"Improving the Intelligence of Large Language Models" matching MCP servers:

Enables AI coding agents to make evidence-aware design-pattern decisions by analyzing cases, comparing options, detecting misuse, stress-testing assumptions, planning adoption, writing ADRs, and generating evidence plans with transparent scoring.

Provides an institutional research backend for AI assistants, with 15 tools for company, financial, funding, competitor, industry, and news intelligence, plus Markdown/PDF report generation, featuring deterministic source routing, extraction, validation, and citation generation.

Enables AI assistants to access real-time web data through search, markdown scraping, and browser automation while bypassing anti-bot protections. It provides tools for web research, e-commerce monitoring, and data extraction from across the globe.

MCP server for GreyNoise threat intelligence, enabling IP analysis, GNQL queries, tag and vulnerability lookups, and session/pcap retrieval via natural language.

An MCP server that lets AI models run code in 31 languages, evaluate symbolic math and logic problems, and measure complexity—exposed as 48 tools for execution, session management, translation, optimization, and more.

Enables AI assistants to perform institutional research and due diligence by retrieving, extracting, validating, and citing data from public sources, then generating reports in markdown, HTML, or PDF.

Provides institutional research data retrieval, extraction, validation, and citation generation for AI assistants via the Model Context Protocol.

Enables AI assistants to perform institutional research on companies, financials, industry, news, litigation, and risk, and to generate cited markdown, HTML, or PDF reports through MCP.

Provides local, offline searchable access to Roku and BrightScript development documentation via MCP tools and resources, including full-text search, sectioned reading of large docs, and background syncing from the upstream repo.

A community-built MCP server for the Spaceship API, enabling management of domains, DNS records, contacts, and marketplace listings through natural language.

Enables natural language control of live ArcGIS Pro sessions through the Model Context Protocol, allowing inspection of projects, layers, and attributes, and execution of geoprocessing tasks.

MCP server for Threadlinqs Intelligence — 49 tools across threat intelligence, detections, IOCs, threat actors, MITRE attack-chains, C2 infrastructure, and Purple-tier composite intelligence. Drop-in for Claude Code, Claude Desktop, Cursor, and any MCP-compatible client.

Integrates Granola.ai meeting intelligence with MCP clients to provide direct access to meeting notes, transcripts, and workspace organization. It allows users to search and retrieve meeting content through natural language by leveraging existing Granola credentials.

A task management MCP server for AI-driven development, enabling creation, tracking, and organization of tasks with subtasks, priorities, and dependencies via natural language commands.

Provides access to Shodan's IoT search engine API for device search, host intelligence, exploit database, network scanning, and security analysis through natural language.

A local-first, no-API-key MCP server that enables LLMs to search the web, fetch pages, and read documents using multiple engines and smart fallbacks.

MCP server for overseer.nvim — gives any MCP-capable coding agent running inside Neovim (Claude Code, Codex, Gemini CLI, opencode) the same visibility and control over tasks the user has: list, run, tail, restart, stop. Agent-started dev servers land in the user's own task list instead of becoming invisible orphaned processes.

Enables AI models to access and search offline Wikipedia and other knowledge bases stored in ZIM format files. Provides intelligent content retrieval, structured browsing, advanced search capabilities, and metadata extraction for comprehensive offline knowledge access.

Relays error logs from other MCP servers when an LLM call fails and the returned error message is unclear, helping the model handle errors more intelligently.

Enables LLMs to interact with the AT Protocol ecosystem, including Bluesky, through natural language. Supports public data access without authentication and full write operations with authentication.