MCP Comparison
Compare features, tools, and capabilities of these MCP servers side by side.
ChainAware Behavioural Prediction MCP
The ChainAware Behavioural Prediction MCP is an MCP-based server that provides AI-powered tools to analyze wallet behaviour prediction, fraud detection, and rug pull prediction. Designed for Web3 security and DeFi analytics, it enables developers and platforms to integrate risk assessment, predictive wallet behavior insights, and rug-pull detection through MCP-compatible clients. The server exposes three specialized tools and uses Server-Sent Events (SSE) for real-time responses, helping safeguard DeFi users, monitor liquidity risks, and score wallet or contract trustworthiness. Access to production endpoints is API-key gated, reflecting a private backend architecture that supports secure, scalable risk analytics across wallets, contracts, and pools.
Graphiti MCP Server
Graphiti MCP Server is an experimental implementation that exposes Graphiti's real-time, temporally-aware knowledge graph capabilities through the MCP (Model Context Protocol) interface. It enables AI agents and MCP clients to interact with Graphiti's knowledge graph for structured extraction, reasoning, and memory across conversations, documents, and enterprise data. The server supports multiple backends (FalkorDB by default and Neo4j), a variety of LLM providers (OpenAI, Anthropic, Gemini, Groq, Azure OpenAI), and multiple embedder options, all accessible via an HTTP MCP endpoint at /mcp/ for broad client compatibility. It also includes queue-based asynchronous episode processing, rich entity types for structured data, and flexible configuration through config.yaml, environment variables, or CLI arguments.
| Feature | ChainAware Behavioural Prediction MCP | Graphiti MCP Server |
|---|---|---|
| Verified | ||
| Official | ||
| Tools Available | 3 | 9 |
| Has Installation Guide | ||
| Has Examples | ||
| Website | ||
| Source Code |
- predictive_fraud
- predictive_behaviour
- predictive_rug_pull
- add_episode
- search_nodes
- search_facts
- delete_entity_edge
- delete_episode
- get_entity_edge
- get_episodes
- clear_graph
- get_status
Can't decide? Check out both MCP servers for more details.