"Resources or tools for conducting in-depth research" matching MCP servers:

Provides web automation utilities, including taking Camofox browser tab screenshots and saving them directly to local files.

A comprehensive Model Context Protocol server providing access to 70+ IT tools for developers and system administrators, including encoding/decoding, text manipulation, hashing, and network utilities.

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 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.

An MCP server that connects AI assistants to a Neo4j graph database, enabling querying of movie data through tools like graph statistics, genre-based search, and movie details, along with advanced features such as LLM sampling and completions.

Enables agents to quickly find and edit code in a codebase with surgical precision. Find symbols, edit them everywhere with tools for reading code blocks, searching/replacing text, and making precise line-based modifications.

An MCP server that provides AI clients with access to developer documentation via llms.txt files. Exposes tools, resources, and prompts.

Enables multi-level reasoning with configurable depth levels, session-based state management, structured thought input, and real-time trace resources.

A task-board MCP server that provides tools to search, create, and update tasks, resources for reading the board, and prompts for standup and triage workflows.

Provides a Model Context Protocol server with tools for knowledge base search, retrieval, and addition, plus system time, resources, and prompts. Supports stdio and Streamable HTTP transports for local and shared deployments.

A production-grade MCP server that provides real-time weather data and demonstrates the complete MCP protocol surface including tools, resources, prompts, and structured output.

Provides comprehensive documentation for MAX Platform, including Bot API endpoints, guides, Bridge API, and UI components, via MCP tools and resources for AI coding agents.

Exposes Cursor-style skill packs (SKILL.md trees) via MCP resources, tools, and prompts, enabling any MCP client to list, get, search skills, and retrieve skill context.

Inspect a cronstable job scheduler's jobs, logs, run history, DAG workflows, and cluster health, and ask why a job did or didn't run. Read-only by default; tools that run, pause, or approve jobs and workflow runs need opt-in.

A production-grade TypeScript starter for building Model Context Protocol servers, supporting stdio and Streamable HTTP transports with modular tools, resources, and prompts.

An MCP server that demonstrates the Model Context Protocol using a mock SQLite database of an online store, offering tools for product search, sales analysis, and reviews, along with resources and prompts for learning MCP integration.

A small, readable MCP learning project implemented in TypeScript that uses a local JSON notebook to demonstrate core MCP features such as tools, resources, prompts, sampling, and notifications.

Enables agents to open or connect to a Colab browser tab and use notebook tools, resources, prompts, and progress through a local stdio session.

Provides access to Deutsche Bahn train timetables, station information, and schedule changes through Model Context Protocol tools and resources.

A production-grade MCP server for the Code-Fundi API, enabling AI agents to map codebases, search semantically, and analyze blast radius. It provides tools for repository management, AI-powered research, and impact analysis before shipping changes.

A production-grade, extensible Python template for building Model Context Protocol servers with support for Streamable HTTP and stdio transports. It provides a structured framework for implementing tools, resources, and prompts with built-in authentication, observability, and background task management.

Firecrawl, the context API for AI agents, as an MCP server. Search the web, scrape any URL, parse PDFs and documents, crawl and map sites, interact with pages in a real browser, run Agent research jobs, monitor pages for changes, and search scientific papers. Returns clean Markdown or structured JSON. Run locally with npx firecrawl-mcp or connect to https://mcp.firecrawl.dev/v2/mcp

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.

A test MCP server that exercises all protocol features including tools, resources, prompts, and sampling to help client builders validate implementations.

Integrates Agent Skills into LLMs by discovering skills in a configured directory and progressively loading their instructions and resources on demand through a structured disclosure pattern.

A minimal TypeScript starter template for building Model Context Protocol (MCP) servers with auto-loading architecture for tools, resources, and prompts. Includes code generators, dual transport support (stdio/HTTP), and production-ready structure.

Provides complete access to Model Context Protocol documentation through an MCP server, allowing LLMs to query specific sections like 'Tools', 'Resources', and 'Authorization' to retrieve comprehensive protocol specifications.

Exposes GOV.UK Frontend components and Design System patterns and styles as MCP resources for use with AI assistants.