* feat: add agent platform showcase and blog post Add a complete platform example (Users, Posts, Comments, Mail) that mirrors micro/blog, demonstrating how existing microservices become AI-accessible through MCP with zero code changes. Includes blog post "Your Microservices Are Already an AI Platform" walking through real agent workflows: signup, content creation, commenting, tagging, and cross-service messaging. https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc * refactor: rename handler types to drop redundant Service suffix UserService → Users, PostService → Posts, CommentService → Comments, MailService → Mail. Matches micro/blog naming convention. https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc * refactor: consolidate top-level directories, reduce framework bloat Move internal/non-public packages behind internal/ or into their parent packages where they belong: - deploy/ → gateway/mcp/deploy/ (Helm charts belong with the gateway) - profile/ → service/profile/ (preset plugin profiles are a service concern) - scripts/ → internal/scripts/ (install script is not public API) - test/ → internal/test/ (test harness is not public API) - util/ → internal/util/ (internal helpers shouldn't be imported externally) Also fixes CLAUDE.md merge conflict markers and updates project structure documentation. All import paths updated. Build and tests pass. https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc * refactor: redesign model package to match framework conventions Rename model.Database interface to model.Model (consistent with client.Client, server.Server, store.Store). Remove generics in favor of interface{}-based API with reflection. Key changes: - model.Model interface: Register once, CRUD infers table from type - DefaultModel + NewModel() + package-level convenience functions - Schema registered via Register(&User{}), no per-call schema passing - Memory implementation as default (in model package, like store) - memory/sqlite/postgres backends updated for new interface - protoc-gen-micro generates RegisterXModel() instead of generic factory - All docs, blog, and README updated https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc * docs: clarify blog post 7 uses modular monolith, not multi-service Blog post 7 demonstrated all handlers in a single process but framed it as microservices without acknowledging the architectural difference. - Add "A Note on Architecture" section explaining this is a modular monolith demo and pointing to micro/blog for multi-service - Clarify that handlers can be broken out into separate services later - Fix "service registry" language to match single-process reality - Restructure "Adding MCP to Existing Services" to distinguish the in-process approach from registry-based gateway options - Update closing to acknowledge both paradigms - Fix README type names (&CommentService{} -> &Comments{}, etc.) https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc --------- Co-authored-by: Claude <noreply@anthropic.com>
Platform Example: AI Agents Meet Real Microservices
This example mirrors the micro/blog platform — a real microblogging application built on Go Micro. It demonstrates how existing microservices become AI-accessible through MCP with zero changes to business logic.
Services
| Service | Endpoints | Description |
|---|---|---|
| Users | Signup, Login, GetProfile, UpdateStatus, List | Account management and authentication |
| Posts | Create, Read, Update, Delete, List, TagPost, UntagPost, ListTags | Blog posts with markdown and tagging |
| Comments | Create, List, Delete | Threaded comments on posts |
| Send, Read | Internal messaging between users |
Running
go run .
MCP tools available at: http://localhost:3001/mcp/tools
Agent Scenarios
These are realistic multi-step workflows an AI agent can complete:
1. New User Onboarding
"Sign up a new user called carol, then write a welcome post introducing herself"
The agent will: call Signup → use the returned user ID → call Posts.Create
2. Content Creation
"Log in as alice and write a blog post about Go concurrency patterns, then tag it with 'golang' and 'concurrency'"
The agent will: call Login → call Posts.Create → call TagPost twice
3. Social Interaction
"List all posts, find the welcome post, and comment on it as bob saying 'Great to be here!'"
The agent will: call Posts.List → pick the right post → call Comments.Create
4. Cross-Service Workflow
"Send a mail from alice to bob welcoming him, then check bob's inbox to confirm delivery"
The agent will: call Mail.Send → call Mail.Read to verify
5. Platform Overview
"Show me all users, all posts, and all tags currently in use"
The agent will: call Users.List, Posts.List, and ListTags (potentially in parallel)
How It Works
The key insight: you don't need to write any agent-specific code. The MCP gateway discovers services from the registry, extracts tool schemas from Go types, and generates descriptions from doc comments.
service := micro.New("platform",
micro.Address(":9090"),
mcp.WithMCP(":3001"), // This one line makes everything AI-accessible
)
service.Handle(&Users{})
service.Handle(&Posts{})
service.Handle(&Comments{})
service.Handle(&Mail{})
Each handler method becomes an MCP tool. The @example tags in doc comments give agents sample inputs to learn from.
Connecting to Claude Code
Add to your Claude Code MCP config:
{
"mcpServers": {
"platform": {
"command": "curl",
"args": ["-s", "http://localhost:3001/mcp/tools"]
}
}
}
Or use stdio transport:
micro mcp serve --registry mdns
Architecture
Agent (Claude, GPT, etc.)
│
▼
MCP Gateway (:3001) ← Discovers services, generates tools
│
▼
Go Micro RPC (:9090) ← Standard service mesh
│
├── UserService ← Signup, Login, Profile
├── PostService ← CRUD + Tags
├── CommentService ← Threaded comments
└── MailService ← Internal messaging
Relation to micro/blog
This example is a simplified, self-contained version of micro/blog. The real platform splits each service into its own binary with protobuf definitions. This example uses Go structs directly for simplicity, but the MCP integration works identically either way — the gateway discovers services from the registry regardless of how they're implemented.