"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.

MCP server for the Mamba Labs GitHub Organization Signal Scanner actor on Apify. Resolve a company domain to its GitHub organization with repo, language and activity signals.

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 LLMs like Claude to interact with PicoScope oscilloscopes for signal acquisition, measurement, and analysis. Supports device management, data capture, triggering, and signal generation through natural language commands.

Local-first MCP server that analyzes and compiles prompts for multiple LLM clients, detecting intent, missing context, and waste risks to generate cost-aware, task-specific prompts.

Enables read-only analysis of FST waveform files, including signal value queries, timing measurements, event search, latency analysis, and PNG plot generation using human-readable time addressing.

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.

Pre-build reality check for AI coding agents. Scans GitHub, Hacker News, npm, PyPI & Product Hunt in parallel — returns a 0-100 reality signal with real competitor data.

Local-first inspectable memory substrate for Claude Code. Three read-only MCP tools (search_pairs, compact_session, substrate_info) over a signal-scored parse of ~/.claude/projects/, zero outbound calls.

Compacts noisy test, build, and cloud-log output before an AI agent reads it — dedupes repeats, collapses stack frames, folds Playwright retries, and renders CloudWatch/GCP JSON logs down to the signal. Typically 80–95% fewer tokens on failures. Tool: compact_output. Run: npx -y logslim logslim-mcp

Enables AI agents to search a curated directory of Claude Code agent skills, MCP servers, and plugin marketplaces ranked by community signal.

A Python MCP server that reduces token usage by ~98% when working with log files by auto-detecting format and stripping noise to return only actionable signal.

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

Integrates usage-based billing into AI coding tools, enabling meter usage, signal verification, and billing management via the ClockNext API.

MCP proxy that compresses tool schemas on the fly. Up to 98% token reduction, 100% signal preserved verified after every compression. Zero LLM calls, fully deterministic.

Provides shared long-term memory and proactive suggestions across AI coding agents, enabling persistent user preferences and behavior rules that are remembered and applied across different tools. Includes memory capture, recall, extraction, and suggestion tools with a local-first and privacy-focused design.

Enables agents to control a JUNTEK JDS2800 USB signal generator over serial, configuring frequency, waveform, amplitude, offset, duty, phase, sweeps, arbitrary waveforms and independent output enables, with verified readback. It also provides bundled manual reference material and a measured 50-ohm sine power calibration so requested dBm levels can be set and previewed within the calibrated ranges.

Local MCP server for querying VCD waveform files via SQLite; enables AI agents to ask precise questions about signal values, transitions, and clock cycles without dumping raw VCD text.

Codex-optimized MCP server for Godot 4.x with a compact set of high-signal tools for project, scene, script, editor, and API operations.

Connects AI assistants to Siemens Questa Visualizer, enabling natural language control of HDL simulation such as opening waveforms, running simulation, and examining signal values.