"A server for interacting with a large language model chat" matching MCP servers:

Enables AI coding agents to request a second opinion from a different frontier model via a single tool call, with PII scrubbed before transit, live web search, and support for Claude, ChatGPT, Cursor, and Gemini.

Enables AI agents to request an independent second opinion from a different frontier model, with PII scrubbing before transit, live web search grounding, caching, and multi-provider failover.

An MCP server that turns the Hugging Face Hub into a conversational model picker with a tool-use eval harness to prove the agent actually uses it correctly.

Enables coding agents to add a bounded semantic-judgment layer for routing, ranking, extraction, verification, and escalation, returning typed signals and review recommendations.

Enables AI-to-AI consultation for critical thinking and complex reasoning via OpenRouter, allowing one AI to delegate tasks to another AI model.

Enables AI agents to identify what language text is written in, returning top matches, confidence scores, script detection, and character statistics via a pay-per-call x402 API without requiring an API key.

Enables interactive AI chat through the Anthropic API, with document retrieval, slash commands, and extensible MCP tool integrations.

Scores submitted prose against the FAA plain-language standard and returns it rewritten to the pass bar, exposing score_prose and improve_prose tools that report findings, a numeric score, and the best-scoring rewrite.

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.

An MCP server that seats multiple LLMs as a council, letting your assistant query them in parallel or in sequence, relay answers for cross-critique, and merge conclusions within one conversation.

MCP server that pings 130+ free coding LLM models across 17 providers in real-time, ranks them by latency, and helps AI agents pick the fastest available model.

Discovers local model runtimes such as Ollama, LM Studio, and LocalAI, and exposes their endpoint metadata to MCP clients like Copilot.

Enables AI coding agents to offload large file reads and boilerplate code generation to cheaper or local worker models through MCP, reducing token consumption and keeping context clean.

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.

Provides AI agents with a toolset to query model inventories, trace dependencies, and analyze the impact of changes across machine learning models and data pipelines.

Enables language models to receive external randomness so the same prompt can produce different answers while still following the user's request.

Cost-aware multi-LLM routing MCP server that automatically routes tasks to free models first with fallback to paid, using task difficulty classification.

Routes subagent tasks across Claude and OpenAI lanes by task kind and quota state, deciding whether to spawn a single model, run a duel of both vendors, or run both and ship the merge. It records duels with attested proof-of-run session ids, grades sides blind with one judge per vendor, and tracks per-kind standings and lane pacing.

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.

MCP server for discovering and cataloging generative AI models, enabling agents to search by modality, view pricing/terms, and manage contracts with providers via Beckn-aligned APIs.

Routes questions to multiple AI models (local and cloud) and synthesizes their answers in individual, categorized, or deconflicted modes.

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.

Enables MCP-compatible clients to call TokenHub's image generation and editing APIs through natural language, supporting text-to-image, image-to-image, and configurable model and endpoint settings.

Provides up-to-date AI model names and pricing from models.dev, solving model hallucination by fetching recently released models.

Exposes product-style completion tools (OpenAI chat-completions-shaped and Anthropic messages-shaped) that are fulfilled by sampling the host agent's own LLM over MCP, so no model API keys are ever needed. Also offers a model listing endpoint aliasing the host's model.

Enables MCP clients to query live OpenRouter LLM pricing and monthly price history back to 2023 without API keys. It supports finding the cheapest model for a job, estimating workload costs, tracking price changes, and comparing providers.

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 users to scan Hugging Face for Apple-MLX models, estimate memory fit and decode speed for their Mac, and get ranked recommendations for a use case, with all agent work running locally.