cross-llm-mcp
Access multiple Large Language Models via MCP server
Pricing
Free tier
Flat rate
Adoption
→StableLicense
Open Source
Data freshness
Aging · Jun 8, 2026Overview
What is cross-llm-mcp?
A Model Context Protocol (MCP) server that provides access to various LLM APIs including ChatGPT, Claude, DeepSeek, Gemini, and Grok, enabling developers to integrate diverse AI capabilities into their applications.
Key differentiator
“cross-llm-mcp stands out by offering a unified interface to access multiple LLM APIs, providing developers with the flexibility and control needed for diverse AI integration scenarios.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
API requires Python-specific patterns, TypeScript SDK is community-maintained
v0.1 to v0.2 migration required rewriting chain definitions
Official docs focus on basic setup and usage, lack examples for complex scenarios
Self-hosted instances may suffer from latency when handling multiple concurrent requests
GitHub issues have slow response times, few contributors to the project
Fit analysis
Who is it for?
✓ Best for
Teams that need to compare performance across different LLM APIs in a single environment
Developers who require flexibility in choosing between multiple models for specific tasks
Projects where self-hosting and control over the deployment are critical
✕ Not a fit for
Users requiring real-time streaming capabilities, as this tool is designed for batch processing
Budget-constrained projects that cannot afford to host their own MCP server
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Works well with
Next step
Get Started with cross-llm-mcp
Step-by-step setup guide with code examples and common gotchas.