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codebase-wiki

codebase-wiki

by carreira-cloud
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Codebase Wiki

Architectural knowledge base with MCP interface for AI agents.

Agents discover services, generate LLM-powered docs with Mermaid C2/C3/sequence diagrams, and index them for semantic search. Includes self-learning notes and first-class workflow/flow indexing.

Quick Start

npm install -g @carreira-cloud/codebase-wiki

cd my-project
codebase-wiki init              # Initialize knowledge base
codebase-wiki serve             # Browse at http://localhost:3080
codebase-wiki start-mcp         # Start MCP server for AI agents

Related MCP server: ainative-opencode-memory-mcp

Commands

Command

Description

init

Initialize knowledge base for current repo

serve

Start web UI (markdown + mermaid rendering, flows tab)

start-mcp

Start MCP server (stdio JSON-RPC, 12 tools)

search <query>

Search docs, notes, and flows by keyword

get <service>

Retrieve full documentation for a service

list

List all indexed services

stats

Statistics: services, flows, notes, content size

install-opencode

Install OpenCode skills and commands

MCP Tools

Documentation (8 tools)

Tool

Description

wiki_index

Index an LLM-generated architectural document

wiki_search

Search documentation by keyword

wiki_get

Retrieve full documentation for a service

wiki_list

List all indexed services

wiki_delete

Remove a service's documentation

wiki_stats

Statistics: services, content size, notes count, flows count

Self-Learning Notes (3 tools)

Tool

Description

wiki_note

Store a self-learning discovery note

wiki_notes_search

Search agent notes by keyword

wiki_notes_list

List notes (optional type filter)

Workflows & Flows (3 tools)

Tool

Description

wiki_flow_index

Index a workflow diagram with keywords and linked services

wiki_flow_search

Search flows across all services by keyword

wiki_flow_list

List flows (optional service/flow_type filter)

OpenCode Commands

/wiki generate <service>       → Agent discovers, generates docs, indexes via MCP
/wiki generate-all              → Generate docs for all services
/wiki enhance <service> <flow>  → Add Mermaid C3/C2/sequence diagrams
/wiki discover-flows <service>  → Discover and index all workflows with edge cases
/wiki flow-search <query>       → Search flows across all services
/wiki flow-list <service>       → List flows for a service
/wiki search <query>            → Search docs + notes + flows
/wiki get <service>             → Retrieve full doc
/wiki list                      → List all indexed services
/wiki stats                     → Knowledge base statistics

Self-Learning

Agents automatically add notes when they discover something new. Six note types:

Type

Trigger

gotcha

Unexpected behavior, edge case, known bug

pattern

Recurring pattern across 2+ services

integration

Undocumented service integration detail

convention

Code convention, naming pattern

decision

Design decision (lightweight ADR)

tip

Shortcut, useful command, workflow hack

Flows & Diagrams

Each flow is independently indexed with:

  • Mermaid sequence diagram (happy path + error paths + edge cases)

  • Keywords for discoverability

  • Linked services for cross-service navigation

  • Flow type: happy_path, error_path, edge_case, recovery, full

Diagrams render in the web UI via Mermaid.js. The UI also renders service documentation markdown (tables, code blocks, headings) via marked.js.

Architecture

src/
├── cli.ts              # CLI entry (8 commands)
├── mcp-server.ts       # MCP JSON-RPC server (12 tools)
├── ui-server.ts        # Web UI (marked.js + mermaid.js, flows tab)
├── lancedb/client.ts   # JSON file-backed storage (docs, notes, flows)
├── types.ts            # TypeScript types
└── index.ts            # Public API exports

docs/
├── getting-started.md
├── mcp-tools.md
├── self-learning.md
├── configuration.md
└── architecture.md

Storage: .codebase-wiki/rag_db/docs.json + notes.json + flows.json

License

MIT — Bruno Carreira

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

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