Question 1

Why build a custom MCP server instead of standard API integrations?

Accepted Answer

Standard API integrations and brittle function-calling scripts require hardcoded endpoints, bespoke prompt wrappers, and constant maintenance whenever client requirements change. A custom Model Context Protocol (MCP) server implements Anthropic's open standard, providing unified tool discovery, strict type schema validation, context persistence, and secure bidirectional execution between LLMs (like Claude Desktop or custom agents) and your private databases or APIs.

Question 2

Who owns the intellectual property and code?

Accepted Answer

You own 100% of the intellectual property, source code, tool definitions, agent workflows, and architecture schemas from day one. Everything is developed directly inside your private Git repositories under full IP transfer agreements with zero proprietary runtime lock-in.

Question 3

How do you protect proprietary company data?

Accepted Answer

Security and privacy are engineered as foundational constraints. All LLM integrations enforce strict zero-data-retention (ZDR) commercial agreements so your queries never train public models. Furthermore, vector search is hosted internally (via pgvector or isolated self-hosted instances), and MCP servers are configured over private local stdio channels or TLS-encrypted Server-Sent Events (SSE) protected by role-based access control (RBAC).

Question 4

What engagement models do you offer?

Accepted Answer

I operate with three flexible, high-impact engagement models: (1) Fixed-Scope Technical Sprints (2–4 weeks) with defined deliverables for custom MCP server builds, agentic workflows, or enterprise RAG retrieval systems; (2) Fractional AI Partner / Lead Architect for ongoing strategic advisory and hands-on architecture leadership; and (3) End-to-End AI SaaS & MVP Engineering for complete technical execution from database schema and backend APIs to full-stack UI and deployment.

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