Prism MCP offers an enterprise-grade Model Context Protocol server designed for persistent session memory and advanced semantic search capabilities. With features like optimistic concurrency control, multi-tenant RLS, and integration with Vertex AI and Brave Search, it empowers AI agents to harness knowledge accumulation and context loading effectively.
Prism MCP — Enterprise-Grade AI Agent Memory & Multi-Engine Search
Prism MCP is a production-ready Model Context Protocol (MCP) server that provides robust features for building intelligent AI agents. This platform integrates persistent session memory, a brain-inspired knowledge accumulation system, and a powerful multi-engine search combining Brave Search and Google's Vertex AI Discovery Engine.
Key Features:
- Persistent Session Memory: Instantly save and resume context with the
/resume_sessioncommand, ensuring that AI agents maintain their continuity without needing multiple tool calls. - Optimistic Concurrency Control: Protect against data loss in multi-client environments with version-tracked data handling.
- Progressive Context Loading: Load sessions at varying depths (quick/standard/deep) for improved resource management.
- Semantic Search Capabilities: Utilize embeddings (pgvector) to search session memory by meaning rather than keywords, leading to more relevant results.
- Auto-Compaction: Manage memory efficiently with Gemini-powered ledger compaction, automatically archiving older entries.
- Multi-Model Orchestration: Engage with multiple AI models seamlessly, allowing for flexible querying from both real-time web sources and curated enterprise data.
Comparison with Other Solutions:
Prism MCP stands out in several areas compared to its competitors:
| Capability | Prism MCP | Mem0 | Zep | Basic Memory |
|---|---|---|---|---|
| Architecture | MCP-native | Standalone | Standalone | MCP-native |
| Storage | Supabase | Hybrid DBs | PostgreSQL + Neo4j | Local files |
| Cold Start Fix | Yes | No | No | No |
| Progressive Loading | Yes | No | No | No |
| Semantic Search | Yes | Yes | Yes | No |
| Auto-Compaction | Yes | No | Yes | No |
| Infrastructure Cost | Free tier available | Free tier available | Paid (self-hosted) | Free (local only) |
| Multi-Tenant RLS | Yes | No | No | No |
Core Architecture:
The Prism MCP server operates on a multi-tool architecture, providing seamless integration between various APIs, including Brave Search for live data and Google's Vertex AI for deeper insights. The server facilitates structured request handling and manages session memory through Supabase, enhancing the user experience by allowing multiple projects to run concurrently.
Example API Calls:
Utilizing the tools provided by Prism MCP, perform operations such as:
{
"name": "knowledge_search",
"arguments": {
"project": "ecommerce-api",
"category": "debugging",
"query": "Stripe webhook"
}
}
This enables effective searching across all accumulated knowledge by keyword, category, or free text while automatically extracting relevant keywords and categories for efficient management.
Getting Started:
To deploy the Prism MCP server, clone the repository and configure your application with minimal setup. This makes it suitable for developers looking to implement powerful AI capabilities without extensive infrastructure overhead.
Prism MCP represents an advanced solution for creating AI agents equipped with memory and knowledge systems, ensuring continuous improvement and adaptability in dynamic environments.
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