MCP Architect

MCP Architect

Contract

Houston, TX

Key Roles in MCP Architecture

MCP itself defines three core participant roles (not job titles, but architectural components):

1. MCP HostThe user-facing AI application (e.g., Claude Desktop, Claude Code, VS Code with AI extensions, custom AI agents, or platforms like Agent force).

Coordinates multiple MCP clients.

Manages user interactions, permissions, and lifecycle.

Orchestrates requests to LLMs and merges context from servers.

Renders results to the user.

2. MCP ClientA component (usually embedded in the host) that maintains a dedicated, stateful connection to an MCP server.

Handles communication using the JSON-RPC-based MCP protocol.

Manages sessions, authentication, and context exchange.

Routes requests and receives tools, resources, prompts, and notifications.

3. MCP ServerThe provider of capabilities (the backend that exposes data and actions).

Executes tools (actions the AI can take).

Provides resources (structured data/context).

Offers prompts (templated instructions/workflows).

Handles authentication, data retrieval, execution, caching, and security.

Can run locally (e.g., via STDIO) or remotely (e.g., via streamable HTTP).

This separation follows a clean division of concerns: the host/client focus on AI reasoning and user experience, while the server handles secure execution and data access.

Responsibilities of an MCP Architect Role

Based on emerging job descriptions and MCP-related architecture discussions (e.g., from companies building AI agents or integrations), someone in an MCP-focused architect or senior engineering role typically handles:

Designing scalable MCP solutions for high-volume data access and AI agent workflows.

Architecting and developing MCP servers for various backends (databases, APIs, file systems, cloud services, enterprise tools like Jira/Confluence).

Implementing custom MCP tools, resources, and prompts to extend AI capabilities.

Ensuring secure, production-ready integrations (authentication, defense-in-depth security, session management, caching).

Following best practices like single responsibility principle for servers and handling transport layers (local STDIO vs. remote HTTP).

Integrating MCP clients into host applications (e.g., AI IDEs, chat agents, or custom frameworks using LangChain/similar).

Collaborating on composable AI systems where MCP acts as the universal connector for agents.

Optimizing for performance, security, and interoperability across different MCP-compatible hosts (e.g., Anthropic s Claude ecosystem, Microsoft tools, or open-source agents).

These responsibilities blend software architecture, AI engineering, distributed systems, and protocol implementation. Roles often require experience with JSON-RPC, agent frameworks, security models, and modern AI tooling.