Cortex
Provides a Telegram bot bridge that allows users to interact with their local AI agent remotely, enabling session management, command routing, and concurrent task handling from a phone.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@CortexWhat did we learn from yesterday's debugging session?"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Claude Code, Cursor, Windsurf — your AI coding agent is powerful, but isolated. It can't be reached from your phone. It can't talk to other agents. It can't build its own tools. And it forgets everything between sessions.
Cortex fixes all four.
It's a set of independent Python packages that plug into any MCP-compatible agent via the standard Model Context Protocol. No vendor lock-in, no platform to adopt — just pip install the capabilities you need.
┌──────────────────────────────────────────────┐
│ CORTEX (plug-in layer) │
│ │
│ Dispatcher A2A Hub Forge Memory Replay │
│ (command) (comms) (tools) (recall) (capture)│
└──────────────────┬─────────────────────────────┘
│ MCP + hooks
┌──────────────────▼─────────────────────────────┐
│ Your Agent (Claude Code / Cursor / etc.) │
└────────────────────────────────────────────────┘Components
Package | Problem | Solution | Status | Install |
Can't reach your agent from your phone | Telegram bot that bridges to your local agent — sessions, routing, concurrent tasks | Beta |
| |
Agent can't build its own tools | Describe a tool in English → generates code → runs tests → iterates up to 5x → installs it | Alpha |
| |
Agents can't discover or delegate to each other | WebSocket hub + MCP bridge for agent-to-agent communication | Alpha |
| |
Sessions are ephemeral — decisions and learnings are lost | Auto-captures sessions via hooks, extracts phases/decisions/patterns, generates interactive HTML replays | Alpha |
| |
Agent forgets everything between sessions | Semantic memory store — LLM extraction + vector search via MCP | Alpha |
|
Each package is independently installable and useful on its own. No coupling between components.
Related MCP server: Cognitive Core
Quick Start
# Install one component
pip install agent-dispatcher
dispatcher init # interactive setup — Telegram bot token, project paths
dispatcher start # your agent is now reachable from your phone
# Or install everything
pip install cortex-cli-agent[all]
cortex init # sets up MCP servers, hooks, Telegram
cortex status # health check all componentsHow It Works: MCP Plug-ins
Every Cortex component is an MCP server. Add one line to your agent's config and it gains new abilities:
{
"mcpServers": {
"forge": { "command": "forge-mcp" },
"a2a-hub": { "command": "a2a-hub", "args": ["bridge"] },
"memory": { "command": "python3", "args": ["-m", "memory.server"] }
}
}Now your agent can do things it couldn't before:
You: "I need a tool that validates YAML configs against a schema"
→ Claude calls Forge → generates code → runs tests → installs the tool
You: "Delegate the code review to the review agent"
→ Claude calls A2A Hub → discovers agents → sends the task → gets results
You: "What did we learn from yesterday's debugging session?"
→ Claude calls Memory → semantic search → returns relevant learningsThe agent doesn't know these are plug-ins — they appear as native capabilities through the MCP protocol.
Architecture
┌─────────────────────────────────────────────────────────────────────┐
│ cortex-cli (orchestrator) │
│ cortex init / cortex status │
├────────────┬────────────┬──────────────┬──────────────┬─────────────┤
│ │ │ │ │ │
│ Dispatcher │ A2A Hub │ Forge │ Vibe Replay │ Memory │
│ │ │ │ │ │
│ Telegram │ WebSocket │ Desc → Gen │ Hook-based │ Semantic │
│ → Agent │ hub for │ → Test → Fix │ capture → │ search + │
│ bridge │ agent-to- │ → Install │ analyze → │ LLM │
│ │ agent │ (MCP/CLI/ │ HTML replay │ extraction │
│ Sessions, │ comms │ module) │ │ │
│ routing, │ │ │ Decisions, │ MCP server │
│ memory │ MCP bridge │ 5x iterate │ patterns, │ for agents │
│ │ for agents │ loop │ wisdom │ │
├────────────┼────────────┼──────────────┼──────────────┼─────────────┤
│ MCP │ MCP │ MCP │ MCP + Hooks │ MCP │
└────────────┴────────────┴──────────────┴──────────────┴─────────────┘
│
plugs into any MCP host
│
┌───────────────▼───────────────────┐
│ Claude Code / Cursor / Windsurf │
└───────────────────────────────────┘For detailed architecture documentation, see docs/ARCHITECTURE.md.
Design Principles
Plug-in, not platform — extends your existing agent, doesn't replace it
Each component stands alone — install one or all, no coupling
MCP-first — every component is an MCP server, one JSON line to connect
No external services — SQLite, JSONL, local WebSocket — everything runs on your machine
Fail-safe — capture hooks are non-blocking; if Cortex fails, your agent keeps working
Project Structure
cortex/
├── packages/
│ ├── cortex-cli/ # Umbrella CLI — setup, status, health checks
│ ├── dispatcher/ # Telegram → agent bridge (Beta, 310 tests)
│ ├── a2a-hub/ # Agent-to-Agent protocol hub (Alpha, 80 tests)
│ ├── forge/ # Self-evolving tool generation (Alpha, 120 tests)
│ ├── vibe-replay/ # Session capture & replay (Alpha, 50 tests)
│ └── memory/ # Semantic memory module (Alpha, 30 tests)
├── docs/ # Architecture guide
├── examples/ # Walkthroughs
├── pyproject.toml # uv workspace
└── CONTRIBUTING.md # How to contributeDevelopment
git clone https://github.com/zzhiyuann/cortex.git
cd cortex
uv sync --all-packages # install all packages in dev mode
uv run pytest # all 600+ tests
uv run pytest packages/dispatcher/tests/ # one package
uv run ruff check packages/ # lintSee CONTRIBUTING.md for the full guide.
Status
Cortex is early-stage open source. The Dispatcher is in beta (daily driver for the author); other components are alpha. APIs may change. Contributions and feedback are very welcome.
License
MIT — see LICENSE.
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