Introduction to MCI
The Model Context Interface (MCI) is an open-source, platform-agnostic system that revolutionizes how you create and share AI agent tools. By leveraging simple JSON schemas, MCI enables developers to define collections of tools that work universally across programming languages and platforms.What is MCI?
Universal Tool Definition
Define AI tools using standardized JSON schemas that work in every programming language - Python, Node.js, Go, PHP, and beyond.
Multiple Execution Types
Support for HTTP, CLI, File, Text & MCP operations,
allowing you to wrap REST APIs, command-line tools, file operations, and
templates.
Built-in Authentication
Comprehensive authentication support including API Keys, Bearer
Tokens, Basic Auth, and OAuth2 - all configured declaratively.
Advanced Templating
Powerful template engine with environment variables, conditional logic (
@if), and iteration (@foreach) for dynamic tool execution.MCI transforms complex AI tool development into simple JSON configuration.
Your entire toolset fits in a single file thatβs easy to review, share, and
maintain.
Why Use MCI?
π Simplicity Over Complexity
Unlike complex server-based solutions, MCI tools are declarative JSON files that live directly in your project repository. No servers to maintain, no complex deployments - just clean, readable schemas.π Secure by Design
Your entire toolset is transparent and auditable. Every tool is defined in plain JSON that humans and AI can easily review. No black-box servers, no mysterious third-party code accessing your data.π Universal Compatibility
Write once, run everywhere. MCI works with any programming language because it uses operations available in every programming language - HTTP requests, CLI commands, file operations, and text processing.π¦ Maximum Flexibility
- Project-Wide Tools
- Agent-Specific Tools
- API Wrappers
- Mixed Sources
One
.mci.json file containing all tools for your entire project.How MCI Differs from MCP
| Aspect | MCI | MCP |
|---|---|---|
| Complexity | Simple JSON files | Full server implementations |
| Use Case | API/CLI wrappers, simple tools | Complex logic, stateful operations |
| Languages | Universal (JSON-based) | Language-specific servers |
| Sharing | A few files | Whole project |
| Review | Easy JSON audit | Full codebase review |
| Infrastructure | None required | Server infrastructure |
When to Choose MCI
π― Perfect for MCI
π― Perfect for MCI
- API Wrappers: Wrapping REST APIs with authentication
- CLI Tool Integration: Executing command-line tools
- Simple Workflows: File operations and text templating
- Rapid Prototyping: Quick tool development and iteration
- Easy Sharing: Tools that need to be shared across teams
- Security-Conscious: Environments requiring full auditability
β‘ Better with MCP
β‘ Better with MCP
- Complex Logic: Tools requiring sophisticated business logic
- Stateful Operations: Tools that maintain state across calls
- Real-time Features: Streaming or real-time data processing
- Custom Protocols: Non-standard communication requirements
- Performance Critical: High-throughput, low-latency operations
Quick Start Example
See MCI in action with this complete example:1
Create Your Schema
weather-tools.mci.json
2
Use in Python
3
Use in MCP client
Register
uvx mcix run to any MCI client such as Cluade desktop, Cursor, etc.4
Share Everywhere
Copy
weather-tools.mci.json to any project, any language. It just works!Whatβs Next: The MCI Ecosystem
MCI is rapidly evolving with an ambitious roadmap to make AI tool development
universally accessible.
π Language Adapters
Python β
Ready Now
Full-featured adapter with 92%+ test coverage and comprehensive authentication support.
Node.js π§
In Development TypeScript-first implementation with the same simple API.
Coming Q1 2024.
Go π
Planned High-performance Go implementation for system-level tools and
microservices.
PHP π
Planned Bringing MCI to the PHP ecosystem for web applications and CMS
integrations.
Rust π
Planned Ultra-fast Rust adapter for performance-critical applications.
Java π
Planned
Enterprise-ready Java implementation for large-scale applications.
π MCI Library
A centralized repository of community-contributed MCI tools:- Curated Collections: Pre-built tools for popular APIs (GitHub, Slack, AWS)
- Quality Assurance: All tools tested and documented
- Version Management: Semantic versioning for tool schemas
- Discovery: Search and browse tools by category and functionality
π¦ MCI Package Manager
Coming soon - a dedicated package manager for MCI tools:- Easy Installation
- Dependency Management
- Publishing
- Updates
π― Planned Features
Enhanced Template Engine
Enhanced Template Engine
Jinja2 Integration: Replace the current basic template engine with full Jinja2 support for more robust templating options.Include Directive: Add
@include("path/to/file.md") to simplify reusing prompt parts and templates.Advanced Authentication
Advanced Authentication
OAuth2 Flows: Complete OAuth2 implementation with refresh tokens and PKCE support.Dynamic Credentials: Runtime credential resolution and rotation.
Tool Composition
Tool Composition
Pipeline Tools: Chain multiple tools together in declarative workflows.Conditional Execution: Execute tools based on runtime conditions and previous results.
IDE Integration
IDE Integration
VS Code Extension: Syntax highlighting, validation, and debugging for MCI schemas.IntelliSense: Auto-completion and inline documentation for schema properties.
Getting Started
π Schema Reference
Complete documentation of the MCI JSON schema with examples and best
practices.
π Python Guide
Comprehensive Python adapter documentation with advanced usage patterns.
π¬ Join Community
Connect with other developers, share tools, and get help from the community.
Ready to revolutionize your AI development? MCI makes building powerful AI
tools as simple as writing JSON. Start with the quickstart guide and join
thousands of developers already using MCI.
