"Information on Air Quality Index (AQI)" matching MCP servers:

Provides real-time air quality data (US AQI, PM2.5, PM10, ozone, NO2, SO2, CO) for any city via natural language, using free Open-Meteo data and a single tool.

Local-first air-quality MCP for AI agents: AirGradient, AirThings, PurpleAir, IQAir and Awair.

Enables Claude Desktop and Claude Code to read locally synced Fitbit Air health data — scores, trends, sleep, activity, running and body age — run read-only SQL against it, and keep a journal and coach notes on the user's Mac. It also offers profile edits, a refresh tool, and guided prompts such as morning check-ins, weekly reviews, race planning and score explanations.

Enables AI agents to screen and filter stock universe, compute custom quality scores, inspect score history, manage scoring systems, and generate shareable screen links, acting as the signed-in user.

Enables AI assistants to perform governed risk assessments through AIR: discover projects, upload evidence, run assessments, and retrieve structured reports.

A personal file-indexing MCP server that provides semantic and keyword search over a file index, plus file content lookup and browsing. It enables agents to search and retrieve files from a user's home directory.

Enables Cursor and Codex agents to audit Agent Skill structure (frontmatter, broken links, missing files), analyze dependencies for undeclared, unused or vulnerable packages via OSV, and run 28 local bug and code-quality rules with SonarQube-style A–E ratings. It can also optionally pull issues, metrics and quality-gate status from SonarQube or SonarCloud, or scan and upload results.

Provides structural, queryable understanding of a Python codebase via MCP tools, enabling direct lookups for callers, dependencies, and class hierarchies without repeated grep/read cycles.

Connects AI coding assistants to PyCharm's code quality inspections and optionally SonarQube for IDE, providing unified, de-duplicated code analysis results without uploading source code.

An MCP server that deterministically scores landing pages on conversion-critical signals and blocks ad spend on low-quality pages to prevent wasted budget.

A Model Context Protocol (MCP) server that helps large language models index, search, and analyze code repositories with minimal setup

Provides natural language access to over 100 years of historical market index data, including S\&P 500, NASDAQ 100, and Nikkei 225. It enables users to query price ranges, compare symbol performance, and analyze historical market trends directly within Claude.

Enables AI agents to search any local folder through a private SQLite FTS5 index that extracts text from PDFs, Office documents, plain text, code and zip listings, returning ranked matches instead of slow ls/grep scans. It also supports metadata and glob listing, paged retrieval of already-extracted text, duplicate detection, and incremental background re-indexing with secrets and caches excluded by default.

Indexes local documents (PDF, Word, Markdown, text) into a SQLite database for AI agents to search and retrieve bounded, source-located passages. Runs fully locally with optional OCR, preserving privacy.

Per-unit cost of 13 back-office tasks done by a person vs by software, in the US, Greece and Ukraine, with an official statistic behind every hourly wage. Bundled data, works offline.

Self-hosted hybrid code search MCP server with text, symbol, and semantic search layers. Runs locally, no third-party MCP servers, LSP, or SaaS.

Enables AI clients to browse instruments, items, dimensions, expert assignments, and calculate Content Validity Index (CVI) via a standard MCP interface.

Enables unified code search and analysis over a monorepo, combining exact, semantic, and call graph queries with indexing, incremental updates, and impact analysis.

Generates and deploys Cloudera Data Engineering (CDE) Airflow jobs from ODCS data contracts, validating live table data in CDW against schema and data-quality rules without WAP staging.

MCP server for Magic: The Gathering card prices, deck analysis, sealed product EV calculations, and investment insights, powered by live data from 5 vendors covering 99K+ cards.

A local MCP server that indexes codebases using Tree-sitter AST parsing and LanceDB, enabling AI models to search across repositories with sub-second latency.

Helps with cicd work, failed tests in automation and also tmmi/iso scans en reports.

AI memory that works like yours. Neural pathway architecture gives your AI persistent recall, contextual awareness, and cross-session continuity the way human memory actually works. 14 MCP tools. Works with Claude Code, Cursor, Windsurf, and any MCP client. $50/mo unlimited.

Enables AI agents to search millions of podcasts, read and search episode transcripts with timestamps and speakers, and access chapters, soundbites, Podcasting 2.0 tags, value-for-value data, feed health, and index statistics through 36 tools.

Provides real-time system metrics and information through a Model Context Protocol interface, enabling access to CPU usage, memory statistics, disk information, network status, and running processes.

Provides tools to test regex patterns for correctness, performance (ReDoS), and memory usage, and suggests safe rewrites. Enables LLMs to iterate on regex generation with verifiable feedback.

On Board is a local MCP server that gives multiple AI agents and IDEs a shared project memory, ticket queue, and handoff history, so agents can seamlessly continue each other's work. It supports agent-to-agent wake events, enabling autonomous workflows like reject-fix-resubmit cycles without human relay.

Local-first supply-chain CVE scanner. Scans project deps, system packages (Homebrew/apt), and IDE extensions (VS Code, JetBrains) via OSV, NVD, GHSA, EPSS, and CISA KEV. Listed in the official MCP Registry as io.github.DevInder1/tridentchain-security.

Enables AI agents to start, control, and verify local open.mp/SA-MP game servers via MCP stdio, using a headless RakClient to send allowed slash commands and assert round-trip responses.

Enables AI agents to search and retrieve details about Odoo code elements (models, fields, views, etc.) with exact file locations using MCP tools.