"Learning or Writing Code in Python" matching MCP servers:

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

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

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.

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

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.

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

Lets an assistant read recorded production AI agent runs — steps, model and tool calls with arguments, and outcomes — along with the findings of comparison runs that checked a prompt or model change against those recordings, and verify a signed evidence bundle offline with no account or network. It is strictly read-only: no tool starts a replay or comparison, so nothing can spend money or act without a person deciding.

Self-hosted Nightingale (n9e) includes a native Streamable HTTP MCP server at /mcp for querying alerts, rules, metrics, logs, hosts and dashboards with the caller's existing permissions. Users deploy the Nightingale server themselves; the implementation and deployment documentation are in the main repository, and the official website is https://n9e.io.

Lets your coding agent check whether a production deploy actually worked. It waits for DeployAngel's verdict on a release (cleared, failed, or not cleared yet) and reads the evidence when one fails, including jobs that quietly stopped running.

Enables AI assistants to query and analyze AI agent sessions from observability providers like Shepherd (AIOBS) and Langfuse, allowing users to debug agent runs, compare sessions, track performance, and analyze LLM usage patterns.

Enables developers to build production-grade MCP services with dependency injection, zero global state, layered imports, and a sample user-notes tool, resource, and prompt. It includes Testcontainers, Prometheus metrics, Kubernetes probes, and structured logging for testable local and production deployments.

Enables remote log searching, tailing, and file reading across servers via MCP tools, with pluggable execution via SSH, pyinfra, or local commands.

Enables AI agents to investigate incidents by listing services and dependencies, searching redacted logs, summarizing metrics, checking recent deploys, and producing ranked timelines with scoped tokens, validation, rate limiting, and audit logging.

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.

MCP server for analyzing Perfetto traces with LLMs — query .pftrace files in PerfettoSQL via Claude Code or any MCP client

Enables read-only inspection of local coding-agent sessions across Claude Code, OpenCode, Cursor, and Codex, including running status, topics, todos, and transcripts, without writing or sending messages.

MCP server for Python JSON logs

Enables transparent security for any MCP server by intercepting tool calls, blocking prompt injection attempts, masking PII in responses, and writing immutable audit 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.

An MCP server that connects Claude (or any MCP compatible client) to your existing log infrastructure. Query, summarize, and trace logs in plain English across GCP Cloud Logging, AWS CloudWatch, Azure Log Analytics, Grafana Loki, and Elasticsearch without writing filter expressions or leaving your editor.

A local stdio MCP server with recording and tracking tools that lets Codex and Claude Code agents log chat activity, tasks, and delegations onto a loopback-only visual Kanban board with animated mascots. It enables observing work in progress while leaving conversation and execution in the originating client, without hosting models or running AI itself.

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

Read-only MCP server that surfaces UniFi network data from a UCG-Fiber console to Claude, enabling monitoring of hosts, sites, devices, clients, ISP metrics, and device stats via read-only API tools.

Enables coding agents to trace, profile, and investigate performance hotspots in application code, native code, GPU kernels, and inference stacks by coordinating local profilers, benchmark tools, trace processors, and direct capture targets. Returns bounded, typed runtime evidence with observed inputs, provenance, coverage, and limitations, all through explicit artifact paths or commands with no workspace setup required.

An advanced system monitoring solution that uses unsupervised machine learning algorithms to detect abnormal resource usage patterns in real-time, with features including anomaly detection, process analysis, and Discord integration.

A local-first MCP server that gives AI coding agents runtime visibility and AI-managed debug logging. It replaces blind print() debugging by turning runtime execution into causal chains, allowing agents to instantly locate bugs by finding missing .success events in Python and TypeScript code. Single binary with MCP, CLI, and HTTP interfaces.

Provides cryptographically signed, tamper-evident compute usage receipts via a Model Context Protocol server, exposing tools to record usage, verify receipts, list the ledger, and verify ledger integrity without requiring any account, API key, or single cloud provider.

Enables classification of GPU workloads as training, inference, or idle from telemetry data, with tools for one-shot classification, benchmarking, and audit log verification.

16-tool MCP server for Google PageSpeed Insights & Chrome UX Report APIs. Analyze, compare, and optimize web performance directly through Claude, Cursor, or any MCP-compatible AI client.

Read-only MCP server for Grafana Loki: lets AI agents (Claude Code, Cursor, Copilot) discover labels, read bounded LogQL pages, count lines by label or time, and export logs — across several Loki stands

MCP server exposing rlg (RustLogs) log files as tools for on-call / SRE agent workflows. Three tools over JSON-RPC stdio — tail_log (last N events, filtered by level/target), filter_log (predicate filtering), summarize_errors (grouped error taxonomy). Pure Rust. MIT OR Apache-2.0.

Tells an agent what went wrong with its own Ollama calls, in sentences with the fix: lost prompt cache and where the prompt stopped matching, context overflow, a model running partly on CPU, tool schemas crowding the prompt. Also the last turn in numbers and which local models fit in video memory. Local, read-only, nothing leaves the machine.

Production-grade MCP Gateway in Go featuring dynamic OpenAPI tool registration, RBAC governance, in-flight PII/DLP redaction, and structured JSON audit logging.

Compares AI coding tool spend before and after a migration -- Cursor, Claude Code, GitHub Copilot, OpenCode, Codex CLI -- via an MCP server, real numbers from each vendor's own API or local logs.

Uptime monitoring for websites, APIs, SSL certificates, domain expiry, ping and TCP/UDP ports. 15 tools to list, create, pause and delete monitors, pull incident timelines with error codes, and read hourly or daily uptime and response-time statistics.

MCP server for the Chrome UX Report, providing real-user Core Web Vitals (LCP, INP, CLS) and historical trends for any origin or URL via natural language queries.