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#Python / FastMCP 2 items linked

Case studies, ventures, and publications tagged with Python / FastMCP across Samuel Mofrad's architecture portfolio.

Architectural Case Studies (2)

Samuel Mofrad

Samuel Mofrad

🚀 Ventures & Client Products
Founder & AI Systems Architect • softwork.ing Technology Arm • AI/ML & Cloud Solutions
softwork.ing Core • Multi-Agent Fleet • ⏱ •

softwork.ing Enterprise AI Agent & Cloud Orchestration Platform

Architected and deployed enterprise-grade Model Context Protocol (MCP) server hubs enabling secure, bi-directional tool execution between autonomous LLM agents and internal client backends.

• Architectural Implementation:
  • Engineered JSON-RPC 2.0 transport layers over stdio and SSE with strict mutual TLS (mTLS) and token-based client authentication.
  • Integrated semantic vector indexing (Qdrant & pgvector) allowing autonomous multi-agent systems to safely query repositories, Jira, and databases.
  • Deployed fault-tolerant agent runners on Kubernetes with isolated sandboxing to prevent prompt injection and unauthorized API lateral traversal.
  • Established repeatable agentic delivery playbooks connecting enterprise clients with elite engineers through the softwork.ing talent network.
Python / FastMCP MCP Protocol Agentic AI Kubernetes Vector Search
♥ ★ 64 reactions
Verified Architecture • European Enterprise
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Samuel Mofrad

Samuel Mofrad

📚 Open Source & Education
Open Source Lead Architect • Open Source Community & FastMCP • Open Source & AI Tooling
Open Source Blueprint • Community Adoption • ⏱ •

Production FastMCP Reference Architecture for AI Multi-Agent Systems

Engineered and open-sourced a hardened, production-ready reference starter kit for the Model Context Protocol (FastMCP), enabling teams to build secure tool servers for Claude, OpenAI, and custom autonomous agents.

• Architectural Implementation:
  • Implemented zero-trust authentication middleware with mutual TLS (mTLS) and scoped Bearer token validation for SSE and stdio transports.
  • Built containerized Docker recipes with minimal Alpine images and unprivileged runtime users preventing container escapes.
  • Packaged comprehensive automated testing harnesses covering tool schema generation, error propagation, and latency benchmarking.
  • Provided clear documentation and architectural decision records (ADRs) adopted by developers building multi-agent AI ecosystems.
Python / FastMCP MCP Protocol Autonomous Agents Docker Security
♥ ★ 81 reactions
Verified Architecture • European Enterprise
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