"Artifact Hub" matching MCP servers:

A centralized, Git-backed knowledge base and MCP server for teams to store, search, and reuse agent-generated artifacts like skills, specs, plans, reviews, and ADRs, with IDE/Agent integration and a Dashboard for governance.

An extensible MCP hub that exposes internal services (chat, observability, RAG) as namespaced tools via FastMCP, with OpenAPI auto-generation, auth, and resilient error handling.

An MCP server that turns the Hugging Face Hub into a conversational model picker with a tool-use eval harness to prove the agent actually uses it correctly.

A personal knowledge hub MCP server that allows LLMs to query Akib Dabgar's skills, experience, projects, and education using Dynamic Context Retrieval.

Enables multiple isolated Claude sessions to read markdown knowledge bases versioned in git and deposit proposals, while only a manager role integrates changes.

A provider-neutral MCP server that provides tools for managing skills, agents, references, and artifact memory in a local workspace.

DC Hub is the live Model Context Protocol layer for data-center and energy infrastructure. AI agents call 92 tools across 24,600+ facilities for land+power, grid, interconnection, fiber, and Capacity Source — with as_of timestamps. Connect: https://dchub.cloud/connect · Docs: https://dchub.cloud/ai-agents · Endpoint: https://dchub.cloud/mcp · Pro $99/mo.

Self-hosted enterprise knowledge hub that compiles organizational docs into a structured wiki and serves it to AI clients via MCP with fine-grained access control.

An MCP server for aggregating multi-domain intelligence feeds, performing 80:20 crossover analysis, and publishing structured insights to multiple channels.

Enables access to the Hugging Face Hub API to search and retrieve information about machine learning models, datasets, and their metadata. Provides comprehensive tools for exploring the Hugging Face ecosystem including model details, dataset information, and parquet file access.

Implements the Recursive Language Model pattern, enabling LLMs to process arbitrarily long contexts through session-based document management, on-demand chunking, BM25 search, and artifact storage.

A Model Context Protocol server that provides Claude and other LLMs with read-only access to Hugging Face Hub APIs, enabling interaction with models, datasets, spaces, papers, and collections through natural language.

An MCP server for searching and downloading academic papers from multiple sources including arXiv, PubMed, bioRxiv, and Sci-Hub, designed for seamless integration with large language models like Claude Desktop.

Enables local-first context retrieval and management from JSONL and Markdown sources through MCP, with a rebuildable full-text search index and support for stable reference pagination.

An MCP server with RAG capabilities that provides AI clients secure access to local notes, documents, web pages, and task management tools for developer operational tasks. Features file operations, web scraping with content cleaning, and personal knowledge corpus search functionality.

An MCP server that retrieves and provides AI model information from OpenAI, Anthropic, and Google through a unified interface.

Enables AI coding agents to share a persistent local-first memory hub, storing and recalling architectural decisions and context across different tools via MCP, so users can switch assistants without losing context.

Transforms any GitHub repository into a documentation hub for AI assistants, enabling access to up-to-date documentation and code to eliminate hallucinations. Supports repository-specific and dynamic endpoints with smart search capabilities.

A meta-MCP server that uses Llama AI as an orchestrator to intelligently route requests and coordinate workflows across multiple MCP services like Stripe, GitHub, and databases. Enables complex multi-service operations with AI-driven decision making and parallel execution capabilities.

Enables browsing, searching, and importing sessions from multiple coding agents into the current one, or reopening them in their native agent, all locally and read-only.