"Serverless" matching MCP servers:

Provides tools for AI assistants to manage and diagnose MWAA Airflow environments, EMR Serverless jobs, S3 files, and Confluence documentation. It features automated pipeline failure diagnosis and comprehensive log retrieval across these integrated platforms.

Manage satellites, hosting, serverless functions, changes and more through any MCP-compatible client. Includes a built-in documentation tool to access Juno's official guides and references.

A basic serverless MCP server using LanceDB to store and retrieve documents via three tools: ingest, retrieve, and get table details.

Provides read-only access to PostgreSQL databases via MCP, enforcing least-privilege roles, row-level security, masked views, and SQL AST guardrails to prevent data leakage and unauthorized operations, enabling AI agents to safely query sensitive production data.

Serverless connector to access Google Contacts via MCP, enabling AI agents to securely interact with contacts without storing data.

An MCP server that enables semantic search over local files or GitHub repositories by indexing content into a serverless vector database, allowing AI assistants to understand meaning rather than just keywords.

Headless, peer-to-peer context synchronization for local AI agents. It enables multiple LLM agents to share structured context and resolve state conflicts over a serverless P2P network.

Enables deploying, inspecting, and managing serverless functions on the MetaCall FaaS platform through a Model Context Protocol interface. Supports uploading zip packages, triggering deployments, retrieving logs, listing repositories and subscriptions, and invoking deployed functions with token-based authentication.

A read-only MCP server for safe, structured investigation of AWS serverless resources, providing curated tools for tracing dependencies, permissions, and failures without exposing raw SDK access.

Demonstrates the new stateless MCP protocol on a serverless platform, showing how it survives instance death and cold starts unlike the legacy session-based approach.

Enables AI agents to diagnose and analyze AWS serverless infrastructure through Model Context Protocol, providing access to CloudWatch logs, Lambda functions, DynamoDB tables, IAM policies, and Bedrock-powered incident root-cause analysis.

A serverless-accelerated hybrid development platform that minimizes dependencies in the local development environment and organically combines a virtual operating system kernel inside a web browser with the local host resources.

Enables LLM clients to inspect and query your own GCP and AWS infrastructure, including BigQuery/Athena, CI build systems, container/serverless runtimes, and their logs through configurable environments.