"Information about SVG (Scalable Vector Graphics)" matching MCP servers:

A production-grade MCP server for integrating RAG into AI agents, supporting multiple vector databases with enterprise security and dynamic tool selection.

Enables agents to stamp events with vector clocks, resolve state via LWW CRDT reconciliation, and coordinate distributed swarms through token-bucket gossip, Raft leader/quorum voting, and two-phase commit. It runs over MCP with zero external dependencies, delivering deterministic happens-before causal ordering and convergence across agent networks.

A semantic proxy that reduces AI agent token usage by exposing only three core tools and using local vector embeddings to search for and execute hundreds of underlying MCP tools. It streamlines communication between agents and MCP Routers by identifying relevant tools through natural language queries.

A Model Context Protocol (MCP) server that provides intelligent search capabilities for discovering relevant Claude Agent Skills using vector embeddings and semantic similarity. This server implements the same progressive disclosure architecture that Anthropic describes in their Agent Skills enginee

Central registry for AI tools with vector search and knowledge graph, enabling intelligent tool discovery, chaining, and execution via MCP.

Search and discover AI agents, skills, prompts, bundles and MCP connectors from a curated catalog of 4500+ assets. Provides tools for searching, browsing categories, and accessing detailed information about each asset.

Provides AI assistants with real-time access to the AGNO framework documentation by enabling them to browse, search, and fetch documentation pages. This server allows users to query information about AGNO's Agents, Teams, and Workflows directly through MCP-compatible clients.

A Model Context Protocol server that enables scalable mobile automation for iOS and Android through a platform-agnostic interface, allowing LLMs to interact with mobile applications via accessibility snapshots or screenshot-based inputs.

A persistent memory implementation using a local knowledge graph that lets Claude remember information about users across conversations.

Welcome to Hyperbrowser, the Internet for AI. Hyperbrowser is the next-generation platform empowering AI agents and enabling effortless, scalable browser automation. Built specifically for AI developers, it eliminates the headaches of local infrastructure and performance bottlenecks, allowing you to

The AgentOps MCP server provides access to observability and tracing data for debugging complex AI agent runs. This adds crucial context about where the AI agent succeeds or fails.

A Model Context Protocol server that enables scalable mobile automation through a platform-agnostic interface for iOS and Android devices, allowing agents and LLMs to interact with mobile applications using accessibility snapshots or coordinate-based interactions.

A Model Context Protocol server that provides a scalable backend solution for efficient interaction with Medusa's data models through the JavaScript SDK.

An advanced contextual memory server for agent orchestration providing chronological history, semantic vector search via Redis Stack, and temporary scratchpad storage. It also enables context compression through history rollups and facilitates inter-agent communication using a Redis-based Pub/Sub system.

Official Kimss MCP server — call your Kimss agents, models, files, and vector stores from Cursor and other MCP clients using your API key.

A distributed MCP server framework enabling scalable task execution across multiple nodes with streamable HTTP transport, integrated authentication, and real-time streaming via the Asgard infrastructure.

A server that enables AI models to access user geolocation information via EdgeOne Pages Functions through the Model Context Protocol.

A transparent message ferry between Claude Desktop and Claude Code CLI, enabling task delegation with any MCP configuration without the bridge needing to know about specific MCPs.

Enables real-time communication and shared vector memory between Claude Code, OpenAI Codex CLI, and Google Gemini CLI. It allows different AI platforms to exchange messages, share context, and collaborate through a unified MCP interface.

A Python MCP server on Cloudflare implementing the stateless MCP 2026-07-28 protocol, enabling load-balanced and scalable tool execution without session affinity.