"LINE" matching MCP servers:

Audits any site's UX the way a design-literate reviewer would — contrast, tap targets, type scale, colour discipline, scan patterns, copy — and returns the rule, the source line and the exact fix.

Enables coding agents to identify likely runtime failures in JavaScript and TypeScript by ranking risky files, tracing dependencies, analyzing logs, and obtaining independent model reviews with line-level reasons.

tailtest-cline is a Cline plugin that automatically generates and runs tests every time the agent edits a source file. https://github.com/avansaber/tailtest-cline

Eyes for AI coding agents: deterministic MCP server that tells the LLM which CSS rule wins, in which file, on which line — and why. Cascade verdicts, blast radius, interaction timelines, pixel-perfect audits.

Runs SQL statements in memory against real PostgreSQL 18 and SQLite 3.49 engines after loading your schema and sample rows, returning each statement's own verdict: errors with line, column, and hints, constraint violations, or the resulting rows. It also compares both dialects to expose portability differences, all with no database server, network, or API key.

Drives a browser - or a native Expo/React Native app - and your dev server, putting both on one correlated timeline so a console error and the backend stack trace from the same moment line up. For Claude Code and AI agents.

Enables AI assistants to lint, render, fix, inspect, and find free space in KiCad schematics and PCBs, providing visual feedback and safe automated text fixes.

An independent review layer for AI-generated text: a 10-lens gate run by a separate model over output it did not write, returning the flagged line and the reason for each check rather than a single opaque verdict. A check that cannot complete reports unknown instead of a pass; lens_health needs no API key.

Compares Figma frames to live pages, checking colors, fonts, and border radii, and generates a shareable HTML report.

Programmatic email deliverability testing for AI agents. Create inbox placement tests across Gmail, Outlook, Yahoo, Mail.ru, Yandex — get per-provider placement (Inbox/Spam/Promotions), SPF/DKIM/DMARC auth, Rspamd & SpamAssassin verdicts, DNS health (MX, PTR, DNSBL), and live SSE results.

Enables agents and users to validate Kubernetes manifests (YAML/JSON, multi-document) against the API of a chosen Kubernetes version without needing a cluster. It reports removed or deprecated APIs with replacements, unknown or misspelt fields, misconfigurations the API server would reject, Pod Security Standard violations, and common risks, each with file, line, and fix.

Enables checking for broken links on web pages and entire websites through natural language commands. Provides detailed reports including HTTP status codes and supports options like excluding external links and respecting robots.txt.

Lints local Markdown files or whole directory trees for broken relative links and images, empty link targets or text, heading hierarchy problems, and common README issues. Only relative targets on disk are checked, so external http(s) links are never fetched.

Allows AI agents to interact with serial devices via RS232/UART, enabling port listing, connection, read/write, control line manipulation, and protocol specification for automated debugging and testing.

MCP server for Java branch coverage analysis using JaCoCo. Enables agent-style coverage feedback with per-test-class granularity and uncovered line identification.

Enables AI agents to render HTML and audit its typography using book-quality Knuth–Plass line breaking, hyphenation, and microtypography in a headless browser, returning markup diagnostics and a page screenshot for visual, iterative CSS refinement.

Exposes repository reconnaissance tools — file listing and verbatim reading, regex search, dependency-tree parsing across Python/Node/Rust/Go, and test-coverage ingestion — so agents can gather line-numbered evidence from real source files. This lets an audit pipeline physically re-verify every claim and drop findings that cannot be located in the code.

Enables AI agents to build, wire, inspect and simulate digital circuits directly in a running Logisim Evolution window, with every edit appearing live and undoable. Agents work from exact ports, real netlists and truth tables rather than screenshots, and can verify designs through simulation.

MCP server to lint and validate Kubernetes-related manifests(Helm, FluxCD, ArgoCD, Kustomize, etc.)

Enables an agent to drive a running Unreal Engine game via UE4SS by reading/writing UObject properties and calling UFunction, with verdicts that verify whether the requested state change actually happened.