"Signal" matching MCP servers:

An MCP server that runs developer tooling commands (tests, linters, etc.) and returns compact, grouped error summaries to AI agents, reducing token usage and context window pollution. It supports multiple adapters for different tools and provides tools like run_check, diff_runs, and get_log_slice for iterative debugging.

Helps AI coding agents migrate Angular Reactive Forms to Signal Forms by locating form constructs, distinguishing mechanical renames from judgment calls, and providing verified before/after recipes. It only detects and advises, never edits source code.

Enables AI-powered security scanning of code changes and files through coding assistants, detecting vulnerabilities and providing fixes.

Signalint is an MCP server that provides JavaScript and TypeScript diagnostics by running Oxlint, TypeScript, and optionally Biome, with caching, clustering of repeated issues, and detection of oscillating diagnostics.

Provides AI assistants with tools to check npm package versions and security heuristics, including version lookups, signal-based analysis, and batch analysis of package.json files.

A task-aware context compression layer for Agent workflows, RAG pipelines, and AI Coding assistants, reducing noisy logs, retrieval chunks, and code context into high-signal LLM inputs via CLI, Python SDK, and MCP.

A function-level call-graph indexer for GDScript/Godot projects, exposed as an MCP server so AI coding assistants can answer questions like 'what calls this function?' or 'what would break if I change this signal?' without re-reading the whole codebase.

Enables analysis of RTL waveform files (VCD, FST) through WAL (Waveform Analysis Language). Supports signal inspection, transition extraction, and advanced waveform queries for hardware design verification.

Automates Close-to-Shore methodology for Godot game development by creating tasks in Shrimp MCP from hop plans and generating interactive visualizations of signal architectures, dependencies, and project metrics.

Provides MCP tools to review git changes using OpenAI Codex CLI, enabling code review of unstaged, staged, or last-commit changes.

Enables AI agents to discover open-source libraries worth reusing through multi-signal repository ranking and to search real code with sub-50ms local regex/semantic queries federated to live GitHub, grep.app, and package-registry backends. It exposes seven tools over stdio—repo search, code search, repo profile/tree, file and docs fetching, and a usage guide—with structured filters, typed pre-execution errors, and a byte-identical CLI twin.