ADHAM

**Myriade** is the AI-native data platform for exploring, cataloging, and governing data warehouses. This MCP server exposes Myriade's data analyst capabilities to any compliant client (Claude Desktop, Cursor, VS Code, Copilot, etc.). Once connected, your AI client can: - **Discover** — `list_databases`, `list_tables`, `get_table_schema`, `get_database_info` - **Sample & query** — `sample_data`, `query` (read-only, governance-enforced) - **Browse the catalog** — `search_catalog`, `read_asset`, `update_asset` (descriptions, tags, status) - **Ask the analyst** — `ask` runs Myriade's data analyst agent end-to-end on a natural-language question, returning a synthesized answer with deep links into the Myriade UI for queries, charts, and documents All requests are scoped to the authenticated user's organization, run in read-only mode, and respect Myriade's governance policies (PII masking, table-level ACLs). **Auth:** OAuth 2.1 with Dynamic Client Registration. Sign in once with your Myriade account; tokens are scoped to your org. **Self-host:** Available — see https://github.com/myriade-ai/myriade-private for setup. The hosted version at `app.myriade.ai` is the easiest way to try it.

Gateway connector between LLM agents and world data. Official Model Context Protocol server for the Sugra API, backed by a bundled endpoint catalog and operation_id calls. Works with Anthropic Claude, OpenAI GPT, Google Gemini, xAI, and any MCP-enabled IDE. Client details: Anthropic Claude: Claude Desktop, Claude Code (CLI), claude.ai (web) OpenAI GPT: ChatGPT (via MCP connector) Google Gemini: Gemini CLI, Gemini Code Assist (VS Code + JetBrains) xAI: Remote MCP Tools in xAI SDK and Responses API IDEs: VS Code (native), Cursor, Zed, Cline, Continue.dev, Windsurf Custom agents: anything built on the Python or TypeScript MCP SDK

MCPMate is a comprehensive Model Context Protocol (MCP) management center designed to address configuration complexity, resource consumption, security risks, and other issues in the MCP ecosystem, providing users with a unified management platform.

Lutra is the first MCP compatible client built for everyone

Persistent cloud memory for AI coding agents. 14 MCP tools — store, recall, semantic search, knowledge graph. Works with Claude Code, Cursor, Windsurf, OpenClaw. One config file, zero SDK.

## Overview ### what is Chain.Love MCP? Chain.Love MCP is a hosted remote MCP server and gateway for AI agents. It provides a single endpoint for discovering and comparing Web3 infrastructure services across 50+ blockchain networks, including RPCs, indexing, oracles, storage, compute, and developer tools. ### how to use Chain.Love MCP? To use Chain.Love MCP, add the hosted endpoint to your MCP client and connect to `https://app.chain.love/mcp` over Streamable HTTP. For public use cases, the basic MCP server URL is enough. For private downstream MCPs, add credentials only when required using `x-chainlove-cred-<credentialKey>` headers. ### key features of Chain.Love MCP? - Hosted remote MCP gateway for AI agents - Single endpoint for Web3 infrastructure discovery across 50+ blockchain networks - Aggregates infrastructure options across RPCs, indexing, oracles, storage, compute, and developer tools - Streamable HTTP transport - Public documentation and onboarding resources available online ### use cases of Chain.Love MCP? - Discovering and comparing Web3 infrastructure providers across many blockchain networks - Finding RPC, indexing, oracle, storage, compute, and developer tooling options through one MCP server - Giving AI agents a single hosted integration surface for Web3 infrastructure discovery - Reducing the need to integrate many separate provider-specific endpoints ### FAQ from Chain.Love MCP? - Can Chain.Love MCP be used as a hosted remote MCP server? Yes. Chain.Love MCP is designed to be consumed as a hosted remote MCP endpoint at `https://app.chain.love/mcp`. - Does Chain.Love MCP require credentials? Not always. Some downstream integrations may require credentials, which can be passed using `x-chainlove-cred-<credentialKey>` headers when needed. - How do I know which credential header to use? You can check the open-source Chain.Love registry at `https://github.com/Chain-Love/chain-love/blob/main/references/offers/mcpservers.csv` or browse `https://app.chain.love/toolbox/mcpservers` and look for the relevant `credentialKey` value. - Where can I learn more? Landing page: `https://www.chain.love/mcp-gateway` Documentation: `https://chain-love.gitbook.io/mcp-module`

MCP (Model Context Protocol) Server for Sychev Lab - provides access to products, articles, tutorials, and e-commerce features located in https://lab.sychve.xyz

Open-source AI Agent for VS Code and JetBrains that autonomously solves coding tasks end-to-end.

A transparent desktop overlay that gives your AI agent a visual presence on screen. Your AI picks its own body from a library of avatars, colors, and expressions or draws it's own in SVG. Windows, $4.99, 7-day free trial, no account required.

⏩ Create, share, and use custom AI code assistants with our open-source IDE extensions and hub of models, rules, prompts, docs, and other building blocks

A Tiny Terminal Chat App for AI Models with MCP Client Support

Claude Fable 5: Anthropic's first public Mythos-class model, explained

MCP server for German & EU law. Verified, citable legal context for any LLM. Daily updates from official sources, hosted in Germany

test

Premium AI image suite offering advanced fine-tuning and professional editing tools.

Explorer-first MCP client that renders any MCP server's tools as interactive UI — no LLM required, no tool-calling loop. Point it at any MCP server over stdio or SSE and get cards, tables, charts, forms, pipelines, and dashboards auto-generated from your tool outputs. Install with `npx burnish -- <your-mcp-server>`.

Code at the speed of thought – Zed is a high-performance, multiplayer code editor from the creators of Atom and Tree-sitter.

A standalone Python/FastAPI server that implements the Model Context Protocol (MCP) for the OPTIX threat intelligence platform. It exposes 26 analyst-friendly tools that AI assistants and programmatic consumers can use to query threat feeds, search documents and indicators, manage watchlists, triage IOCs, generate detection rules, trigger AI research, and produce intelligence reports — without needing to understand OPTIX's internal REST API.