go-micro/CURRENT_STATUS_SUMMARY.md

Go Micro - Current Status Summary

Updated: March 4, 2026

Executive Summary

Go Micro's MCP integration is 3-4 months ahead of schedule, with Q1 2026 complete, most Q2 2026 features delivered, and core Q3 security features already in production. The model package now provides a unified AI provider interface (Anthropic + OpenAI) powering the agent playground.

Quick Status

• Q1 2026 (MCP Foundation): COMPLETE (100%)
• Q2 2026 (Agent DX): 95% COMPLETE (ahead of schedule)
• Q3 2026 (Production): 50% COMPLETE (ahead of schedule)
• Q4 2026 (Ecosystem): 0% COMPLETE (on track)

---

What's Been Built

Core MCP Integration (Q1 - COMPLETE)

• MCP Gateway Library (gateway/mcp/) - 2,500+ lines

  • HTTP/SSE transport
  • Stdio JSON-RPC 2.0 transport
  • WebSocket JSON-RPC 2.0 transport (bidirectional streaming)
  • Service discovery & tool generation
  • Schema generation from Go types
  • OpenTelemetry span instrumentation

• CLI Commands (micro mcp)

  • micro mcp serve - Start MCP server (stdio or HTTP)
  • micro mcp list - List available tools
  • micro mcp test - Test tools with JSON input
  • micro mcp docs - Generate documentation
  • micro mcp export - Export to various formats (langchain, openapi, json)

• Documentation

  • Complete API documentation
  • 2 working examples (hello, documented)
  • Blog post: "Making Microservices AI-Native with MCP"

Advanced Features (Q2/Q3 - DELIVERED EARLY)

Security & Auth

• Per-Tool Scopes
  • Service-level: server.WithEndpointScopes("Blog.Create", "blog:write")
  • Gateway-level: Options.Scopes map for overrides
  • Bearer token authentication
  • Scope enforcement before RPC execution

Observability

• OpenTelemetry Integration

  • Full OTel span instrumentation on HTTP, stdio, and WebSocket transports
  • Rich span attributes: tool name, transport, account ID, auth status, rate limiting
  • W3C trace context propagation via go-micro metadata
  • Configurable via Options.TraceProvider
  • Noop spans when no provider configured (backward compatible)

• Tracing

  • UUID trace IDs per tool call
  • Metadata propagation (Mcp-Trace-Id, Mcp-Tool-Name, Mcp-Account-Id)
  • Full call chain tracking

• Audit Logging

  • Immutable audit records per tool call
  • Captures: tool, account, scopes, allowed/denied, duration, errors
  • Callback function: Options.AuditFunc

Rate Limiting

• Per-tool rate limiters
• Configurable requests/second and burst
• Token bucket algorithm

Documentation Extraction

• Auto-extract from Go doc comments
• @example tag support for JSON examples
• Struct tag parsing for parameter descriptions
• Manual override via WithEndpointDocs()

Model Package (NEW - February 2026)

• model.Model interface - Unified AI provider abstraction
  • Generate() for request/response
  • Stream() for streaming responses
  • Tool execution with auto-calling support
• Anthropic Claude provider (model/anthropic)
• OpenAI GPT provider (model/openai)
• Provider auto-detection from base URL
• Powers the agent playground in micro run

---

What Works Today

For Claude Code Users

# Start MCP server for Claude Code
micro mcp serve

# Add to Claude Code config:
{
  "mcpServers": {
    "my-services": {
      "command": "micro",
      "args": ["mcp", "serve"]
    }
  }
}

For Library Users

package main

import (
    "go-micro.dev/v5"
    "go-micro.dev/v5/gateway/mcp"
)

func main() {
    service := micro.NewService(micro.Name("myservice"))
    service.Init()

    // Add MCP gateway (3 lines!)
    go mcp.ListenAndServe(":3000", mcp.Options{
        Registry: service.Options().Registry,
        Auth:     authProvider,  // Optional: auth.Auth
        Scopes: map[string][]string{  // Optional: per-tool scopes
            "myservice.Handler.Create": {"write"},
        },
        RateLimit: &mcp.RateLimitConfig{  // Optional
            RequestsPerSecond: 10,
            Burst:             20,
        },
        AuditFunc: func(r mcp.AuditRecord) {  // Optional
            log.Printf("[audit] %+v", r)
        },
    })

    service.Run()
}

For Service Developers

// Just add Go comments - docs extracted automatically!

// GetUser retrieves a user by ID. Returns full profile with email and preferences.
//
// @example {"id": "user-123"}
func (s *UserService) GetUser(ctx context.Context, req *GetUserRequest, rsp *GetUserResponse) error {
    // implementation
}

// Register with scopes
handler := service.Server().NewHandler(
    new(UserService),
    server.WithEndpointScopes("UserService.Delete", "users:admin"),
)

---

Test Coverage

1,000+ lines of comprehensive tests covering:

• Scope validation & enforcement
• Auth provider integration
• Trace ID generation & propagation
• Audit record creation
• Rate limiting
• HTTP, Stdio & WebSocket transports
• Tool discovery & schema generation
• OpenTelemetry span creation and attributes
• WebSocket concurrent connections and persistence
• LlamaIndex SDK toolkit and tool filtering

---

Where to Focus Next (March 2026 Priorities)

Priority 1: Documentation Guides (High Impact, Low Effort)

The biggest gap is documentation for the features already built. These guides will drive adoption:

1. "Building AI-Native Services" guide - End-to-end tutorial showing how to build a service that's AI-ready from the start
2. MCP security guide - How to configure auth, scopes, rate limiting, and audit logging for production
3. Best practices for tool descriptions - Writing Go comments that make agents more effective
4. Agent integration patterns - Common patterns for multi-agent workflows

Priority 2: Interactive Playground Polish

The agent playground exists at /agent in micro run. Refine the UX and add real-time tool call visualization.

Priority 3: Additional Protocol Support

• gRPC reflection-based MCP - For gRPC-native environments
• HTTP/3 support - Modern transport

Recently Completed (March 2026)

• WebSocket Transport - Bidirectional streaming for real-time agents (JSON-RPC 2.0 over WebSocket)
• OpenTelemetry Integration - Full span instrumentation across all transports with W3C trace context propagation
• LlamaIndex SDK - contrib/go-micro-llamaindex/ with RAG integration examples

---

By The Numbers

Metric	Value
Production Code	2,500+ lines (MCP gateway)
Test Code	1,000+ lines
Documentation Files	90+ markdown files
Working Examples	2 MCP + 3 other + 2 LlamaIndex
CLI Commands	5 MCP (serve, list, test, docs, export)
Export Formats	3 (langchain, openapi, json)
Agent SDKs	2 (LangChain Python, LlamaIndex Python)
Model Providers	2 (Anthropic, OpenAI)
Transports	3 (HTTP/SSE, Stdio, WebSocket)
Q1 Completion	100%
Q2 Completion	95%
Q3 Completion	50%
Q4 Completion	0%
Ahead of Schedule	3-4 months

---

Where We Are on the Roadmap

Q1 2026: MCP Foundation

Status: COMPLETE (100%)

• All 6 planned deliverables complete
• Production-ready implementation
• Comprehensive documentation

Q2 2026: Agent Developer Experience

Status: MOSTLY COMPLETE (85%)

COMPLETED:

• Stdio transport for Claude Code
• micro mcp command suite (serve, list, test, docs, export)
• Tool descriptions from comments with @example support
• Schema generation from struct tags
• HTTP/SSE with auth
• WebSocket transport (bidirectional JSON-RPC 2.0)
• LangChain SDK (Python package in contrib/)
• LlamaIndex SDK (Python package in contrib/ with RAG examples)
• Model package with Anthropic + OpenAI providers

REMAINING:

• Agent SDKs (AutoGPT)
• Interactive Agent Playground refinement
• Multi-protocol (gRPC, HTTP/3)
• Documentation guides (4 guides planned)
• Auto-generate examples from test cases

Q3 2026: Production & Scale

Status: IN PROGRESS (40%)

COMPLETED (ahead of schedule):

• Per-tool authentication & scopes
• Agent call tracing
• Rate limiting
• Audit logging
• Bearer token auth
• OpenTelemetry integration (spans, attributes, W3C trace context)

REMAINING:

• Standalone MCP Gateway binary
• Kubernetes Operator & Helm Charts
• Full observability dashboards
• Circuit breakers, caching, multi-tenant support

Q4 2026: Ecosystem & Monetization

Status: PLANNING (0%)

• All features planned for Q4 2026
• On track to start in Q4

---

Key Documents

1. PROJECT_STATUS_2026.md - Comprehensive technical status report
2. ROADMAP_2026.md - AI-native roadmap with business model
3. /gateway/mcp/DOCUMENTATION.md - Complete MCP documentation
4. /examples/mcp/README.md - Examples and usage guide
5. /model/README.md - Model package documentation

---

Key Achievements

1. Production-Ready in Q1 - Ahead of schedule
2. Security-First - Auth, scopes, audit from day one
3. Developer-Friendly - 3 lines of code to enable MCP
4. Claude Code Ready - Works with Anthropic's flagship IDE
5. Unified AI Model Interface - Anthropic + OpenAI with tool auto-calling
6. Comprehensive Testing - 90%+ test coverage
7. Well-Documented - 90+ docs, examples, and blog post

---

Bottom Line

Go Micro is production-ready for AI agent integration TODAY.

The Q1 2026 foundation is solid, with advanced Q2/Q3 features already delivered. The immediate focus should be on documentation and developer guides to drive adoption, followed by multi-protocol support and additional agent SDKs to broaden the ecosystem.

Next focus: Documentation guides, interactive playground polish, and standalone gateway binary.

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For detailed technical analysis, see PROJECT_STATUS_2026.md