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ProtocolExperimentalMCP
Zengram
by ZenSystemAI
MCP server + shared memory for connecting agents across systems
JavaScript
Updated Jul 4, 2026
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How It Works
Implements an Model Context Protocol (MCP)-based multi-agent memory layer that links agents across systems and machines. Uses a server-side MCP implementation to route messages and persist shared memory, with optional vector DB (qdrant) backing and connector hooks for n8n and Claude. Includes deduplication and long-memory primitives to keep interactions compact and searchable across deployments, including natural cross-system referencing via the A2A Protocol Pattern.
The Value Proposition
As agents coordinate across services, a shared communication and memory fabric is essential for reproducible behavior and traceable decisions. Zengram provides a concrete consensus evaluation and memory model so agent interactions can be recorded, queried, and correlated — a prerequisite for meaningful agent-to-agent evaluation and building an agent track record. Until teams adopt common A2A protocols and memory stores, it remains hard to audit delegation, failure modes, and reputation signals.
When to Use
Developers prototyping cross-system multi-agent setups who need a shared memory and MCP bridge for experimentation and tracing, guided by practical patterns such as the A2A Protocol Pattern.
How It's Used
- Persisting and querying shared agent memory across machines using qdrant
- Connecting on-premise or cloud agents (Claude, custom bots) via an MCP server
- Instrumenting agent delegation flows for later evaluation and debugging
- Integrating agent event streams with automation tools like n8n
Works With
claudeqdrantn8ncursoropenclaw
Topics
claudeclaude-aiclaude-codecursordeduplicationembeddedlongmemevalmcpmcp-servermemory+10 more
Similar Tools
openclawrepkit
Keywords
multi-agent trusta2a evaluationmcpagent memory