"How to execute a Python script" matching MCP servers:

Enables SEO audits and URL monitoring via the SEO Radar API from any MCP-compatible AI client.

A unified CLI, web dashboard, and Python API for SLURM job management.

Enables AI agents to manage a Canonical Landscape estate, including inventory, alerts, patching, and script execution, with built-in safety layers to prevent accidental destructive actions.

远程MCP服务，通过Model Context Protocol为AI应用提供阿里云数万个OpenAPI的无缝集成，支持Terraform、多账号、自定义OAuth等能力。

Enables AI agents and MCP-compliant clients to autonomously evaluate SLA breach incidents, escalate alerts, and execute canary rollback playbooks with deterministic, zero-dependency Python tooling.

Enables MCP clients to triage SOC alerts while enforcing a trust firewall across retrieval, memory, and privileged actions. It exposes tools for alerts, logs, memory, and alert actions, with defenses that refuse risky operations in the presence of attacker-controllable content.

Enables AI assistants to programmatically create, execute, and analyze Apache JMeter performance tests. It supports automated bottleneck detection, report generation, and distributed testing management through natural language.

Enables AI assistants to manage and interact with Ignition Gateway 8.3+ through a curated set of tools covering gateway administration, projects, resources, tags, alarms, historian data, and script execution via the REST API.

A powerful, lightweight Model Context Protocol (MCP) server built in Python that enables Artificial Intelligence assistants (Claude Desktop, Cursor, Antigravity, Claude Code, etc.) to manage and monitor your Proxmox VE cluster using natural language.

A Model Context Protocol (MCP) server for comprehensive monitoring and observability of systems using Langfuse.

A read-only MCP server that gives Claude safe access to Kubernetes clusters, enabling listing, describing, and monitoring resources without mutation risks and with secret masking.

A token-efficient MCP server for MySQL, PostgreSQL, and SQLite, providing tools to query databases, execute SQL, and analyze query performance.

Enables read-only querying and analysis of Kibana logs through a logged-in sid Cookie, including keyword/time/index searches, traceId lookups, surrounding log context, and aggregations by service, level, or host. It also validates Kibana connection status and redacts sensitive fields such as cookies, tokens, and passwords.

Enables AI agents to query and analyze Graylog logs through MCP tools for search, aggregation, stream listing, and saved queries, with optional OpenAI-powered natural language orchestration and audit logging.

Enables natural language queries for device support, including resolving device references, retrieving device details, historical metrics, and checking provisioning status. Maintains conversation context for multi-turn interactions.

Enables AI assistants to directly read and write Google Apps Script projects, manage versions, deployments, and inspect execution logs to debug triggers.

Enables external AI clients to autonomously execute backend tools via SSE, including system health checks, within a FastAPI async microservice with conversational memory.

Enables querying and managing AI logs through tools like listing logs, retrieving jobs, and performing AI-powered chat queries. Also provides access to gateway security reports and guardrail testing.

Enables secure execution of Python code, SQL queries, and metric fetching through MCP with ephemeral Docker sandboxing.

An MCP server for querying Grafana Loki directly with a discovery-first workflow — labels, values, series, and LogQL queries without requiring Grafana.