> ## Documentation Index
> Fetch the complete documentation index at: https://docs.monolex.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# MCP Platform

> MCP brings the data. OpenCLIs refines it for AI. CLI + MCP hosting with context refinement.

# OpenCLIs MCP Platform

**MCP brings the data. OpenCLIs refines it for AI.**

OpenCLIs is a platform where developers register MCP services without deploying infrastructure. Authentication, hosting, caching, content refinement, and trust scoring — all provided. Developers bring their data; openclis makes it AI-ready.

## The Problem

MCP responses are 70-90% metadata. AI agents pay tokens for UUIDs, timestamps, and formatting that carry no information. A Notion page costs 3,750 tokens through MCP — the actual content is 625 tokens.

## The Solution

```
Any MCP Source → OpenCLIs Refiner → AI gets only what it needs

Notion (15,000 chars) → extract → index → cache → 200 tokens (95% saved)
GitHub (12,000 chars) → extract → index → cache → 150 tokens
Slack  (8,000 chars)  → extract → index → cache → 100 tokens
```

## Platform Services

| Service      | URL               | Purpose                                |
| ------------ | ----------------- | -------------------------------------- |
| **Auth**     | auth.openclis.com | OAuth 2.1 + developer registration     |
| **MCP**      | mcp.openclis.com  | MCP protocol access (AI tools)         |
| **REST**     | rest.openclis.com | REST API access (CLI, curl)            |
| **Registry** | api.openclis.com  | CLI tools + domain trust (281 domains) |

## For Developers

Register a service in 4 API calls. No server deployment. No code changes to openclis.

```
1. Register account     → API key
2. Register service     → MCP endpoint created
3. Define tools         → What your service does
4. Set backend URL      → Where requests go (your webhook)

Done. mcp.openclis.com/your-service is live.
```

### Plugin System

Everything is data, not code:

* **Extractor rules**: D1 templates that convert API responses to markdown
* **Handler types**: kv\_store, proxy, refiner, workspace, webhook
* **AI spec**: Metadata that helps AI choose the right service
* **OpenAPI auto-generation**: Register your API URL, tools are created automatically

### Third-Party Auth

Your users authenticate with your auth system (Supabase, Firebase, Auth0, custom). openclis delegates validation to your URL. We never see your users' credentials.

## For AI Agents

Two ways to access any service:

**MCP** (Claude Code, Cursor):

```
POST mcp.openclis.com/workspace
→ JSON-RPC + schema load → ~1200 tokens
```

**REST/CLI** (Bash, curl):

```
GET rest.openclis.com/workspace/search?query=MCP
→ plain JSON → ~200 tokens
```

Same data. Same auth. 6x fewer tokens via REST.

## Trust Registry

281 domains scored for AI content trust. Ed25519 signed.

```
doc.rust-lang.org    → 0.95 [verified,lang-docs]
stackoverflow.com    → 0.60 [community,qa]
medium.com           → 0.35 [external,blog]
```

AI agents check source trustworthiness before relying on external content.

## Current Status

**Live and operational.** Not accepting public signups yet.

What's working:

* 5 MCP services (niia, notion, consciousness, obsidian, workspace)
* Notion + Obsidian unified workspace search
* Supabase third-party auth integration tested
* Webhook plugin system tested (weather service demo)
* 281 trusted domains, Ed25519 verified
* REST + MCP dual access

## Early Access

If you're building AI CLI tools or MCP services and want to test the platform, contact us:

* **Email**: [dev@monolex.ai](mailto:dev@monolex.ai)
* **GitHub**: github.com/monolex

We're looking for developers who want to:

* Host MCP services without infrastructure
* Reduce AI token costs with context refinement
* Integrate existing APIs as MCP tools (OpenAPI auto-generation)
* Test third-party auth integration