MCP-CLIENT-CHATBOT

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

The second fastest AI chatbot™

Community Internal MCP server for Airtable - 30 tools for schema inspection, field CRUD (formula, rollup, lookup, count), view configuration, formula validation, and extension management. Not affiliated with Airtable Inc.

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.

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.

Fast, intuitive AI image generation platform for everyday creative inspiration.

The new purpose-built IDE to harness magic

# archon-mcp-client A completely silent, standards-compliant [Model Context Protocol (MCP)](https://modelcontextprotocol.io/) client bridge that natively proxies Claude Desktop `stdio` requests directly into an Archon `SSE` remote backend over HTTPS. Unlike other public MCP proxies, this package guarantees complete `stdout` JSON-RPC hygiene, preventing log pollution that crashes Claude Desktop's strict parsers. ## Usage You do not need to install this library. Just configure your `claude_desktop_config.json` to execute it remotely via `npx`. Find more information and full documentation at [https://archonspecs.dev/docs.html](https://archonspecs.dev/docs.html). ```json { "mcpServers": { "archon-mcp": { "command": "npx", "args": [ "-y", "archon-mcp-client", "https://archonspecs.dev/mcp/sse?apiKey=your_api_key_here" ] } } } ```

Lettr is transactional email API for artisans. Send, recieve and track all you transactional emails. With easy-to-use template builder included.

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.

⏩ 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

Image to Image AI is an AI image and video platform that lets you transform reference images or generate new ones from text. Upload one or several images, add a prompt, and get high-quality outputs in multiple aspect ratios (1:1, 16:9, 9:16, etc.) and resolutions (1K, 2K, 4K). It runs on AI Best and supports 9+ models including Nano Banana, Nano Banana Pro, GPT-4o Image, Flux Kontext, and video models like Veo. Use it for product shots, social content, concept art, or marketing—with sharper 2K imagery, 4K scaling, better text in images, and consistent characters.

## 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`

Persistent semantic memory for Claude Code, chats AND code. 74+ MCP tools, local pgvector embeddings, codebase indexing with 14 language extractors, multi-agent team coordination. Self-hosted, zero cloud dependency.

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.

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

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.