, enabling RAG capabilities to provide Claude with up-to-date private information from custom LlamaCloud indices.

Enables you to publish remote MCP tools from your own Lambda behind a single HTTP API endpoint, with selectable authorization (IAM, API key, JWT, Lambda, or Google Workspace), stage throttling, JSON access logs, and RFC 9728 resource metadata discovery. No session table or sticky routing is needed, so any invocation can answer any request.

Enables AI models to retrieve user geolocation information through EdgeOne Pages Functions. Provides access to location data via the Model Context Protocol for integration with large language models.

Enables large language models to retrieve user geolocation data using EdgeOne Pages Functions. It provides a dedicated tool to fetch location information in JSON format through the Model Context Protocol.

Enables Amazon Quick users to access a third-party MCP/REST API through Bedrock AgentCore Gateway with per-user Entra ID 3LO authentication. A request interceptor mints and injects a per-user downstream bearer token so the model never sees it.