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Table of contents

• Why DocGraph
• Features
• Supported agents
• Remote document sources
• Auto-sync
• Read-only mode
• Installation
• Quick start
• CLI reference
• MCP server
• Embeddings & providers
• Configuration
• Programmatic API
• Architecture
• Multi-project support
• Benchmarks
• Telemetry
• Development
• License

Why DocGraph

AI coding agents are only as good as the context they can find. DocGraph turns any project plus its remote knowledge sources into a single hybrid search index that an agent can query with natural language. The search returns the most relevant documents, headings, and code blocks — combining keyword search with semantic vector search across both local files and external SaaS sources.

• Zero setup. A built-in, dependency-free local embedding provider means hybrid search works immediately — no API key, no model download, everything stays on your machine.
• Multi-source. Pull documents from Notion, Jira, Confluence, Linear, GitHub issues/PRs, and local Obsidian vaults into the same graph as your filesystem.
• Multi-project. One MCP server, many indexed projects — pass projectPath to each tool call.
• Agent-native. Ships an installer that natively wires DocGraph into 8 AI agents — Claude Code, Cursor, opencode, Gemini CLI, Codex CLI, Kiro, Antigravity, and (best-effort) Hermes — each in its own native config format. See Supported agents.
• Auto-sync. A debounced file watcher keeps the index current while docgraph watch or the MCP server is running — no manual reindex needed. See Auto-sync.
• Benchmark harness. npm run benchmark clones real doc repos and runs a real git grep (or file-scan) baseline against DocGraph search, N runs median — see Benchmarks.

Features

• 🔎 Hybrid search — SQLite FTS5 + cosine vector similarity, merged with configurable weights.
• 🧠 Offline embeddings out of the box — deterministic feature-hashing vectors; swap in a cloud provider anytime.
• 🌐 Remote source adapters — Notion, Jira, Confluence (Cloud + Data Center), Linear, GitHub, Obsidian, all bundled, with retry/backoff and hash-based re-embed skipping.
• 🔄 Auto-sync — a debounced file watcher re-indexes changed files and removes deleted ones while docgraph watch or the MCP server runs.
• 🗂️ Multi-format indexing — Markdown (front-matter in YAML/TOML/JSON, headings, links, code blocks, tags), JSON, YAML, TOML, AsciiDoc, reStructuredText, Org-mode, plus doc-oriented symbol and comment extraction for JS/TS, Python, Go, Rust, Java/Kotlin/C#, and generic parsing across 40+ file types.
• 🕸️ Knowledge graph — documents, headings, tags, and internal links modelled as nodes and edges you can traverse.
• 📚 Multi-project — one MCP process serves every indexed project via the projectPath arg.
• 🔌 MCP server — 9+ tools exposed over stdio for AI agents.
• 🧑‍💻 8-agent native install — docgraph install writes each agent's own MCP config format non-destructively and can uninstall symmetrically.
• 📊 Benchmark suite — real git grep/file-scan baseline vs. DocGraph search, N-run median per scenario; see Benchmarks.
• 🧩 Clean Architecture — domain / application / infrastructure / presentation layers with dependency inversion, fully unit- and integration-tested.

Doc-oriented, not a code AST. DocGraph's per-language code parsing (JS/TS, Python, Go, Rust, Java/Kotlin/C#) extracts top-level symbol names, headings, and leading doc comments/docstrings via targeted regexes — enough to make source files searchable and to surface their structure in the knowledge graph. It is a companion to a dedicated code-graph tool (e.g. codegraph), not a replacement for a real compiler-grade AST/call-graph.

Supported agents

docgraph install (and docgraph init) detect installed agents and write DocGraph's MCP server into each one's own native config format — no manual JSON/TOML editing required. Every agent below is wired natively; nothing here is a no-op.

Agent	Config path	Format
Claude Code	.mcp.json (local) / ~/.claude.json (global)	JSON mcpServers.<name>
Cursor	.cursor/mcp.json (local) / ~/.cursor/mcp.json (global)	JSON mcpServers.<name>
opencode	opencode.json/opencode.jsonc (local) / ~/.config/opencode/opencode.json (global)	JSON mcp.<name> block
Gemini CLI	.gemini/settings.json (local) / ~/.gemini/settings.json (global)	JSON mcpServers.<name>
Codex CLI	.codex/config.toml (local) / ~/.codex/config.toml (global)	TOML [mcp_servers.<name>]
Kiro	.kiro/settings/mcp.json (local) / ~/.kiro/settings/mcp.json (global)	JSON mcpServers.<name>
Antigravity	~/.gemini/antigravity/mcp_config.json (single well-known location)	JSON mcpServers.<name>
Hermes Agent	.hermes/mcp.json (local) / ~/.hermes/mcp.json (global)	JSON mcpServers.<name> — best-effort, unverified: Hermes has no publicly documented MCP config schema, so this follows the de-facto convention shared by the other agents above

Installs are non-destructive: existing keys and unrelated servers in a config file are preserved, and a file that fails to parse is left untouched (install reports a skip rather than clobbering it). docgraph uninstall is symmetric — it removes exactly the docgraph entry it added.

Remote document sources

Every source listed below ships as a built-in adapter. Enable one or many in .docgraph/settings.json under sources.sources.<name> and they are pulled, indexed, and searched alongside local files.

Source	Auth	Notes
Obsidian	None (filesystem)	Walks a local vault, parses YAML front-matter, extracts inline #tags and [[wikilinks]].
Notion	Bearer integration token	Database query or workspace search; cursor-based pagination (no page-100 cap, no duplicate pages); renders blocks to Markdown.
Jira (Cloud)	Email + API token (Basic) or OAuth bearer	JQL filter configurable; ADF body rendered to Markdown.
Confluence (Cloud)	Email + API token (Basic)	REST v2, space ID or CQL filter. Indexes the full page body (body-format=storage/expand=body.storage), not just metadata.
Confluence (Data Center / self-hosted)	Username + password (or PAT)	Same REST model as Cloud with no cloud-id prefix.
Linear	Personal API key	GraphQL issues query, team and state filters. Pagination is still capped to the first page of results — large teams won't get every issue in one pull.
GitHub	Fine-grained PAT	Issues or pull requests, optional state filter.

All HTTP-based sources (Notion, Jira, Confluence, Linear, GitHub) retry on 429/5xx with exponential backoff + jitter (honoring a Retry-After header when present); if a page fails after retries are exhausted, results already fetched are kept instead of being discarded for the whole run. Remote documents are content-hashed like local files — a pull that finds no change since the last run skips re-parsing/re-embedding that document, so repeated index/sources pull runs against a large, mostly-unchanged remote corpus don't re-pay embedding cost every time.

Obsidian, Jira (Cloud), Confluence (Cloud + Data Center), Linear, GitHub, and the Postman/OpenAPI source are exercised in the test suite and confirmed working as described above.

DocGraph collects and transmits no telemetry of any kind. See TELEMETRY.md.

Auto-sync

Both docgraph watch and the MCP server (docgraph-mcp serve) run a debounced filesystem watcher (via chokidar) on the served project. When files change, DocGraph re-indexes only the changed files — not a full reindex — and removes documents for any file that was deleted. Bursts of events (e.g. a save-all or a branch checkout) are coalesced by a debounce window before the sync runs, so a flurry of edits triggers one incremental sync instead of one per file event.

docgraph watch                 # index, then watch this project and auto-reindex on change
docgraph watch /path/to/project

Autosync is on by default for both watch and serve. Disable it with any of:

• --no-watch (CLI flag on serve)
• DOCGRAPH_NO_WATCH=1 (environment variable)
• "watch": { "enabled": false } in .docgraph/settings.json

The debounce window is configurable via watch.debounceMs (default 1000 ms) — see Configuration.

Read-only mode

Run DocGraph so it never writes to the index: no indexing, no embedding writes, no autosync, no settings mutation — only reads (search, explore, get_*, list, stats, logs). Useful for serving a pre-built index to an agent, CI, or any untrusted context where the index must not change. Every mutating store method throws, the write MCP tools (index_project, index_file) return a JSON-RPC error, and the SQLite connections are opened { readonly: true, fileMustExist: true } — so the project must already be indexed.

Enable it with any of (highest precedence first):

• --read-only (CLI flag, and on docgraph-mcp serve)
• DOCGRAPH_READ_ONLY=1 (environment variable)
• "security": { "readOnly": true } in .docgraph/settings.json

docgraph index                          # build the index first (writable run)
docgraph search "auth" --read-only      # then query it without any writes
DOCGRAPH_READ_ONLY=1 npx @carrilloapps/docgraph docgraph-mcp serve

The flag/env force read-only for the whole process regardless of a project's own settings; when neither is set, each project falls back to its own settings.security.readOnly (default false).

Installation

# As a dependency of the repo you want to index (recommended — local MCP server)
npm install --save-dev @carrilloapps/docgraph
npx docgraph init

# Or globally
npm install -g @carrilloapps/docgraph

# Self-contained installer (no Node.js required; bundles its own runtime)
# macOS / Linux:
curl -fsSL https://raw.githubusercontent.com/carrilloapps/docgraph/main/install.sh | sh
# Windows (PowerShell):
irm https://raw.githubusercontent.com/carrilloapps/docgraph/main/install.ps1 | iex

# From source
git clone https://github.com/carrilloapps/docgraph.git
cd docgraph
npm install
npm run build

The package installs three binaries, each with a short alias:

• docgraph — CLI (short: dg)
• docgraph-mcp — MCP server over stdio (short: dg-mcp; also reachable as docgraph mcp)
• docgraph-install — agent auto-installer for all 8 supported agents (Claude Code, Cursor, opencode, Gemini CLI, Codex CLI, Kiro, Antigravity, Hermes) (short: dg-install)

Every subcommand also has a short alias (e.g. dg s "query" = docgraph search "query", dg i = docgraph index, dg st = docgraph stats) — see CLI reference.

Requires Node.js ≥ 18 on developer machines, or the bundled installer for users.

Quick start

# 1. Add DocGraph as a dev dependency and wire it into your agents.
npm install --save-dev @carrilloapps/docgraph
npx docgraph-install --yes                # auto-detect every installed agent (see Supported agents)

# 2. Configure remote sources you want indexed.
$EDITOR .docgraph/settings.json          # enable notion / jira / github / obsidian / ...

# 3. Build the index (filesystem + every enabled remote source).
docgraph init                             # one-shot: settings + initial index + per-agent MCP config
docgraph search "authentication"

# 4. Inspect.
docgraph stats
docgraph sources list                     # configured + enabled status for every source

docgraph init creates .docgraph/settings.json, builds the index, and writes portable MCP configuration (.mcp.json and opencode.json) that launches the server via npx — no absolute paths, so it works on any machine and OS.

Running from source? Use node dist/presentation/cli/cli.js <command> (or the npm run index / npm run search scripts) instead of the global docgraph binary.

CLI reference

docgraph <command> [options]        # or the short binary: dg <command>

Commands (short alias):
  init [path]              One-shot: settings, initial index, per-agent MCP config
  install | uninstall      Wire DocGraph into / remove from every detected AI agent
  index [path]        (i)  Index local files plus every enabled remote source
  reindex [path]      (ri) Clear and re-index
  watch [path]        (w)  Index, then auto-reindex on file changes (autosync)
  search <query>      (s)  Hybrid search (text + vector)   [also: q]
  stats [path]        (st) Show index statistics
  stats-json [path]   (stj) Show statistics as JSON
  list [path]         (ls) List all indexed documents
  sources [action]    (src) Manage remote sources (list|enable|disable|pull)
  apis [action]            Manage API specs (add|list|remove|enable|disable|pull)
  logs [options]           Read .docgraph/docgraph.log (--tail|--level|--grep|--follow*)
  export <file>       (exp) Export the current .docgraph.db to a portable file
  import <file>       (imp) Import a previously-exported .docgraph.db backup
  exclude [action]    (ex) Manage exclude patterns (list|add|remove|default|gitignore)
  files                    List supported file extensions
  settings [action]   (cfg) Manage settings (show|init|path)
  providers           (prov) List supported embedding providers
  serve [path]             Print MCP server configuration
  mcp [path]               Run the MCP server over stdio (= the docgraph-mcp binary)

Long and short forms are interchangeable — docgraph search "api", dg search "api", and dg s "api" are identical.

* --follow streams new log entries live as they're written (polling by byte offset, so it keeps working no matter how large the file grows) — Ctrl-C to stop. --tail, --level, and --grep all work as documented. See LOGGING.md.

Search options: --limit=n, --format=json|text, --ext=<ext>, --lang=<lang>, --tags=a,b,c, --no-vector, --no-text. Any command accepts --path=<dir>.

docgraph search "api" --lang=typescript --format=json
docgraph sources list                              # see which sources are enabled
docgraph sources pull --path=/path/to/project      # force a remote-source refresh
docgraph exclude add "**/fixtures/**"
docgraph stats

MCP server

MCP speaks over stdio. docgraph init writes the config below automatically; docgraph serve prints it without touching any files. The launch command is portable — it resolves the locally installed binary via npx, so there are no absolute, machine-specific paths. The project root is inferred from the server's working directory, the DOCGRAPH_PROJECT env var, or the projectPath argument every tool accepts.

Launch forms (short & long)

The server can be started three equivalent ways — use whichever you prefer:

Form	Command
Short (recommended for humans)	npx -y @carrilloapps/docgraph mcp
Explicit binary	npx -y -p @carrilloapps/docgraph docgraph-mcp serve
Short binary alias	npx -y -p @carrilloapps/docgraph dg-mcp serve

The generated agent configs below use the explicit docgraph-mcp binary for maximum robustness; the short mcp subcommand is a convenience that routes through the main CLI.

Claude Code (.mcp.json):

{
  "mcpServers": {
    "docgraph": {
      "command": "npx",
      "args": ["-y", "-p", "@carrilloapps/docgraph", "docgraph-mcp", "serve"]
    }
  }
}

opencode (opencode.json):

{
  "mcp": {
    "docgraph": {
      "type": "local",
      "command": ["npx", "-y", "-p", "@carrilloapps/docgraph", "docgraph-mcp", "serve"],
      "enabled": true
    }
  }
}

Set DOCGRAPH_DEBUG=1 to log JSON-RPC traffic to stderr.

Available tools

Tool	Description
index_project	Index local files plus every enabled remote source
index_file	Index a specific file
search	Hybrid search across indexed documents (with optional projectPath)
explore	Explore a topic with surrounding context (headings, code)
get_document	Get a document by ID or path
get_related	Get documents related by tags and links
get_stats	Get index statistics
list_documents	List indexed documents
get_document_graph	Get a document's node/edge connections
list_projects	List projects with an active .docgraph index in this MCP server

Embeddings & providers

By default provider: "auto" resolves to the built-in local provider — deterministic, offline, dependency-free hashing embeddings that make hybrid search work with no setup. For higher-quality semantic recall, configure a cloud or local-server provider; auto picks it up automatically when the matching API key is present in the environment.

Run docgraph providers to see every provider and its API-key environment variable.

• Local, no key: local (default), ollama, lmstudio, localai, jan
• Cloud, API key: openai, cohere, voyageai, mistral, google, huggingface, fireworks, togetherai, azure, minimax, replicate

export OPENAI_API_KEY=sk-...
docgraph reindex      # auto-detects OpenAI and regenerates embeddings

Configuration

Settings are read from .docgraph/settings.json (or docgraph.json) at the project root; anything omitted falls back to sensible defaults. Values of the form ${ENV_VAR} are expanded from the environment. Create a starter file with docgraph settings init.

{
  "embedding":   { "provider": "auto", "dimension": 256 },
  "indexing":    { "chunkSize": 512, "generateOnIndex": true },
  "search":      { "vectorWeight": 0.7, "textWeight": 0.3, "minScore": 0.1, "limit": 20 },
  "exclude":     { "useGitignore": true, "useDefaultPatterns": true },
  "sources": {
    "sources": {
      "notion":  { "enabled": true, "options": { "token": "${NOTION_TOKEN}", "databaseId": "..." } },
      "obsidian":{ "enabled": true, "options": { "vaultPath": "/Users/me/Vault" } },
      "jira":    { "enabled": false, "options": { "host": "https://acme.atlassian.net" } }
    },
    "pullOnIndex": true,
    "pullOnReindex": true,
    "maxPagesPerSource": 50,
    "maxConcurrentSources": 4
  },
  "watch": { "enabled": true, "debounceMs": 1000 },
  "security": { "readOnly": false }
}

sources.pullOnIndex, sources.pullOnReindex, sources.maxPagesPerSource, and sources.maxConcurrentSources are enforced: index/reindex consult pullOnIndex/ pullOnReindex to decide whether to touch the network at all, each remote source is capped to maxPagesPerSource pages via configureMaxPages(), and up to maxConcurrentSources sources are pulled concurrently instead of strictly one at a time.

Key	Default	Description
embedding.provider	auto	Embedding provider (local, openai, ...)
embedding.dimension	256	Vector size for the local provider
indexing.chunkSize	512	Characters per embedded chunk
indexing.generateOnIndex	true	Generate embeddings while indexing
sources.sources.<name>.enabled	false	Per-source enable flag
sources.pullOnIndex	true	Whether index pulls remote sources at all
sources.pullOnReindex	true	Whether reindex pulls remote sources at all
sources.maxPagesPerSource	50	Per-source page cap, forwarded to each adapter
sources.maxConcurrentSources	4	Max remote sources pulled concurrently
watch.enabled	true	Auto-sync file watcher for watch/serve (see Auto-sync)
watch.debounceMs	1000	Debounce window (ms) before an auto-sync re-index runs
security.readOnly	false	Forbid all writes; overridden per-run by --read-only / DOCGRAPH_READ_ONLY (see Read-only mode)
search.vectorWeight / textWeight	0.7 / 0.3	Hybrid merge weights
search.minScore	0.1	Minimum cosine similarity for vector hits
exclude.useGitignore	true	Honour the project .gitignore

Programmatic API

import { Container } from '@carrilloapps/docgraph';

const docgraph = new Container('/path/to/project');
await docgraph.indexing.indexProject();

const results = await docgraph.search.search({ query: 'authentication tokens', limit: 5 });
for (const hit of results) {
  console.log(`${(hit.score * 100).toFixed(1)}%  ${hit.document.relativePath}`);
}

// Remote sources are first-class: pull them on demand.
const counts = await docgraph.indexing.pullRemoteSources();
console.log('Pulled:', counts);

docgraph.close();

Individual services (IndexingService, SearchService, QueryService), ports, adapters, the ProjectRegistry, and every source implementation are all exported for advanced composition and testing.

Multi-project support

One MCP server process serves every indexed project. Each tool call accepts an optional projectPath argument; if absent, the server uses the DOCGRAPH_PROJECT env var or its working directory. Projects are kept in a small LRU (default DOCGRAPH_MAX_PROJECTS=16) so long-running sessions don't grow unbounded. Use list_projects to inspect what's loaded.

// Library form
import { ProjectRegistry } from '@carrilloapps/docgraph';
const registry = new ProjectRegistry({ maxProjects: 16 });
const services = registry.get('/projects/alpha');
const other    = registry.get('/projects/beta');

DOCGRAPH_MAX_PROJECTS=32 npx @carrilloapps/docgraph docgraph-mcp serve

Benchmarks

npm run benchmark clones real-world documentation repos, builds a DocGraph index, and runs a fixed set of natural-language queries against it, scoring both a WITH (DocGraph search) and a WITHOUT DocGraph arm. The baseline arm is a real comparison, not a stub: git grep -n -i over the same checkout, falling back to a manual recursive file scan if git is unavailable. Each scenario is measured N runs (default 4), median reported.

npm run build                                    # benchmark shells out to dist/, so build first
npm run benchmark
npm run benchmark -- --runs=8                    # custom run count
npm run benchmark -- --scenario=react-native     # one scenario at a time

Results are generated locally, on demand — the script writes a full report (per-run latency, hit counts, and a per-scenario summary) to benchmarks/results.json and prints a summary table to stdout. That output directory is not checked into this repository or published anywhere, so no numbers are quoted here — run it yourself against your own docs. Bundled scenarios: react-native (facebook/react-native), supabase-js (supabase/supabase-js), and astro (withastro/docs).

Telemetry

DocGraph collects, stores, and transmits no telemetry or usage data of any kind. See TELEMETRY.md for the full policy. Every event — index start, vector-search warning, source fetch, MCP request — is written as a structured JSON-Lines entry to .docgraph/docgraph.log and rotated locally (format reference in LOGGING.md). Nothing leaves the user's machine unless you explicitly configure a cloud embedding provider, in which case only document chunks are sent to that provider to compute embeddings.

docgraph logs                            # last 50 entries
docgraph logs --tail=200 --level=error   # last 200 errors only
docgraph logs --grep="vector"            # entries matching 'vector'
docgraph logs --grep="vector" --follow   # streams new matches live, Ctrl-C to stop
docgraph logs --all                      # list every rotated file
docgraph logs --format=json              # pipe into jq / dashboards

Log format (one JSON object per line, NDJSON / JSON-Lines):

{"ts":"2026-07-03T18:53:36.975Z","level":"info","msg":"embeddings.enabled","ctx":{"provider":"auto","resolvedProvider":"local"}}
{"ts":"2026-07-03T18:53:37.443Z","level":"info","msg":"indexing.complete","ctx":{"component":"indexing","documents":61,"nodes":216,"edges":175,"vectors":828}}

Configure via .docgraph/settings.json:

{
  "logging": {
    "level": "info",                // "error" | "warn" | "info" | "debug"
    "maxBytes": 5242880,            // 5 MB before rotation
    "maxFiles": 3,                  // docgraph.log, .1, .2 retained
    "mirrorStderr": false           // set true or DOCGRAPH_DEBUG=1 to mirror to stderr
  }
}

Level	What you'd see at default info
error	Uncaught exceptions, embedding provider failures, MCP tool errors
warn	Embeddings disabled, malformed config, source fetch failures
info	Index start/complete, source initialised, project loaded, MCP tool calls
debug	Per-request latency, every batch embed, every GraphQL round-trip

Architecture

DocGraph follows Clean Architecture. Dependencies point inward — inner layers know nothing about outer ones — so the core logic is independent of SQLite, HTTP and the file system.

┌──────────────────────────────────────────────────────────────────────────┐
│ presentation/        CLI · MCP server (stdio JSON-RPC) · Installer        │
├──────────────────────────────────────────────────────────────────────────┤
│ container.ts         composition root (wires everything per project)      │
│ project-registry.ts  LRU cache of containers, one per projectPath          │
├──────────────────────────────────────────────────────────────────────────┤
│ application/         IndexingService · SearchService · QueryService       │
│                      (use cases — pullRemoteSources() lives here)         │
├──────────────────────────────────────────────────────────────────────────┤
│ domain/              entities · ports (interfaces) ·                       │
│                      chunker   (no external deps)                          │
├──────────────────────────────────────────────────────────────────────────┤
│ infrastructure/      SQLite store · vector store · embedding providers ·   │
│                      filesystem source · remote sources (Notion, Jira,    │
│                      Obsidian, Confluence, Linear, GitHub) ·               │
│                      file watcher (auto-sync) · config                    │
└──────────────────────────────────────────────────────────────────────────┘

src/
├── domain/                          # Enterprise rules — depends on nothing
│   ├── entities.ts                  #   Document, GraphNode/Edge, SearchResult, ... (Zod)
│   ├── ports.ts                     #   Repository, VectorStore, EmbeddingProvider, ...
│   └── chunker.ts                   #   Pure text-chunking service
├── application/                     # Use cases — depends only on domain
│   ├── indexing-service.ts          #   indexProject, pullRemoteSources, indexRemoteDocument
│   ├── search-service.ts
│   └── query-service.ts
├── infrastructure/                  # Adapters — implement domain ports
│   ├── config/settings.ts           #   DocGraphSettings + sources.sources
│   ├── persistence/                 #   SQLite knowledge store + vector store
│   ├── filesystem/                  #   Document source + multi-format parser
│   ├── embeddings/                  #   Provider factory + local/cloud providers
│   ├── sources/                     #   Remote source adapters (Notion, Jira, Obsidian, ...)
│   └── watch/                       #   Debounced file watcher (auto-sync)
├── presentation/                    # Entry points
│   ├── cli/                         #   Argument parsing + CLI
│   ├── installer/                   #   Native install for all 8 supported agents
│   └── mcp/                         #   MCP server (multi-project, autosync)
├── container.ts                     # Composition root
├── project-registry.ts              # Multi-project LRU
└── index.ts                         # Public library API

The document metadata, knowledge graph, vectors, and remote-source cache all live in a single SQLite database at .docgraph/docgraph.db inside the indexed project.

Development

npm install
npm run build          # compile TypeScript to dist/
npm run typecheck      # type-check without emitting
npm test               # node:test runner, 60+ specs across 12 files
npm run benchmark      # real git-grep/file-scan baseline vs. DocGraph search, see Benchmarks section

Tests use the built-in node:test runner (no test-framework dependency) and cover the domain services, infrastructure adapters, remote sources, multi-project registry, and full end-to-end flows through the composition root.

License

MIT © Junior Carrillo