# Cortensor MCP
An MCP server that plugs Claude, Cursor, and other AI assistants directly into Cortensor's decentralized inference network. Session persistence, task orchestration, and validation tools included.
## Why Cortensor MCP?
### The Problem
AI agents lack:
- Persistent memory across conversations
- Access to decentralized inference networks
- Structured task orchestration tools
- Built-in validation and consistency checking
### Our Solution
Cortensor MCP provides a unified interface that:
- **Persists** session memory using Cloudflare Durable Objects
- **Connects** AI assistants to Cortensor's decentralized network
- **Orchestrates** tasks with structured routing (analyze, summarize, extract, generate, validate, decide, plan)
- **Validates** outputs against rubrics and checks for logical consistency
**Result:** AI agents gain persistent memory, decentralized inference capabilities, and powerful validation tools—all through a single MCP server.
### Creating a Persistent Session
```
Create a new session for my research project with initial context about blockchain analysis
```
### Routing Tasks to Cortensor
```
Analyze this smart contract code and identify potential security issues
```
### Validating Content Against a Rubric
```
Validate this documentation against criteria: clarity, completeness, and accuracy
```
## Features
| Tool | Description |
|------|-------------|
| **session_create** | Create or retrieve an agent session with persistent memory |
| **session_remember** | Store information in session memory for later recall |
| **session_recall** | Retrieve stored information from a session |
| **task_route** | Route structured tasks to Cortensor with output formatting |
| **validate_rubric** | Validate content against a weighted scoring rubric |
| **validate_consistency** | Check content for contradictions and logical issues |
| **research_analyze** | Analyze code, docs, or issues and extract actionable items |
| **research_summarize** | Generate digest, changelog, or status reports from multiple items |
| **cortensor_status** | Check Cortensor network connectivity and latency |
| **cortensor_infer** | Direct inference request to Cortensor network |
## Setup Guide
### 1. Clone and Install
```bash
git clone https://github.com/SuReaper/cortensor-mcp.git
cd cortensor-mcp
npm install
```
### 2. Run Locally or Deploy
```bash
# Local development
npx wrangler dev
# Production deployment
npx wrangler deploy
```
## MCP Configuration
Add to your MCP settings (Roo Code / Cline / Claude Desktop):
```json
{
"mcpServers": {
"cortensor": {
"type": "sse",
"url": "https://your-worker.workers.dev/sse",
"alwaysAllow": [
"session_create",
"session_remember",
"session_recall",
"task_route",
"validate_rubric",
"validate_consistency",
"research_analyze",
"research_summarize",
"cortensor_status",
"cortensor_infer"
],
"timeout": 300
}
}
}
```
## Task Types
| Type | Behavior |
|------|----------|
| `analyze` | Identify patterns and insights |
| `summarize` | Concise summary, preserve key info |
| `extract` | Extract data points and entities |
| `generate` | Generate content from requirements |
| `validate` | Check correctness, flag issues |
| `decide` | Reasoned decision with explanation |
| `plan` | Actionable steps with priorities |
