@byterover/cipher
v0.3.0TypeScript
Memory-powered AI agent framework with real-time WebSocket communication, MCP integration, and composable patterns
0/weekUpdated 5 months agoElastic-2.0Unpacked: 72.6 MB
Published by BYTEROVER
npm install @byterover/cipherCipher
Memory-powered AI agent framework with MCP integration
Overview
Cipher is an opensource memory layer specifically designed for coding agents. Compatible with Cursor, Windsurf, Claude Desktop, Claude Code, Gemini CLI, AWS's Kiro, VS Code, Roo Code, Trae, and Warp through MCP, and coding agents, such as Kimi K2. (see more on examples)
Built by Byterover team
Key Features:
- 🔌 MCP integration with any IDE you want.
- 🧠 Auto-generate AI coding memories that scale with your codebase.
- 🔄 Switch seamlessly between IDEs without losing memory and context.
- 🤝 Easily share coding memories across your dev team in real time.
- 🧬 Dual Memory Layer that captures System 1 (Programming Concepts & Business Logic & Past Interaction) and System 2 (reasoning steps of the model when generating code).
- ⚙️ Install on your IDE with zero configuration needed.
Quick Start 🚀
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``bashInstall globally
npm install -g @byterover/cipher
Or install locally in your project
npm install @byterover/cipher
`
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Show Docker Setup
bash
Clone and setup
git clone https://github.com/campfirein/cipher.git
cd cipherConfigure environment
cp .env.example .env
Edit .env with your API keys
Start with Docker
docker-compose up --build -dTest
curl http://localhost:3000/health
`> 💡 Note: Docker builds automatically skip the UI build step to avoid ARM64 compatibility issues with lightningcss. The UI is not included in the Docker image by default.
>
> To include the UI in the Docker build, use:
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bash
pnpm i && pnpm run build && npm link
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Show CLI commands
bash
Interactive mode
cipherOne-shot command
cipher "Add this to memory as common causes of 'CORS error' in local dev with Vite + Express."API server mode
cipher --mode apiMCP server mode
cipher --mode mcpWeb UI mode
cipher --mode ui
`> ⚠️ Note: When running MCP mode in terminal/shell, export all environment variables as Cipher won't read from
file.
>
> 💡 Tip: CLI mode automatically continues or creates the "default" session. Use /session new to start a fresh session._The Cipher Web UI provides an intuitive interface for interacting with memory-powered AI agents, featuring session management, tool integration, and real-time chat capabilities._
Configuration
Cipher supports multiple configuration options for different deployment scenarios. The main configuration file is located at
memAgent/cipher.yml.$3
Show YAML example
`yaml
LLM Configuration
llm:
provider: openai # openai, anthropic, openrouter, ollama, qwen
model: gpt-4-turbo
apiKey: $OPENAI_API_KEYSystem Prompt
systemPrompt: 'You are a helpful AI assistant with memory capabilities.'MCP Servers (optional)
mcpServers:
filesystem:
type: stdio
command: npx
args: ['-y', '@modelcontextprotocol/server-filesystem', '.']
`📖 See Configuration Guide for complete details.
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Create a
file in your project root with these essential variables:
Show .env template
`bash
====================
API Keys (At least one required)
====================
OPENAI_API_KEY=sk-your-openai-api-key
ANTHROPIC_API_KEY=sk-ant-your-anthropic-key
GEMINI_API_KEY=your-gemini-api-key
QWEN_API_KEY=your-qwen-api-key====================
Vector Store (Optional - defaults to in-memory)
====================
VECTOR_STORE_TYPE=qdrant # qdrant, milvus, or in-memory
VECTOR_STORE_URL=https://your-cluster.qdrant.io
VECTOR_STORE_API_KEY=your-qdrant-api-key====================
Chat History (Optional - defaults to SQLite)
====================
CIPHER_PG_URL=postgresql://user:pass@localhost:5432/cipher_db====================
Workspace Memory (Optional)
====================
USE_WORKSPACE_MEMORY=true
WORKSPACE_VECTOR_STORE_COLLECTION=workspace_memory====================
AWS Bedrock (Optional)
====================
AWS_ACCESS_KEY_ID=your-aws-access-key
AWS_SECRET_ACCESS_KEY=your-aws-secret-key
AWS_DEFAULT_REGION=us-east-1====================
Advanced Options (Optional)
====================
Logging and debugging
CIPHER_LOG_LEVEL=info # error, warn, info, debug, silly
REDACT_SECRETS=trueVector store configuration
VECTOR_STORE_DIMENSION=1536
VECTOR_STORE_DISTANCE=Cosine # Cosine, Euclidean, Dot, Manhattan
VECTOR_STORE_MAX_VECTORS=10000Memory search configuration
SEARCH_MEMORY_TYPE=knowledge # knowledge, reflection, both (default: knowledge)
DISABLE_REFLECTION_MEMORY=true # default: true
`> 💡 Tip: Copy
to .env and fill in your values:
>
> `bash
> cp .env.example .env
> `MCP Server Usage
Cipher can run as an MCP (Model Context Protocol) server, allowing integration with MCP-compatible clients like Claude Desktop, Cursor, Windsurf, and other AI coding assistants.
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To use Cipher as an MCP server in your MCP client configuration:
json
{
"mcpServers": {
"cipher": {
"type": "stdio",
"command": "cipher",
"args": ["--mode", "mcp"],
"env": {
"MCP_SERVER_MODE": "aggregator",
"OPENAI_API_KEY": "your_openai_api_key",
"ANTHROPIC_API_KEY": "your_anthropic_api_key"
}
}
}
}
`📖 See MCP Integration Guide for complete MCP setup and advanced features.
👉 Built‑in tools overview — expand the dropdown below to scan everything at a glance. For full details, see
📘.
Built-in Tools (overview)
- Memory
-
cipher_extract_and_operate_memory: Extracts knowledge and applies ADD/UPDATE/DELETE in one step
- cipher_memory_search: Semantic search over stored knowledge
- cipher_store_reasoning_memory: Store high-quality reasoning traces
- Reasoning (Reflection)
- cipher_extract_reasoning_steps (internal): Extract structured reasoning steps
- cipher_evaluate_reasoning (internal): Evaluate reasoning quality and suggest improvements
- cipher_search_reasoning_patterns: Search reflection memory for patterns
- Workspace Memory (team)
- cipher_workspace_search: Search team/project workspace memory
- cipher_workspace_store: Background capture of team/project signals
- Knowledge Graph
- cipher_add_node, cipher_update_node, cipher_delete_node, cipher_add_edge
- , cipher_enhanced_search, cipher_get_neighbors
- , cipher_query_graph, cipher_relationship_manager
- System
- Tutorial Video: Claude Code with Cipher MCP
Watch our comprehensive tutorial on how to integrate Cipher with Claude Code through MCP for enhanced coding assistance with persistent memory:
> Click the image above to watch the tutorial on YouTube.
For detailed configuration instructions, see the CLI Coding Agents guide.
Documentation
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| Topic | Description |
| ------------------------------------------------------------ | --------------------------------------------------------------------------------- |
| Configuration | Complete configuration guide including agent setup, embeddings, and vector stores |
| LLM Providers | Detailed setup for OpenAI, Anthropic, AWS, Azure, Qwen, Ollama, LM Studio |
| Embedding Configuration | Embedding providers, fallback logic, and troubleshooting |
| Vector Stores | Qdrant, Milvus, In-Memory vector database configurations |
| Chat History | PostgreSQL, SQLite session storage and management |
| CLI Reference | Complete command-line interface documentation |
| MCP Integration | Advanced MCP server setup, aggregator mode, and IDE integrations |
| Workspace Memory | Team-aware memory system for collaborative development |
| Examples | Real-world integration examples and use cases |
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For detailed documentation, visit:
- Quick Start Guide
- Configuration Guide
- Complete Documentation
Contributing
We welcome contributions! Refer to our Contributing Guide for more details.
Community & Support
cipher is the opensource version of the agentic memory of byterover which is built and maintained by the byterover team.
- Join our Discord to share projects, ask questions, or just say hi!
- If you enjoy cipher, please give us a ⭐ on GitHub—it helps a lot!
- Follow @kevinnguyendn on X
Contributors
Thanks to all these amazing people for contributing to cipher!
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License
Elastic License 2.0. See LICENSE for full terms.