Aegis MCP Server
Simulated core-banking resilience and high-frequency continuity shield demonstration using Multi-Agent System with anomaly detection and remediation patterns.
README
Project Aegis (Anti-Gravity FinTech Edition)
Project Aegis is a simulated core-banking resilience and high-frequency continuity shield demonstration. It is built as a Multi-Agent System (MAS) via the Model Context Protocol (MCP) using NitroStack.
Important Disclaimer
This project is a simulation for demonstration purposes only. There is no real bank, no real money, and no real customer data anywhere in this system. It does not connect to any real banking infrastructure. Everything runs against a mock in-memory ledger initialized with synthetic data.
Math vs. Presentation Flavor
To evaluate this project accurately, it is important to delineate the actual mathematical implementations from the presentation terminology:
Actual Mathematical & Systems Implementations:
- Incremental SVD Sketching: The
IncrementalSVDEngineimplements a real Frequent-Directions-style matrix sketch over a 4-dimensional telemetry vector. It operates in $O(k \cdot d)$ time, maintaining a baseline of nominal system behavior. - Exponential Decay & Filtering: The sketch utilizes an exponential decay weighting ($\lambda = 0.95$) to adapt to volume growth and an $L_1$-norm clamp to reject extreme single-frame log corruptions.
- Anomaly Detection: The
residualError(x)method mathematically computes the $L_2$ norm of the residual vector after projecting the current telemetry onto the healthy subspace: $|(I - P_S)x|$. Note: The anomaly threshold ($> 15.0$) is a tuned demo constant, not a derived statistical bound. - Remediation Patterns:
- Request Coalescing: The
SingleFlightGatepattern safely deduplicates identical concurrent reads. - Idempotency Locking: The
IdempotencyEnforcercalculates cryptographic hashes to mathematically reject duplicate submission attempts within a TTL window. - Admission Control: The
QosShuntingimplements token-bucket based prioritization.
- Request Coalescing: The
Presentation "Flavor":
- The terms "Anti-Gravity", "Orbital Drift", "Kinetic Mass", and "Structural Collapse" are presentation dressing to visually conceptualize standard load-shedding and telemetry-anomaly scenarios. They map directly to standard distributed systems concepts (e.g., "Orbital Drift" = SVD Subspace Residual Error, "Kinetic Mass" = Lock Contention).
- The agents (PRIME, ATLAS, CERBERUS, HERMES) act as standard MCP tool providers mapping to the remediation patterns above.
Demonstration Modes
Mock Mode (Default)
By default, the dashboard runs in "Mock mode", against an in-memory database generating synthetic, deterministic data.
Live Validation Mode
This project includes a real, verifiable proof layer alongside the mock engine. The Live validation mode tests the system against a genuine local Postgres 15 instance under real Artillery-generated HTTP load, proving that the anomaly detection is triggering on actual connection-pool contention, not scripted telemetry data.
To run the Live validation mode:
- Ensure Docker and Artillery are installed locally:
npm i -g artillery - Start the database:
cd validation && docker-compose up -d - Start the legacy core server:
node validation/legacy-core-server.js - On the frontend dashboard, toggle the "Simulations" data source to Live Validation Harness.
- Triggering the Salary Day Storm will now spawn a child process executing the
thundering-herd.ymlload spec against the local Postgres server.
Note: While Live mode operates on real row-level ACID locks and connection pooling limits, it is still a local, single-machine demo rig and should not be considered a production core-banking environment.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.