Cipher
Memory-powered AI agent framework built by BYTEROVER that provides persistent memory capabilities across conversations and sessions using vector databases and embeddings. The implementation supports multiple LLM providers (OpenAI, Anthropic, Gemini, Ollama, etc.), vector stores (Qdrant, Milvus, in-memory), and includes specialized workspace memory for team collaboration tracking project progress, bug reports, and member activities. Features include automatic memory extraction and storage, reasoning pattern recognition, knowledge graph integration, and MCP aggregator mode that exposes memory tools alongside connected MCP servers with conflict resolution, serving developers who need AI assistants that learn and remember context across coding sessions, teams requiring shared project memory, and organizations building AI workflows that benefit from persistent knowledge retention.
Composite of vulnerability cleanliness, spec conformance, provenance, stability, and usage signals — scanned and weighted by Cognium. Human and agent signals are tracked separately.
View full trust & usage report →Metadata
- Version
- 1.0.0
- Skill type
- atomic
- Execution layer
- mcp-remote
- Category
- database
- Source
- PulseMCP
- Repository
- github.com/campfirein/byterover-cli
- Author type
- human
- Updated
- 2026-05-27
Use via MCP
Resolve Cipher from your agent
Streamable HTTP transport at https://api.skillsregistry.net/mcp. No auth for read tools. Discovery: .well-known/mcp.json.
One command in your shell — Claude Code wires it up and verifies the connection. Run /mcp in any session to confirm.
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp--scope user for --scope project to commit it to .mcp.json.