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HyperChat is a Chat client that strives for openness, utilizing APIs from various LLMs to achieve the best Chat experience, as well as implementing productivity tools through the MCP protocol.

Streamlined AI music engine for custom soundtracks, beats, and thematic background scores.

Visual Studio Code

Apigene MCP Gateway & MCP Client is the runtime layer that connects AI agents to APIs and MCP servers via Model Context Protocol. Key features: • Unified access to 100s of APIs and MCP servers through one gateway • No-code agent builder - configure via chat • Works with ChatGPT, Claude, Cursor, and custom apps • 10x faster tool calling with parallel execution • 99% output reduction with smart compression • Centralized governance, auth, and audit logs Turn any API into an MCP tool without custom code.

E2Easy is a codeless end-to-end testing platform that lets non-technical users and founders create, manage, and run automated browser tests without writing a single line of code. It combines a browser extension for manual recording with an AI-powered Claude Connector that lets you describe tests in plain English.

## 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`

Studio is where you run MCP tools in the browser against real credentials -- see inputs, outputs, and errors before you trust an agent. Enable bundles in your workspace, then add your Hub or per-bundle streamable HTTP URL in Cursor, Claude, ChatGPT, or VS Code. Workspace-scoped credentials; optional mcpbundles CLI on PyPI.

⏩ 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

Your Data. Your AI. Your Rules. Ontheia is a self-hosted, open-source AI agent platform. Run AI agents, automate workflows, and connect AI models to any tool — entirely on your own infrastructure, without sending data to external cloud services.

Ai arcade

Autonomous coding agent right in your IDE, capable of creating/editing files, executing commands, using the browser, and more with your permission every step of the way.

The new purpose-built IDE to harness magic

Context-optimized MCP server for DTC e-commerce brands. Connect Claude (or any MCP client) to your Klaviyo and Shopify data with 16 pre-built analytics tools. Unlike raw API wrappers, dtc-mcp pre-aggregates data server-side and returns only actionable fields — using ~80% less context than dumping raw API responses into your conversation. Features 8 Klaviyo tools — campaign performance, flow breakdowns, subscriber health, profile search, event activity 7 Shopify tools — sales summaries, daily/weekly/monthly trends, product performance, inventory alerts, customer cohorts, order search 2 cross-platform tools — email revenue attribution, full DTC health dashboard Dual revenue metrics — both gross and net revenue on every sales query Smart fallbacks — ShopifyQL when available, GraphQL pagination when not Aggressive caching — respects Klaviyo's strict rate limits (1 req/s on reporting)

MCPwner is a Model Context Protocol (MCP) server that integrates security testing tools into LLM-driven workflows. It provides a unified interface for secret scanning, static analysis (SAST), software composition analysis (SCA), and vulnerability research including 0-day discovery. Instead of manually chaining tools and pasting outputs into your LLM, MCPwner standardizes and streams results directly into the model's working context. This enables continuous reasoning, correlation, and attack path discovery across the entire security research lifecycle - from identifying known vulnerabilities to uncovering novel attack vectors.

Advanced multimodal AI music generator with realistic vocals and pro-level arrangements.