* feat(grpc): reflection option and native gRPC example
Add grpcserver.Reflection() to register go-micro handlers with gRPC's
reflection service, and examples/grpc showing a go-micro v6 service
callable by grpcurl and any standard gRPC client.
Resolvesmicro/go-micro#4880
* docs(grpc): native gRPC compatibility guide with reflection
Update grpc-compatibility guide for the reflection option and
server.Name placement on the gRPC server; remove duplicated intro
text on ai-integration and add client-server description.
* fix(website): convert /docs/overview/mcp/ link to .html for uglyURLs consistency
* fix(website): add .html suffix to single-page doc links missing it
* fix(website): replace blog short IDs with full permalink + .html
* fix: replace /blog/4 with absolute https://go-micro.dev URL in examples README
* fix(website): convert trailing-slash blog cross-references to .html
/blog/YYYY/MM/DD/slug/ → /blog/YYYY/MM/DD/slug.html across 17 files
for uglyURLs consistency. Includes roadmap blog references.
* fix(docs): add index.md symlinks for wayfinding tests
Hugo uses _index.md convention but wayfinding tests expect index.md.
Create symlinks index.md -> _index.md in docs and examples dirs.
Follow-up cleanup after merging the Ollama provider (#3636):
- Add the `ollama` row to the AI provider capability matrix in the provider
guide, and blank-import `ai/ollama` in provider_capabilities_test.go so the
matrix stays enforced against the registry (the provider registers a stream
but wasn't imported in that test, so its row went unchecked).
- README: bump "7 LLM providers" → 8 and list Ollama (local + cloud); add its
default model (`llama3.2`) to the model table.
- Fix a fictional model name shipped in the example and package doc:
`gemma4:31b-cloud` → `gpt-oss:120b`. gemma4 doesn't exist, and the `-cloud`
suffix is for cloud models proxied through a local Ollama, not the direct
ollama.com/v1 endpoint the example uses.
- Record the provider and the new agent.BaseURL/micro.AgentBaseURL option in
the CHANGELOG [Unreleased] section.
Claude-Session: https://claude.ai/code/session_01CmdEY7pYmV5zzwCjNJ4ykL
Co-authored-by: Claude <noreply@anthropic.com>
Add a dedicated Ollama AI provider (ai/ollama/) that auto-detects
local vs cloud mode based on the base URL:
- Local Ollama: native /api/chat endpoint with NDJSON streaming
- Ollama Cloud: OpenAI-compatible /v1/chat/completions with SSE streaming
Both modes support tool calls with a multi-round execution loop.
Add agent.BaseURL option so agents can point at non-default LLM
endpoints (e.g. local Ollama, proxies). Wire it through micro.AgentBaseURL
at the top level.
Include a complete example (examples/agent-ollama/) demonstrating a
knowledge-base service with auto-discovered tools, a custom time tool,
streaming, and env-var configuration for local vs cloud.
Closes#3632
Adds the agentic 'loop' to flows: flow.Loop(body, opts...) is a StepFunc
that runs a body step repeatedly, carrying State across passes, until a
stop condition fires or a hard iteration cap is reached.
- Stop modes: flow.Until (code-defined predicate) and flow.UntilLLM (the
model judges the goal met after each pass — the supervised 'Ralph'
loop). Either firing stops the loop.
- flow.LoopMax is the guardrail: the body never runs more than n times, so
the loop always terminates and can't run up an unbounded bill. Hitting
the cap returns the latest state rather than erroring.
- flow.OnIteration reports per-pass progress.
- Composes as a normal flow step (checkpointed by the step engine).
- Exposed at the top level as micro.FlowLoop / FlowUntil / FlowUntilLLM /
FlowLoopMax / FlowOnIteration, symmetric with the other Flow* helpers.
Includes tests, an offline runnable example (examples/flow-loop), an
'Agent Loops' guide, and a CHANGELOG entry.
Claude-Session: https://claude.ai/code/session_01CmdEY7pYmV5zzwCjNJ4ykL
Co-authored-by: Claude <noreply@anthropic.com>
* docs: compare Go Micro with Google ADK in the comparison guide
Adds a 'vs Agent Frameworks (Google ADK)' section: ADK builds an agent,
Go Micro builds the distributed system the agent lives in (agents are
services in the mesh). Covers the category difference, a feature table,
when to choose each, and MCP/A2A interoperability.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CmdEY7pYmV5zzwCjNJ4ykL
* docs: replace ADK comparison slogan with concrete explanation
State plainly what each tool provides (ADK builds an agent process; Go Micro
builds the surrounding service mesh) instead of marketing phrasing.
* lint: apply golangci-lint autofixes; exclude ST1003 and demo errcheck
Mechanical, behaviour-preserving fixes applied by 'golangci-lint run --fix':
gofmt, misspell (US spelling), usestdlibvars (http.Method*/Status*), unconvert,
and the auto-fixable staticcheck simplifications (QF*, S1017/S1019/S1023/S1039).
Config: exclude ST1003 (remaining offenders are exported API renames, e.g.
web.Id, which would break compatibility) and skip errcheck for examples/ and
internal/harness/ (demo code where fire-and-forget is intentional).
Build and test compilation verified.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CmdEY7pYmV5zzwCjNJ4ykL
* lint: WIP cleanup checkpoint (errcheck config + partial fixes)
Checkpoint of an in-progress golangci-lint cleanup (background pass). Builds
cleanly; lint is not yet zero. Follow-up commit will complete the cleanup and
switch CI to a blocking full-tree lint.
Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01CmdEY7pYmV5zzwCjNJ4ykL
---------
Co-authored-by: Claude <noreply@anthropic.com>
A real-world, runnable example (examples/support): customers/tickets/notify
services become the agent's tools, a flow turns a ticket.created event into
the agent's work, and an approval gate guards the one action that touches a
customer. Runs with no API key (mock model) or against a live provider.
Adds blog/28 'Building a Support Agent in Go' and indexes both.
Claude-Session: https://claude.ai/code/session_01CmdEY7pYmV5zzwCjNJ4ykL
Co-authored-by: Claude <noreply@anthropic.com>
* test(harness): read agent plan from the scoped store
The store-scoping change moved an agent's plan from the default table
key agent/{name}/plan to its own table (database "agent", table {name},
key "plan"). The plan-delegate harness tests still read the old key and
failed with 'not found'; read through store.Scope(mem, "agent", name)
like the agent does.
* docs: orient agents-first across README, landing, and docs overview
Lead with agents (then services and flows), surface MCP + A2A as the
interop story, and frame agents as services. Landing hero and feature
grid reordered agents-first with an A2A gateway card.
* v6: module path go-micro.dev/v6, TLS secure by default, NewService
Cut v6. Three breaking changes, bundled so the major bump is paid once:
- Module path go-micro.dev/v5 -> go-micro.dev/v6 across all imports + go.mod.
- TLS verification on by default (was off). MICRO_TLS_SECURE removed;
MICRO_TLS_INSECURE=true opts out for self-signed/dev.
- micro.NewService(name, opts...) is the canonical service constructor,
symmetric with NewAgent/NewFlow; micro.New kept as a deprecated alias;
the old name-less NewService(opts...) removed. Generators emit NewService.
Also ports the JWT auth token provider in-module (go-micro.dev/v6/auth/jwt/token
on golang-jwt/jwt/v5), dropping the v5-pinned github.com/micro/plugins/v5/auth/jwt
and the deprecated dgrijalva/jwt-go.
Docs/README/landing updated to v6 and @latest; v5->v6 migration guide added;
CHANGELOG cut as [6.0.0]. Blog posts left at their historical versions.
---------
Co-authored-by: Claude <noreply@anthropic.com>
* docs: design note for flow steps + Checkpoint durable execution
* docs: fold in durable-execution decisions (State struct, single Step, run retention, retry)
* docs: rename State.Payload to State.Data
* feat(flow): ordered steps + Checkpoint durable execution
A flow can now be an ordered list of steps (a task with stages) instead
of a single LLM turn. State carries typed Data plus a Stage marker; each
step is checkpointed before and after via a pluggable Checkpoint
(store-backed by default), so a run survives a crash and resumes where it
stopped without re-running completed steps. Flow-level Retry with a
per-step override; runs retained for audit unless DeleteOnSuccess.
Step actions: Call (RPC), LLM (augmented turn), Dispatch (to an agent),
or any StepFunc. Single-step and agent-dispatch flows are unchanged.
* feat(flow): top-level re-exports + durable flow example
Expose the step/checkpoint API from the micro package (FlowSteps,
FlowStep, FlowState, FlowRetry, FlowWithCheckpoint, FlowCall/LLM/Dispatch,
Checkpoint, StoreCheckpoint) and add a runnable, key-free example
demonstrating crash + resume.
* docs: document durable flow steps (guide, README, CLI help)
* docs: blog post + changelog for durable workflows
* fix(flow): scope checkpoint keys by flow name (flow/{name}/runs/{id})
Run keys were flow/runs/{id} — a single global keyspace shared by every
flow on the default store. Namespace them by flow name so each flow's
state is kept apart. StoreCheckpoint now takes a scope argument (the flow
passes its name by default).
* feat(store): Scope handle; scope agent and flow state by name
Add store.Scope(s, database, table) — a store handle that confines every
operation to a database/table without mutating the shared store, so
co-located components don't clobber each other's table (the failure mode
of the global Init(Table(...)) approach).
Use it to keep each agent's memory and plan in its own table
(agent/{name}) and each flow's runs in its own (flow/{name}), instead of
one global table partitioned only by key prefix. Services already scope
by service name.
* feat: consistent state model — service store scoping, flow registry, list/history CLI
- service: scope store via store.Scope (database service / table name),
retiring the Init(store.Table(name)) global-mutation hack; bridge the
default store so handlers using store.DefaultStore stay isolated.
- flow: register in the registry as type=flow while running (with trigger
and step count), deregister on Stop. Live discovery, like agents.
- cli: micro flow list (registry), micro flow runs <name> (durable store),
micro agent history <name> (durable store). list = running, runs/history
= durable, mirroring the service model.
* test: mini-universe end-to-end harness + scheduled GitHub Action
internal/harness/universe boots a small but real go-micro world — four
services, a durable checkout flow that crashes at payment and resumes,
and a guardrailed agent with a tool wrapper reached over RPC — drives the
scenario, asserts the end state (10 checks), and shuts down. Everything
is real except the LLM (mocked), so it's deterministic and needs no key;
-provider anthropic runs it live. Exits non-zero on failure, so it's an
end-to-end test, not just a demo.
Adds .github/workflows/universe.yml (push/PR/daily/dispatch) running the
universe + existing harnesses on the mock provider, plus an opt-in job
that runs live when ANTHROPIC_API_KEY is set. 'make harness' runs them
locally.
* ci: run the live universe job against AtlasCloud (ATLASCLOUD_API_KEY)
* ci: run the live universe job only on schedule or manual dispatch
The deterministic mock job still runs on push/PR/daily; the live
(AtlasCloud) job runs daily and on manual workflow_dispatch only, so
changes don't burn API credits on every PR but can still be checked
against a real model on demand.
---------
Co-authored-by: Claude <noreply@anthropic.com>
* feat(agent): tool-execution wrappers via WrapTool
Restructure ai.ToolHandler to the structured, ctx-carrying shape that
mirrors a go-micro RPC handler:
func(ctx context.Context, call ai.ToolCall) ai.ToolResult
This reuses the existing ToolCall (with its correlation ID) and
ToolResult types instead of the flat (name, input)->(any, string)
signature, and adds ToolCall.Scan for typed argument access.
Add ai.ToolWrapper and the agent option WrapTool / micro.AgentWrapTool —
the tool-side analogue of client.CallWrapper and server.HandlerWrapper.
Reframe the built-in guardrails (MaxSteps, LoopLimit, ApproveTool) as
composed wrappers around a base handler; developer wrappers compose
outermost, so they observe every call and result, including refusals.
Update all provider call sites, the MCP server and chat handlers, the
integration harnesses, and docs to the new signature.
* examples: add agent-wrap-tool showing AgentWrapTool
A runnable example of tool-execution middleware: an observe wrapper that
times calls and records per-tool metrics (correlated by call ID), and a
retry wrapper that recovers a flaky service call before the model sees
it. Demonstrates outermost-first composition and the wrapper/guardrail
interaction (retries are seen by loop detection).
---------
Co-authored-by: Claude <noreply@anthropic.com>
* Initial plan
* feat(health): add RegistryCheck for registry connectivity health checks
Add a RegistryCheck function to the health package that creates a health
check verifying connectivity to the service registry. This enables
Kubernetes readiness probes to detect when a service loses its connection
to the registry (e.g. etcd).
Usage:
health.Register("registry", health.RegistryCheck(reg))
* fix(health): simplify error assertion in registry check test
---------
Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
* feat: add plan and delegate as built-in agent tools
Give agents two self-capabilities, expressed as plain tools wired into
the existing tool handler — no harness or graph, consistent with
"services are the only abstraction":
- plan: record/update an ordered plan, persisted to store-backed memory
and surfaced in the system prompt on later turns (externalized
planning).
- delegate: hand a self-contained subtask to another agent.
Delegate-first — if the target names a registered agent it is called
via RPC; otherwise a focused ephemeral sub-agent is created with
agent.New + Ask in a fresh, isolated context (loads/persists no
history, no built-in tools, so it cannot re-delegate).
Both are added automatically to any non-ephemeral agent, so existing
micro.NewAgent services and micro chat routing get them for free.
Tests are hermetic (memory store + memory registry).
* feat: add agent-plan-delegate example and document plan/delegate
- examples/agent-plan-delegate: coordinator that plans multi-step work,
creates tasks with its own tools, and delegates notification to a
separate registered comms agent over RPC.
- integration tests driving the full Ask loop through a fake provider:
plan tool exposure + persistence, ephemeral delegation with isolated
context, delegate-first RPC routing to a registered agent.
- docs: README (Building Agents + features + examples), AGENT_DESIGN
(Built-in Capabilities), agent-patterns guide (Pattern 9), CLAUDE.md.
* docs: blog post and guide for plan & delegate
- blog/17: "Plan & Delegate: Deep Agents in Go" — what the feature is,
how plan and delegate work, and a runnable getting-started path.
- guides/plan-delegate: reference guide with the smallest-agent snippet,
plan/delegate semantics, and the multi-agent example; linked in nav.
- example: auto-detect provider/key from common env vars (ANTHROPIC_API_KEY,
OPENAI_API_KEY, ...) so 'export KEY && go run main.go' just works.
- onboarding: getting-started paths now include go mod init / go get and a
clone-and-run path, so a reader can actually run it from a cold start.
* refactor: reframe plan/delegate blog and clean up sub-agent construction
- blog/17 retitled "Agents That Plan and Delegate" and reframed around
intent (plan = state intent, delegate = direct it), positioned as the
next beat after blog 15/16 and tied to the existing store + agent RPC
rather than re-announcing them. "Deep agents" now a single in-passing
nod, matching how blog 14 references LangChain.
- agent: add unexported newEphemeral constructor for sub-agents instead
of type-asserting the public Agent interface to set an internal field;
matches the options-only construction idiom used elsewhere.
* feat: expose plan & delegate in the micro chat fallback
Add agent.Builtins(opts...) — returns the built-in tools plus a handler,
so the plan/delegate capabilities can be wired into a tool loop that
isn't a running Agent. micro chat's direct-service fallback now reuses
it (single source of truth, no duplicated handler logic), so planning
and delegation are available there too, not just for registered agents.
Adds a test for the accessor; notes CLI availability in the guide.
---------
Co-authored-by: Claude <noreply@anthropic.com>
* docs: add AI provider integration guide and Supported AI Providers section
Add a step-by-step guide for AI infrastructure companies to implement
ai.Model and contribute a provider to go-micro. Covers the full
lifecycle: skeleton, tool call handling, tests, registration, and PR
checklist.
Add a "Supported AI Providers" section to the project README that lists
current providers (Anthropic, OpenAI) in a table and links to the
integration guide with a call-to-action for new providers and sponsors.
Streamline the "Adding a New Provider" section in ai/README.md to point
to the new guide instead of duplicating a full code listing.
* fix: remove nonexistent Discord link from README
* fix(website): set content container width to 800px on desktop
Move the 800px max-width from .markdown-body up to .content so
the entire content pane (not just the inner body) is sized
correctly. The container now fills up to 800px beside the sidebar.
* feat(ai): wire Atlas Cloud into server and auto-detection
Import atlascloud provider in the micro server so it is available
when running micro run / micro server. Add atlascloud to
AutoDetectProvider so --ai_base_url with an atlascloud domain
selects the right provider automatically.
* feat(ai): add Google Gemini provider
Add ai/gemini implementing ai.Model for Google's Gemini API. Uses
the native generateContent endpoint with system_instruction,
contents/parts, and functionDeclarations — not an OpenAI shim.
Default model gemini-2.5-flash, auth via x-goog-api-key header.
Wire into micro server imports and AutoDetectProvider (matches
googleapis.com and google in base URL).
Update README.md and ai/README.md with provider listing.
* feat(ai): add Groq, Mistral, and Together AI providers
Add three new OpenAI-compatible providers:
- ai/groq: ultra-fast inference, default model llama-3.3-70b-versatile
- ai/mistral: Mistral AI, default model mistral-large-latest
- ai/together: Together AI, default model Llama-3.3-70B-Instruct-Turbo
All three are wired into the micro server imports and
AutoDetectProvider. README and ai/README updated with the full
provider table.
* feat(ai): add ai/tools helper and 'micro chat' interactive agent
Extract the registry-discovery + RPC-execution loop from the web
agent playground into a reusable ai/tools package:
- tools.New(reg) creates a Set bound to a registry
- Set.Discover() walks the registry and returns []ai.Tool with
LLM-safe (underscored) names, remembering the mapping back to
the original dotted form
- Set.Handler(client) returns an ai.ToolHandler that resolves
the safe name and issues the RPC
Add cmd/micro/chat — an interactive 'micro chat' REPL that uses
ai/tools to let users talk to their services through any
registered AI provider. Supports --prompt for single-shot use,
auto-detects the provider from --base_url, and falls back to the
provider's conventional env var (ANTHROPIC_API_KEY, etc).
Update README with the new command and the programmatic example.
* feat(examples): add gRPC interop example
Add examples/grpc-interop showing that any standard gRPC client can
call a go-micro service — no go-micro SDK required on the client
side. Includes:
- proto/greeter.proto with generated Go, gRPC, and micro stubs
- server/ using go-micro gRPC transport
- client/ using stock google.golang.org/grpc (no go-micro imports)
- README with Python example and explanation of how routing works
Addresses the confusion from issue #2818 where users didn't know
that go-micro gRPC services are callable by any gRPC client.
---------
Co-authored-by: Claude <noreply@anthropic.com>
* 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>
* 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
---------
Co-authored-by: Claude <noreply@anthropic.com>
* docs: update all four documentation guides and mark Q2 complete
- ai-native-services: add WithMCP one-liner, standalone gateway,
WebSocket client example, and OpenTelemetry observability section
- mcp-security: add OTel distributed tracing, WebSocket authentication
(connection-level and per-message), DeniedReason audit field
- tool-descriptions: add manual overrides with WithEndpointDocs and
export formats section
- agent-patterns: add LangChain/LlamaIndex SDK pattern and standalone
gateway production pattern with Docker example
- Update roadmap: mark Q2 documentation as complete, Q2 at 100%
- Update status: reflect all recent completions, shift priorities
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
* feat: add agent demo example and blog post
Add examples/agent-demo with a multi-service project management app
(projects, tasks, team) that demonstrates AI agents interacting with
Go Micro services through MCP. Includes seed data and example prompts.
Add blog post 4 "Agents Meet Microservices: A Hands-On Demo" walking
through the example code and showing cross-service agent workflows.
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
* feat: enable multiple services in a single binary
Remove global state mutations from service and cmd option functions so
that configuring one service no longer overwrites another's settings.
Key changes:
- service/options.go: remove all DefaultXxx global writes from option
functions; newOptions() now creates fresh Server, Client, Store, and
Cache per service while sharing Registry, Broker, and Transport
- cmd/cmd.go: newCmd() uses local copies instead of pointers to package
globals; Before() no longer mutates DefaultXxx vars
- cmd/options.go: remove global mutations from all option functions
- service/service.go: export ServiceImpl type for cross-package use
- service/group.go: new Group type for multi-service lifecycle
- micro.go: add Start/Stop to Service interface, expose Group and
NewGroup convenience function
- examples/multi-service: working example with two services
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
* docs: highlight multi-service binary support
Add multi-service section to README with code example, update features
list, add to examples index, and note in status summary.
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
* feat: unify service API and clean up developer experience
- Unified service creation: micro.New("name", opts...) as canonical API
- Clean handler registration: service.Handle(handler, opts...) accepts
server.HandlerOption args directly, no need to reach through Server()
- Unexported serviceImpl: users interact through Service interface only
- Service groups use Service interface (not concrete type)
- Fixed Stop() to properly propagate BeforeStop/AfterStop errors
- Fixed store init: error-level log instead of fatal on init failure
- Updated all examples to use consistent patterns
- Updated README, getting-started, MCP docs, and guides
- Added blog post about the DX cleanup
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
---------
Co-authored-by: Claude <noreply@anthropic.com>
* docs: update all four documentation guides and mark Q2 complete
- ai-native-services: add WithMCP one-liner, standalone gateway,
WebSocket client example, and OpenTelemetry observability section
- mcp-security: add OTel distributed tracing, WebSocket authentication
(connection-level and per-message), DeniedReason audit field
- tool-descriptions: add manual overrides with WithEndpointDocs and
export formats section
- agent-patterns: add LangChain/LlamaIndex SDK pattern and standalone
gateway production pattern with Docker example
- Update roadmap: mark Q2 documentation as complete, Q2 at 100%
- Update status: reflect all recent completions, shift priorities
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
* feat: add agent demo example and blog post
Add examples/agent-demo with a multi-service project management app
(projects, tasks, team) that demonstrates AI agents interacting with
Go Micro services through MCP. Includes seed data and example prompts.
Add blog post 4 "Agents Meet Microservices: A Hands-On Demo" walking
through the example code and showing cross-service agent workflows.
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
* feat: enable multiple services in a single binary
Remove global state mutations from service and cmd option functions so
that configuring one service no longer overwrites another's settings.
Key changes:
- service/options.go: remove all DefaultXxx global writes from option
functions; newOptions() now creates fresh Server, Client, Store, and
Cache per service while sharing Registry, Broker, and Transport
- cmd/cmd.go: newCmd() uses local copies instead of pointers to package
globals; Before() no longer mutates DefaultXxx vars
- cmd/options.go: remove global mutations from all option functions
- service/service.go: export ServiceImpl type for cross-package use
- service/group.go: new Group type for multi-service lifecycle
- micro.go: add Start/Stop to Service interface, expose Group and
NewGroup convenience function
- examples/multi-service: working example with two services
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
* docs: highlight multi-service binary support
Add multi-service section to README with code example, update features
list, add to examples index, and note in status summary.
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
---------
Co-authored-by: Claude <noreply@anthropic.com>
* docs: update all four documentation guides and mark Q2 complete
- ai-native-services: add WithMCP one-liner, standalone gateway,
WebSocket client example, and OpenTelemetry observability section
- mcp-security: add OTel distributed tracing, WebSocket authentication
(connection-level and per-message), DeniedReason audit field
- tool-descriptions: add manual overrides with WithEndpointDocs and
export formats section
- agent-patterns: add LangChain/LlamaIndex SDK pattern and standalone
gateway production pattern with Docker example
- Update roadmap: mark Q2 documentation as complete, Q2 at 100%
- Update status: reflect all recent completions, shift priorities
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
* feat: add agent demo example and blog post
Add examples/agent-demo with a multi-service project management app
(projects, tasks, team) that demonstrates AI agents interacting with
Go Micro services through MCP. Includes seed data and example prompts.
Add blog post 4 "Agents Meet Microservices: A Hands-On Demo" walking
through the example code and showing cross-service agent workflows.
https://claude.ai/code/session_01GkduEhcrqcG45rdfYh8dAc
---------
Co-authored-by: Claude <noreply@anthropic.com>
* Initial plan
* Add MCP per-tool scopes, tracing, rate limiting, and audit logging
- Add Scopes field to Tool struct for per-tool scope requirements
- Add Auth (auth.Auth) integration to Options for token inspection
- Add trace ID generation (UUID) propagated via metadata to downstream RPCs
- Add per-tool rate limiting with configurable requests/sec and burst
- Add AuditFunc callback for immutable tool-call audit records
- Extract tool scopes from registry endpoint metadata ("scopes" key)
- Update both HTTP and stdio transports with auth/trace/rate/audit
- Add comprehensive tests for all new functionality
Co-authored-by: asim <17530+asim@users.noreply.github.com>
* Revert unrelated example go.mod changes
Co-authored-by: asim <17530+asim@users.noreply.github.com>
* Remove auto-generated example go.sum files
Co-authored-by: asim <17530+asim@users.noreply.github.com>
* Add WithEndpointScopes helper, gateway-level ToolScopes, and documentation
- Add server.WithEndpointScopes() for declaring per-endpoint auth scopes at
handler registration time
- Add mcp.Options.ToolScopes for gateway-level scope overrides without
changing individual services
- Update documented example to show WithEndpointScopes usage
- Update examples/mcp/README.md with scopes, tracing, and rate-limiting docs
- Update gateway/mcp/DOCUMENTATION.md with scopes section and FAQ
- Add tests for both new features
Co-authored-by: asim <17530+asim@users.noreply.github.com>
* Fix ToolScopes doc comment: clarify override (not merge) semantics
Co-authored-by: asim <17530+asim@users.noreply.github.com>
* Revert unrelated example go.mod/go.sum changes
Co-authored-by: asim <17530+asim@users.noreply.github.com>
* Rename ToolScopes to Scopes in MCP Options
The field name "Scopes" is more universal and consistent with how
auth scopes are used throughout go-micro. Updated all code references,
tests, and documentation.
Co-authored-by: asim <17530+asim@users.noreply.github.com>
* MCP gateway: add per-tool scopes, tracing, rate limiting, and audit logging
Co-authored-by: asim <17530+asim@users.noreply.github.com>
---------
Co-authored-by: copilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>
Co-authored-by: asim <17530+asim@users.noreply.github.com>
Alexander Serheyev