"Information about cursors (general use or specific context)" matching MCP servers:

Enables AI agents to query OpenRouter model information including prices, ELO rankings, context, and perform comparisons.

A Model Context Protocol server that enables role-based context management for AI agents, allowing users to establish specific instructions, maintain partitioned memory, and adapt tone for different agent roles in their system.

Zero-dependency macOS desktop automation for AI agents. Screenshot, mouse, keyboard, clipboard, and window control via MCP. 18 tools, macOS 13+, one command: npx mac-use-mcp.

MCP server that recommends which npm/PyPI libraries to use or avoid, with concise verdicts, alternatives, and code snippets, keeping responses under 500 tokens.

Provides LLMs with full PostgreSQL database access, including tools for query execution, schema management, and data export. It also features a dedicated insights system for storing business memos and supports both local stdio and remote HTTP transport.

Local-first documentation for AI agents

Enables LLM assistants to store, retrieve, and update user-specific context memory including travel preferences and general information through a chat interface. Provides analytics on tool usage patterns and token costs for continuous improvement.

An MCP server that preserves LLM context by intercepting large data outputs and returning only concise summaries or relevant sections. It enables efficient sandboxed code execution, file processing, and documentation indexing across multiple programming languages and authenticated CLIs.

Deterministic dependency + CVE context for AI coding tools, over the Model Context Protocol. A ~0.85 MB pure-Rust MCP server.

An MCP server that edits files through a real Neovim instance, giving agents access to LSP diagnostics, formatting, code actions, and plugin commands.

Provides AI assistants with real-time visibility into your codebase's internal libraries, team patterns, naming conventions, and usage frequencies to generate code that matches your team's actual practices.

MCP server providing deep PostgreSQL context to AI assistants, including schema DDL, index health, foreign key associations, query execution plans, and performance statistics via read-only tools.

Aggregator MCP proxy that collapses N downstream MCP servers into 4 meta-tools with progressive tool discovery, and compresses large tool outputs (HTML→Markdown, JSON summarization) with full-output retrieval via read_more and a per-session token-savings report.

Durable project-memory MCP: decisions, constraints, and pipelines across Claude sessions

Intelligent context manager for AI coding assistants that uses a three-level memory system (core, active, archive) to remember project context across conversations.

A system for defining, composing, and managing task-specific contexts for AI-powered development, enabling consistent, high-quality results.

A high-performance MCP server providing up-to-date documentation for Go, npm, Python, Rust, Docker, Kubernetes, Terraform, and more — fetched from official sources, not training data.

Provides persistent tool context that survives across Claude Desktop chat sessions, automatically injecting tool-specific rules, syntax preferences, and best practices. Eliminates the need to re-establish context in each new conversation.

Enables AI assistants to scan project dependencies and Infrastructure as Code files for security vulnerabilities and misconfigurations. It also provides automated fixing capabilities to remediate identified security issues.

Enables LLM agents to compress handoffs into structured, auditable context capsules, preserving goals, constraints, decisions, and risks without external API calls.