"Artifacts capabilities and features" matching MCP servers:

Provides a standardized protocol for tool invocation, enabling an AI system to search the web, retrieve information, and provide relevant answers through integration with LangChain, RAG, and Ollama.

A multi-tool AI assistant system that uses Model Context Protocol to connect language models with various tools, including math calculations and weather information.

Provides structured dealer brand data including inventory, promotions, reviews, and dealer profile via MCP tools, enabling LLMs to answer accurate brand-related queries.

A meta-MCP server that acts as a universal gateway, allowing users to discover and execute tools from thousands of other MCP servers through semantic search. It dynamically loads servers on demand and provides standardized functions for searching, discovering, and running tools across the entire MCP ecosystem.

Enables Codex to rank available tools and skills, rerank code and documentation search results, and triage saved output artifacts using Jev-based relevance scoring while leaving final decisions to Codex.

An MCP server that enables LLMs to pull-based search through Clawket's RAG repository for exploratory and conditional queries. It provides read-only access to search artifacts, tasks, and decisions via HTTP API.

Enables read-only access to a local-first catalog of portable agent skills, exposing tools to discover ranked matches, inspect stored artifacts, traverse declared relationships, and view configuration.

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.

A Model Context Protocol server that provides AI assistants with access to Glean's enterprise knowledge features, including content search, people directory, and AI chat capabilities.

A server enabling integration between KoboldAI's text generation capabilities and MCP-compatible applications, with features like chat completion, Stable Diffusion, and OpenAI-compatible API endpoints.

A Model Context Protocol server implementation that enables seamless integration with Claude and other MCP-compatible clients to access Prem AI's language models, RAG capabilities, and document management features.

A persistent AI memory server that enables storage and retrieval of context and project artifacts across conversations. It features full-text search, version history, and automatic content chunking using local SQLite or hosted cloud storage.

Local-first MCP server for querying multi-repo engineering documentation artifacts from a SQLite corpus.

An MCP server that integrates the Brave Search API to provide both web and local search capabilities, with features like pagination, filtering, and smart fallbacks.

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.

Provides AI agents with a comprehensive web intelligence stack including crawling, private search via SearXNG, and intelligent RAG capabilities for focused content extraction. It supports advanced features like semantic vector search and knowledge graph integration for code validation to enhance AI performance and reliability.

Pinecone integration with vector search capabilities

Enables advanced OpenAI GPT model integration with Claude through 5 specialized tools including GPT-5 reasoning, token optimization, context management, batch processing, and model comparison. Features intelligent fallback mechanisms and task-specific system prompts for enhanced AI capabilities.

Provides AI assistants with safe, controlled access to PostgreSQL databases with read-only defaults, granular permissions, query safety features, and schema introspection capabilities.

A production-grade MCP server and client implementation with comprehensive features including structured logging, health checks, metrics, authentication, and RAG capabilities with PostgreSQL vector search. Supports both stdio and SSE transports with containerization and security features for enterprise deployment.