"Integrating Web3 Wallet Functionality in AI Chat Applications" matching MCP servers:

Exposes a local DeepSeek Harness instance to external MCP clients over Streamable HTTP, legacy HTTP+SSE, or a stdio bridge. Enables creating sessions, running multi-turn conversations, reading and full-text searching history, cancelling running turns, and listing or selecting models.

MCP server that drives chat.sakana.ai via headless Chrome with persistent sessions. Enables AI assistants to interact with Sakana AI chat through tools like session management, with ToS gate and browser automation.

This MCP server enables interactive chat with AI models via the Anthropic API, supporting document retrieval and command-based prompts.

Enables interactive command-line chat with AI models via the Anthropic API, supporting document retrieval with @mentions and slash-command prompts with tab auto-completion.

Enables chat with Claude AI via terminal, supporting document retrieval, command-based prompts, and extensible tools through the Model Context Protocol.

WordPress plugin that runs an MCP server on your own site: search and read published posts and pages, look up WooCommerce products, describe the site as schema.org types and query site figures, with drafts only when the site enables them. Signed-in access by default; anonymous access and OAuth are optional and off.

A memory layer for AI coding tools that indexes transcripts from Claude Code, Gemini CLI, Codex, OpenCode, and Antigravity into a unified searchable history, providing 52 MCP tools for agents to recall past sessions, search across tools, and write back decisions.

Call OpenAI Codex from Claude Code for independent second opinions, structured code review, and delegated coding tasks through a FastMCP plugin that drives the codex CLI safely.

Lets any MCP host or OpenAI-compatible client chat with Meta's Muse (muse.ai Hatch) agent by driving your own logged-in Chrome, exposing tools for status, login, new chat, prompting, and reading replies. It also serves an OpenAI-compatible HTTP endpoint with real SSE streaming and prompt-injected tool calling, plus a small CLI for one-shot generation.

Enables AI clients to query web chats they are already signed in to, such as Perplexity, Gemini, ChatGPT, Claude, and DeepSeek, through the user's own Chrome via the DevTools Protocol. It provides prompt submission, session listing, cancellation, status diagnostics, and payload safety checks over local stdio without an HTTP server, tunnel, or browser extension.

Enables interactive chat with AI models and document retrieval via the Anthropic API, supporting command-based prompts and MCP tool integrations.

Enables users to describe their LLM fine-tuning job once and get the cheapest, fastest, and most balanced GPU options across a dozen cloud providers in seconds.

Renders Azure Content Understanding field schema as interactive table cards in VS Code Chat, enabling editing and persistence of field descriptions.

Enables chatting with an AI waifu character through MCP tools, with user management and dialog history.

Enables Codex to delegate code reviews, coding tasks, image/video generation, and background investigations to Grok via MCP tools.

AI-powered todo and calendar management using OpenAI and Google Calendar. Supports natural language commands in English and Turkish, with MCP endpoints for tool interactions.

Enables agents to inspect configured LLM models and send chat requests to them, with support for parameter overrides, file-based prompts, and output to files.

Enables users to describe an LLM fine-tuning workload and receive ranked, cost- and runtime-optimized GPU recommendations across multiple cloud providers by estimating VRAM and FLOPs.

Enables users to describe an LLM fine-tuning job once and receive the cheapest, fastest, or most balanced GPU hardware options across a dozen cloud providers by calculating required VRAM/FLOPs and aggregating live pricing.

Enables users to describe an LLM fine-tuning job and receive ranked, task-aware GPU recommendations with estimated VRAM/FLOPs, cost, and runtime across more than ten cloud providers.

Enables users to describe an LLM fine-tuning workload once and get task-aware VRAM/FLOPs estimates plus ranked cheapest, fastest, and balanced GPU recommendations across multiple cloud providers.

Enables users to describe an LLM fine-tuning job and receive the cheapest, fastest, or most balanced GPU options across multiple cloud providers by calculating required VRAM and FLOPs.

An MCP server that queries ChatGPT via the Codex CLI with real file context, read-only, and no length limits, enabling second opinions grounded in actual files.

Enables users to describe an LLM fine-tuning job and receive ranked GPU recommendations across a dozen cloud providers based on estimated VRAM/FLOPs, live pricing, cost, and speed. It returns cheapest, fastest, and balanced hardware options without manual comparison.

Enables users to describe an LLM fine-tuning workload once and get ranked, cost- and speed-optimized GPU recommendations across multiple cloud providers by estimating VRAM/FLOPs requirements.

MCP server for OpenAI ChatGPT API. Enables chat completions, vision analysis, embeddings, and model listing through natural language.

Enables users to describe an LLM fine-tuning job once and get ranked GPU hardware recommendations with estimated VRAM/FLOPs, cost, and runtime across a dozen cloud providers.

Multi-cloud MCP server that exposes cloud AI models as tools for AI CLI agents, supporting streaming, conversation history, parallel multi-model queries, and dynamic model discovery.

Enables users to describe an LLM fine-tuning job once and receive VRAM/FLOPs-aware recommendations for the cheapest, fastest, or most balanced GPU options across a dozen cloud providers.

It enables users to describe an LLM fine-tuning workload once and receive task-aware VRAM/FLOPs estimates plus ranked cheapest, fastest, or balanced GPU recommendations across multiple cloud providers.