"How to run Python code" matching MCP servers:

Enables agents to interact with the Logflare API by writing JavaScript functions that run in a Vercel Sandbox, using three tools: search, execute_read, and execute_write.

MCP server that provides read-only analysis of Claude Code session transcripts, enabling queries about project activity, session details, and tool usage.

A Model Context Protocol server for Zoho Site24x7 that uses a JavaScript sandbox to execute API calls, enabling management of monitors, accounts, and MSP/BU tenancy through natural language.

Maintenance, recovery, and observability for Claude Code. CLI + MCP server + dashboard.

MCP server for Python JSON logs

Runs, tests, and finds issues in your Python services with zero code changes, then helps your AI agent fix what breaks and proves it with acceptance tests.

Hosted remote MCP server for issuing run receipts, summarizing agent changes, checking test evidence, flagging review risks, and exporting run logs for Antigravity agents.

Enables grading a website's security headers with per-gap fixes and a README badge, and analyzing logs, code, configs or suspicious messages to determine what happened, how severe it is, and what to fix first. Requests are masked for sensitive data and automatically retried across multiple AI providers when one refuses, subject to a defensive-use-only policy.

MCP server for safely exposing SQL Server database capabilities to LLM clients, with read-only mode, security features, and observability.

Enables AI agents to trace Python code execution in real time via PEP 669, exposing call trees, variable deltas, and async context through MCP tools.

Detrix is an agentic debugger. Watch any variable at any line, zero code changes during debugging Local or cloud - same workflow for Docker containers and remote hosts Python, Go, Rust - observation points capture values without pausing, without restarting

Surface Claude Code token usage, estimated cost, and plan-limit status in any MCP client. Enables agents to query usage data from local logs and Anthropic API.

Analyzes how search engines and AI systems discover, crawl, cite, and convert traffic via CLI and MCP tools.

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

Claude Code token usage and cost visibility for MCP-capable agents.

Echo tool MCP server that extracts and logs W3C Trace Context from requests to verify propagation from Claude Code.

An observability tool for agentic AI pipelines that intercepts MCP and Python tool calls to provide real-time metrics, session replays, and alerts via a local dashboard. It enables centralized monitoring of multiple MCP servers through multiplexer and proxy modes without requiring changes to existing agent code.

A Python-based MCP server that analyzes PostgreSQL query plans, suggests indexes, and checks pagination safety to help optimize database performance.

Enables MCP clients to query and triage security findings published to BigQuery and correlate them with execution, sandbox, and diagnostic traces in Cloud Logging. Exposes tools, resources, and prompts for filtering issues by severity, status, repository, or CWE, retrieving patch diffs and verification results, and diagnosing why a remediation or verification run failed.

An MCP server that records agent execution metrics and exposes a Context Window Explorer to visualize exactly what entered the model's context window across sessions, tokens, and tool calls.