Thank you for sending your enquiry! One of our team members will contact you shortly.
Thank you for sending your booking! One of our team members will contact you shortly.
Duration 14 hours
Course Outline
Anatomy of the Protocol
- Limitations of function calling alone in complex agent ecosystems
- Core MCP components: tools, resources, prompts, and their associated JSON schemas
- The lifecycle of an MCP session: initialization, tool listing, invocation, result return, and termination
- Contrasting MCP with OpenAPI and GraphQL for exposing capabilities to agents
Developing a Stdio MCP Server
- Setting up a TypeScript MCP server using the official SDK
- Defining tool schemas with Zod to generate runtime validation
- Coding tool handlers that interact with internal REST APIs or databases
- Managing errors, partial outcomes, and long-running execution processes
Developing an HTTP MCP Server
- Upgrading from stdio to HTTP to support remote deployment and load balancing
- Implementing security via bearer tokens and mTLS authentication
- Handling graceful degradation during mid-session HTTP connection failures
- Deploying HTTP MCP servers behind Kong or nginx with rate limiting controls
Client Integration Strategies
- Registering MCP servers with Claude Code via configuration files
- Connecting OpenClaude to multiple MCP endpoints concurrently
- Developing custom Python agent clients using the MCP Python SDK
- Adapting dynamically to changes in tool availability during runtime
Exposing Resources and Prompts
- Providing read-only resources to enhance agent context
- Designing parameterized prompt templates to steer agent reasoning
- Dynamically updating resources as underlying data evolves
- Distinguishing between mutable tools and immutable resources for security clarity
Internal Tool Registry and Discovery
- Creating an organization-wide MCP registry with metadata and ownership tracking
- Facilitating auto-discovery through DNS-SD or well-known endpoint files
- Managing tool versioning and deprecating outdated endpoints without disrupting clients
- Cataloging tools with natural language descriptions to improve agent searchability
Enterprise Security Controls
- Enforcing authorization checks within tool handlers based on agent identity
- Isolating high-risk tools from general agent access using network segmentation
- Sandboxing tool execution using seccomp and gVisor containers
- Logging all tool interactions for compliance and forensic investigation
Performance and Reliability Engineering
- Configuring timeout policies for different tool categories: databases, compute, and external APIs
- Implementing circuit breakers to handle downstream service instability
- Caching tool outputs to minimize redundant high-cost computations
- Evaluating MCP server deployment as sidecars versus standalone microservices
Interoperability Across Agent Platforms
- Verifying MCP server compatibility with clients like Claude Code and Continue.dev
- Managing transport negotiation variations across different platforms
- Developing polyfill adapters for non-MCP agent frameworks
- Establishing an internal, cross-platform tool marketplace
Growing the Internal MCP Ecosystem
- Gathering developer feedback on tool utility and accuracy
- Conducting quarterly tool reviews to remove obsolete integrations
- Onboarding new teams through self-service MCP server templates
- Contributing enhancements back to the open-source MCP specification
Requirements
- Proficiency in TypeScript or Python programming
- Familiarity with LLM tool invocation and function-calling architectures
- Foundational knowledge of networking protocols, including HTTP, WebSockets, and JSON-RPC
Target Audience
- Backend developers creating bespoke tools for AI agents
- Platform engineers standardizing access to enterprise systems for AI agents
- Solution architects designing scalable AI tool ecosystems for corporate deployment