Multi LLM Cross Check MCP Server

Created By
lior-psa year ago
Overview

what is Multi LLM Cross-Check MCP Server?

Multi LLM Cross-Check MCP Server is a Model Control Protocol (MCP) server that enables users to cross-check responses from multiple LLM (Large Language Model) providers simultaneously, providing a unified interface for querying different LLM APIs.

how to use Multi LLM Cross-Check MCP Server?

To use the server, clone the repository, set up the environment, and configure it in Claude Desktop with your API keys. Once configured, the server starts automatically when you open Claude Desktop, allowing you to use the cross_check tool in your conversations.

key features of Multi LLM Cross-Check MCP Server?

  • Query multiple LLM providers in parallel (OpenAI, Anthropic, Perplexity AI, Google)
  • Asynchronous processing for faster responses
  • Easy integration with Claude Desktop
  • Error handling for API key issues and independent responses from each LLM

use cases of Multi LLM Cross-Check MCP Server?

  1. Comparing responses from different LLMs for accuracy.
  2. Enhancing the quality of generated content by leveraging multiple AI sources.
  3. Researching diverse perspectives on a given prompt.

FAQ from Multi LLM Cross-Check MCP Server?

  • What LLM providers are supported?

Currently supports OpenAI, Anthropic, Perplexity AI, and Google.

  • Do I need API keys for all providers?

No, you only need to provide API keys for the providers you wish to use; others will be skipped.

  • Is the server free to use?

Yes, the server is free to use, but you will need to have valid API keys for the LLM providers.

Project Info
Created At
a year ago
Updated At
a year ago
Author Name
lior-ps
Star
-
Language
-
License
-

Recommend Servers

View All
//beforeyouship — LLM Cost Modeling From Your Editor
@Indiegoing

Query realistic LLM cost models without leaving your editor. beforeyouship models the **true monthly cost** of an LLM app architecture — retries, prompt caching, batch discounts, infra overhead, and 3×/10× growth — across GPT-5.x, Claude, Gemini, DeepSeek, and more. Not a token calculator: a planning tool for the design phase, before you commit to a stack. **No API key needed to try it** — demo mode covers the six free-tier models. A Pro key from [beforeyouship.dev](https://beforeyouship.dev) unlocks the full 18-model catalog. ## What you can ask - "How much will a RAG chatbot cost at 10,000 requests/day?" - "Compare Claude Haiku vs Gemini Flash pricing for my workload" - "What's the cheapest model for a multi-step agent at scale?" - "Show me current per-token prices for Anthropic models" ## Tools ### `estimate_cost` Full cost model for an architecture at a given usage level. Returns Naive / Realistic / Worst Case monthly cost per model, 3×/10× growth scenarios, and an opinionated recommendation with reasoning. ### `get_model_prices` Current per-1M-token pricing — input, output, cached input, batch — with context windows and staleness metadata. ### `list_archetypes` Seven preset architecture patterns (simple chatbot, chatbot with history, RAG pipeline, multi-model router, coding assistant, document processor, multi-step agent) used as starting points for estimates. ## Setup **Claude Code:** ​```bash claude mcp add --transport http beforeyouship https://beforeyouship.dev/api/mcp ​``` **Cursor / other clients** — add a remote server: ​```json { "mcpServers": { "beforeyouship": { "type": "streamable-http", "url": "https://beforeyouship.dev/api/mcp" } } } ​``` Add an `Authorization: Bearer bys_...` header with a Pro key for the full catalog. ## Try it > Estimate the monthly cost of a RAG pipeline at 10,000 requests/day

16 hours ago