The MCP server for Nanostores that scans your codebase with AST analysis to find stores, subscribers, and dependency chains, and can ingest live events to spot noisy, error-prone, or unused stores.
A bridge between AI assistants and the Paradex perpetual futures trading platform for managing accounts, vaults, and orders. It enables users to retrieve real-time market data, monitor positions, and execute trading strategies through the Model Context Protocol.
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 read-only MCP server that provides family-context tools for the A2Me platform, enabling AI assistants to answer family-related questions and help write messages by securely accessing family member profiles, upcoming events, and recent activity.
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.
A Model Context Protocol server for the Quire project management platform, enabling AI assistants to securely interact with Quire projects, tasks, and data.
Enables LLMs to access MCP protocol specifications and TypeScript SDK documentation with context-aware search and code templates for building custom MCP servers.
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.
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.